Background: The immunomodulation of the antitumor response driven by immunocheckpoint inhibitors (ICIs) such as PD-L1 (Programmed Death Ligand-1) monoclonal antibody (alpha-PD-L1) have shown relevant clinical outcomes in a subset of patients. This fact has led to the search for rational combinations with other therapeutic agents such as Doxorubicin (Dox), which cytotoxicity involves an immune activation that may enhance ICI response. Therefore, this study aims to evaluate the combination of chemotherapy and ICI by developing Dox Immunoliposomes functionalized with monovalent-variable fragments (Fab') of alpha-PD-L1. Results: Immunoliposomes were assayed in vitro and in vivo in a B16 OVA melanoma murine cell line over-expressing PD-L1. Here, immune system activation in tumor, spleen and lymph nodes, together with the antitumor efficacy were evaluated. Results showed that immunoliposomes bound specifically to PD-L1(+) cells, yielding higher cell interaction and Dox internalization, and decreasing up to 30-fold the IC50, compared to conventional liposomes. This mechanism supported a higher in vivo response. Indeed, immunoliposomes promoted full tumor regression in 20% of mice and increased in 1 month the survival rate. This formulation was the only treatment able to induce significant (p < 0.01) increase of activated tumor specific cytotoxic T lymphocytes at the tumor site. Conclusion: PD-L1 targeted liposomes encapsulating Dox have proved to be a rational combination able to enhance the modulation of the immune system by blocking PD-L1 and selectively internalizing Dox, thus successfully providing a dual activity offered by both, chemo and immune therapeutic strategies.

Enteric reabsorption occurs when a drug is secreted into the intestinal lumen and reabsorbed into the systemic circulation. This distribution process is evidenced by multiple peaks in pharmacokinetic profiles. Commonly, hepatobiliary drug secretion is assumed to be the underlying mechanism (enterohepatic reabsorption, EHR), neglecting other possible mechanisms such as gastric secretion (enterogastric reabsorption, EGR). In addition, the impact of drug reabsorption on systemic clearance, volume of distribution and bioavailability has been a subject of long-standing discussions. In this work, we propose semi-mechanistic pharmacokinetic models to reflect EHR and EGR and compare their respective impact on primary pharmacokinetic parameters. A simulation-based analysis was carried out considering three drug types with the potential for reabsorption, classified according to their primary route of elimination and their hepatic extraction: (A) hepatic metabolism-low extraction; (B) hepatic metabolism-intermediate/high extraction; (C) renal excretion. Results show that an increase in EHR can significantly reduce the clearance of drugs A and B, increase bioavailability of B drugs, and increase the volume of distribution for all drugs. Conversely, EGR had negligible impact in all pharmacokinetic parameters. Findings provide background to explain and forecast the role that this process can play in pharmacokinetic variability, including drug-drug interactions and disease states.

Background: IMI2-PainCare-BioPain-RCT3 is one of four similarly designed clinical studies aiming at profiling a set of functional biomarkers of drug effects on the nociceptive system that could serve to accelerate the future development of analgesics, by providing a quantitative understanding between drug exposure and effects of the drug on nociceptive signal processing in human volunteers. IMI2-PainCare-BioPain-RCT3 will focus on biomarkers derived from non-invasive electroencephalographic (EEG) measures of brain activity. Methods: This is a multisite single-dose, double-blind, randomized, placebo-controlled, 4-period, 4-way crossover, pharmacodynamic (PD) and pharmacokinetic (PK) study in healthy subjects. Biomarkers derived from scalp EEG measurements (laser-evoked brain potentials [LEPs], pinprick-evoked brain potentials [PEPs], resting EEG) will be obtained before and three times after administration of three medications known to act on the nociceptive system (lacosamide, pregabalin, tapentadol) and placebo, given as a single oral dose in separate study periods. Medication effects will be assessed concurrently in a non-sensitized normal condition and a clinically relevant hyperalgesic condition (high-frequency electrical stimulation of the skin). Patient-reported outcomes will also be collected. A sequentially rejective multiple testing approach will be used with overall alpha error of the primary analysis split between LEP and PEP under tapentadol. Remaining treatment arm effects on LEP or PEP or effects on EEG are key secondary confirmatory analyses. Complex statistical analyses and PK-PD modeling are exploratory. Discussion: LEPs and PEPs are brain responses related to the selective activation of thermonociceptors and mechanonociceptors. Their amplitudes are dependent on the responsiveness of these nociceptors and the state of the pathways relaying nociceptive input at the level of the spinal cord and brain. The magnitude of resting EEG oscillations is sensitive to changes in brain network function, and some modulations of oscillation magnitude can relate to perceived pain intensity, variations in vigilance, and attentional states. These oscillations can also be affected by analgesic drugs acting on the central nervous system. For these reasons, IMI2-PainCare-BioPain-RCT3 hypothesizes that EEG-derived measures can serve as biomarkers of target engagement of analgesic drugs for future Phase 1 clinical trials. Phase 2 and 3 clinical trials could also benefit from these tools for patient stratification.

V937 is an investigational novel oncolytic non-genetically modified Kuykendall strain of Coxsackievirus A21 which is in clinical development for the treatment of advanced solid tumor malignancies. V937 infects and lyses tumor cells expressing the intercellular adhesion molecule I (ICAM-I) receptor. We integrated in vitro and in vivo data from six different preclinical studies to build a mechanistic model that allowed a quantitative analysis of the biological processes of V937 viral kinetics and dynamics, viral distribution to tumor, and anti-tumor response elicited by V937 in human xenograft models in immunodeficient mice following intratumoral and intravenous administration. Estimates of viral infection and replication which were calculated from in vitro experiments were successfully used to describe the tumor response in vivo under various experimental conditions. Despite the predicted high clearance rate of V937 in systemic circulation (t(1/2) = 4.3 min), high viral replication was observed in immunodeficient mice which resulted in tumor shrinkage with both intratumoral and intravenous administration. The described framework represents a step towards the quantitative characterization of viral distribution, replication, and oncolytic effect of a novel oncolytic virus following intratumoral and intravenous administrations in the absence of an immune response. This model may further be expanded to integrate the role of the immune system on viral and tumor dynamics to support the clinical development of oncolytic viruses.

Background Anti-programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1) monoclonal antibodies (mAbs) show remarkable clinical anti-tumour efficacy. However, rational combinations are needed to extend the clinical benefit to primary resistant tumours. The design of such combinations requires the identification of the kinetics of critical immune cell populations in the tumour microenvironment. Methods In this study, we compared the kinetics of immune cells in the tumour microenvironment upon treatment with immunotherapy combinations with different anti-tumour efficacies in the non-inflamed tumour model TC-1/A9. Tumour-bearing C57BL/6J mice were treated with all possible combinations of a human papillomavirus (HPV) E7 long peptide, polyinosinic-polycytidylic acid (PIC) and anti-PD-1 mAb. Tumour growth and kinetics of the relevant immune cell populations were assessed over time. The involvement of key immune cells was confirmed by depletion with mAbs and immunophenotyping with multiparametric flow cytometry. Results The maximum anti-tumour efficacy was achieved after intratumoural administration of HPV E7 long peptide and PIC combined with the systemic administration of anti-PD-1 mAb. The intratumoural immune cell kinetics of this combination was characterised by a biphasic immune response. An initial upsurge of proinflammatory myeloid cells led to a further rise in effector CD8(+) T lymphocytes at day 8. Depletion of either myeloid cells or CD8(+) T lymphocytes diminished the anti-tumour efficacy of the combination. Conclusions The anti-tumour efficacy of a successful immunotherapy combination in a non-inflamed tumour model relies on an early inflammatory process that remodels the myeloid cell compartment.

Simple Summary: The clinical efficacy of immunotherapies when treating cold tumors is still low, and different treatment combinations are needed when dealing with this challenging scenario. In this work, a middle-out strategy was followed to develop a model describing the antitumor efficacy of different immune-modulator combinations, including an antigen, a toll-like receptor-3 agonist, and an immune checkpoint inhibitor in mice treated with non-inflamed tumor cells. Our results support that clinical response requires antigen-presenting cell activation and also relies on the amount of CD8 T cells and tumor resistance mechanisms present. This mathematical model is a very useful platform to evaluate different immuno-oncology combinations in both preclinical and clinical settings. Immune checkpoint inhibitors, administered as single agents, have demonstrated clinical efficacy. However, when treating cold tumors, different combination strategies are needed. This work aims to develop a semi-mechanistic model describing the antitumor efficacy of immunotherapy combinations in cold tumors. Tumor size of mice treated with TC-1/A9 non-inflamed tumors and the drug effects of an antigen, a toll-like receptor-3 agonist (PIC), and an immune checkpoint inhibitor (anti-programmed cell death 1 antibody) were modeled using Monolix and following a middle-out strategy. Tumor growth was best characterized by an exponential model with an estimated initial tumor size of 19.5 mm(3) and a doubling time of 3.6 days. In the treatment groups, contrary to the lack of response observed in monotherapy, combinations including the antigen were able to induce an antitumor response. The final model successfully captured the 23% increase in the probability of cure from bi-therapy to triple-therapy. Moreover, our work supports that CD8(+) T lymphocytes and resistance mechanisms are strongly related to the clinical outcome. The activation of antigen-presenting cells might be needed to achieve an antitumor response in reduced immunogenic tumors when combined with other immunotherapies. These models can be used as a platform to evaluate different immuno-oncology combinations in preclinical and clinical scenarios.

Purpose Both inter-individual (IIV) and inter-occasion (IOV) variabilities are observed in bioequivalence studies. High IOV may be a cause of problems on the demonstration of bioequivalence, despite strict measures are taken to control it. The objective of this study is to investigate further means of controlling IIV by optimizing study design of crossover studies. Methods Data from 18 bioequivalence studies were used to develop population pharmacokinetics (popPK) models to characterize the absorption and disposition processes of 14 drugs, to estimate IOV for each drug substance and to evaluate possible correlations with biopharmaceutical properties of drug substances, classified in accordance to the Biopharmaceutics Drug Disposition Classification System (BDDCS). Results Plasma-pharmacokinetics profiles for the 14 drugs analyzed were successfully described using popPK. The pharmacokinetic parameters that showed greater variability were first-order rate constant of absorption, duration of the zero-order absorption process, relative bioavailability and time of latency. ISCV% estimated for C-max seems to correlate with the log-DoseNumber for Class 1, 2 and 3, despite no direct correlation was observed between popPK model residual variability (RUV) and ISCV%. Nevertheless, higher RUV estimates were observed for Class 2 drugs in comparison to Class 1 and 3. Conclusion Pharmacokinetic parameters related to drug absorption showed greater variability. Ingestion of the IMP along with 240 mL of water showed to standardize gastric emptying. Given the dependency between C-max variability and dose-solubility ratio, for classes 2 and 4, ad libitum water intake may increase C(max )and AUC ISCV%. A water ingestion standardization until the expected T-max of the drug is suggested.

Crohn's disease (CD) is a complex inflammatory bowel disease whose pathogenesis appears to involve several immunologic defects causing functional impairment of the gut. Its complexity and the reported loss of effectiveness over time of standard of care together with the increase in its worldwide incidence require the application of techniques aiming to find new therapeutic strategies. Currently, systems pharmacology modeling has been gaining importance as it integrates the available knowledge of the system into a single computational model. In this work, the following workflow for robust application of systems pharmacology modeling was followed: 1) scope definition; 2) species selection and circulating plasma levels based on a search in the literature; 3) representation of model topology and parametrization of the interactions, after literature data extraction and curation, and the implementation of ordinary differential equations in SimBiology (MATLAB version R2018b); and 4) model curation and evaluation by visual comparison of simulated interleukin (IL) concentrations with the reported levels in plasma, and sensitivity analysis performed to confirm model robustness and identify the most influential parameters. Finally, 5) exposure to two dose levels of recombinant human IL10 was evaluated by simulation and comparison with reported clinical study results. In summary, we present a quantitative systems pharmacology model for the main ILs involved in CD developed using a standardized methodology and supported by a comprehensive repository summarizing the most relevant literature in the field. However, it has to be taken into account that external validation is still pending as available clinical data were primarily used for model training. SIGNIFICANCE STATEMENT Crohn's disease (CD) is a complex heterogeneous inflammatory bowel disorder. Systems pharmacology modeling offers a great opportunity for integration of the available knowledge on the disease using a computational framework. As a result of this work, a comprehensive repository along with a quantitative systems pharmacology model for the main interleukins involved in CD is provided. This model is useful for the in silico evaluation of biomarkers and potential therapeutic targets and can be adapted to address research gaps regarding CD.

Background and Purpose Acute intermittent porphyria (AIP) results from haplo-insufficiency of the porphobilinogen deaminase (PBGD) gene encoding the third enzyme in the haem biosynthesis pathway. As liver is the main organ of pathology for AIP, emerging therapies that restore enzyme hepatic levels are appealing. The objective of this work was to develop a mechanistic-based computational framework to describe the effects of novel PBGD mRNA therapy on the accumulation of neurotoxic haem precursors in small and large animal models. Experimental Approach Liver PBGD activity data and/or 24-hr urinary haem precursors were obtained from genetic AIP mice and wild-type mice, rats, rabbits, and macaques. To mimic acute attacks, porphyrogenic drugs were administered over one or multiple challenges, and animals were used as controls or treated with different PBGD mRNA products. Available experimental data were sequentially used to build and validate a semi-mechanistic mathematical model using non-linear mixed-effects approach. Key Results The developed framework accounts for the different biological processes involved (i.e., mRNA sequence, release from lipid nanoparticle and degradation, mRNA translation, increased PBGD activity in liver, and haem precursor metabolism) in a simplified mechanistic fashion. The model, validated using external data, shows robustness in the extrapolation of PBGD activity data in rat, rabbit, and non-human primate species. Conclusion and Implications This quantitative framework provides a valuable tool to compare PBGD mRNA drug products during early preclinical stages, optimize the amount of experimental data required, and project results to humans, thus supporting drug development and clinical dose and dosing regimen selection.

Background: Ceftolozane-tazobactam is a new antibiotic against multidrug-resistant pathogens such as Pseudomonas aeruginosas. Ceftolozane-tazobactam dosage is still uncertain in children, especially in those with renal impairment or undergoing continuous renal replacement therapy (CRRT). Methods: Evaluation of different ceftolozane-tazobactam dosing regimens in three critically ill children. Ceftolozane pharmacokinetics (PK) were characterized by obtaining the patient's specific parameters by Bayesian estimation based on a population PK model. The clearance (CL) in patient C undergoing CRRT was estimated using the prefilter, postfilter, and ultrafiltrate concentrations simultaneously. Variables such as blood, dialysate, replacement, and ultrafiltrate flow rates, and hematocrit were integrated in the model. All PK analyses were performed using NONMEM v.7.4. Results: Patient A (8 months of age, 8.7 kg) with normal renal function received 40 mg/kg every 6 h: renal clearance (CLR) was 0.88 L/h; volume of distribution (Vd) Vd(1) = 3.45 L, Vd(2) = 0.942 L; terminal halflife (t(1/2,beta)) = 3.51 h, dosing interval area under the drug concentration vs. time curve at steady-state (AUC(tau,SS)) 397.73 mg x h x L-1. Patient B (19 months of age, 11 kg) with eGFR of 22 mL/min/1.73 m(2) received 36 mg/kg every 8 h: CLR = 0.27 L/h; Vd(1) = 1.13 L; Vd(2) = 1.36; t(1/2,beta) = 6.62 h; AUC(SS) 1481.48 mg x h x L-1. Patient C (9 months of age, 5.8 kg), with severe renal impairment undergoing CRRT received 30 mg/kg every 8 h: renal replacement therapy clearance (CLRRT) 0.39 L/h; Vd(1 =) 0.74 L; Vd(2=) 1.17; t (1/2,beta =) 3.51 h; AUC(tau,SS) 448.72 mg x h x L-1. No adverse effects attributable to antibiotic treatment were observed. Conclusions: Our results suggest that a dose of 35 mg/kg every 8 h can be appropriate in critically ill septic children with multi-drug resistance Pseudomonas aeruginosa infections. A lower dose of 10 mg/kg every 8 h could be considered for children with severe AKI. For patients with CRRT and a high effluent rate, a dose of 30 mg/kg every 8 h can be considered.

Total tumor size (TS) metrics used in TS models in oncology do not consider tumor heterogeneity, which could help to better predict drug efficacy. We analyzed individual target lesions (iTLs) of patients with metastatic colorectal carcinoma (mCRC) to determine differences in TS dynamics by using the ClassIfication Clustering of Individual Lesions (CICIL) methodology. Results from subgroup analyses comparing genetic mutations and TS metrics were assessed and applied to survival analyses. Data from four mCRC clinical studies were analyzed (1781 patients, 6369 iTLs). CICIL was used to assess differences in lesion TS dynamics within a tissue (intra-class) or across different tissues (inter-class). First, lesions were automatically classified based on their location. Cross-correlation coefficients (CCs) determined if each pair of lesions followed similar or opposite dynamics. Finally, CCs were grouped by using the K-means clustering method. Heterogeneity in tumor dynamics was lower in the intra-class analysis than in the inter-class analysis for patients receiving cetuximab. More tumor heterogeneity was found in KRAS mutated patients compared to KRAS wild-type (KRASwt) patients and when using sum of longest diameters versus sum of products of diameters. Tumor heterogeneity quantified as the median patient's CC was found to be a predictor of overall survival (OS) (HR = 1.44, 95% CI 1.08-1.92), especially in KRASwt patients. Intra- and inter-tumor tissue heterogeneities were assessed with CICIL. Derived metrics of heterogeneity were found to be a predictor of OS time. Considering differences between lesions' TS dynamics could improve oncology models in favor of a better prediction of OS.

The aim of this work is to build a mechanistic multiscale pharmacokinetic model for the anticancer drug 2',2'-difluorodeoxycytidine (gemcitabine, dFdC), able to describe the concentrations of dFdC metabolites in the pancreatic tumor tissue in dependence of physiological and genetic patient characteristics, and, more in general, to explore the capabilities and limitations of this kind of modeling strategy. A mechanistic model characterizing dFdC metabolic pathway (metabolic network) was developed using in vitro literature data from two pancreatic cancer cell lines. The network was able to describe the time course of extracellular and intracellular dFdC metabolites concentrations. Moreover, a physiologically-based pharmacokinetic model was developed to describe clinical dFdC profiles by using enzymatic and physiological information available in the literature. This model was then coupled with the metabolic network to describe the dFdC active metabolite profile in the pancreatic tumor tissue. Finally, global sensitivity analysis was performed to identify the parameters that mainly drive the interindividual variability for the area under the curve (AUC) of dFdC in plasma and of its active metabolite (dFdCTP) in tumor tissue. From this analysis, cytidine deaminase (CDA) concentration was identified as the main driver of plasma dFdC AUC interindividual variability, whereas CDA and deoxycytidine kinase concentration mainly explained the tumor dFdCTP AUC variability. However, the lack of in vitro and in vivo information needed to characterize key model parameters hampers the development of this kind of mechanistic approach. Further studies to better characterize pancreatic cell lines and patient enzymes polymorphisms are encouraged to refine and validate the current model.

Over the past decade, the insulin-like growth factor (IGF)-signaling pathway has gained substantial interest as potential therapeutic target in oncology. Xentuzumab, a humanized IgG1 monoclonal antibody, binds to IGF-I and IGF-II thereby inhibiting the downstream signaling essential for survival and tumor growth. This pathway is further regulated by circulating IGF binding proteins (IGFBPs). In this work, a mechanistic model characterizing the dynamics and interactions of IGFs, IGFBPs, and Xentuzumab has been developed to guide dose selection. Therefore, in vitro and in vivo literature information was combined with temporal IGF-I, IGF-II, and IGFBP-3 total plasma concentrations from two phase I studies. Based on the established quantitative framework, the time-course of free IGFs as ultimate drug targets not measured in clinics was predicted. Finally, a dose of 1000 mg/week-predicted to reduce free IGF-I and free IGF-II at steady-state by at least 90% and 64%, respectively-was suggested for phase II.

Aims Busulfan and treosulfan are cytotoxic agents used in the conditioning regime prior to paediatric haematopoietic stem cell transplantation (HSCT). These agents cause suppression of myeloid cells leaving patients severely immunocompromised in the early post-HSCT period. The main objectives were: (i) to establish a mechanistic pharmacokinetic-pharmacodynamic (PKPD) model for the treatment and engraftment effects on neutrophil counts comparing busulfan and treosulfan-based conditioning, and (ii) to explore current dosing schedules with respect to time to HSCT. Methods Data on 126 patients, 72 receiving busulfan (7 months-18 years, 5.1-47.0 kg) and 54 treosulfan (4 months-17 years, 3.8-35.8 kg), were collected. In total, 8935 neutrophil count observations were recorded during the study period in addition to drug concentrations to develop a mechanistic PKPD model. Absolute neutrophil count profiles were modelled semimechanistically, accounting for transplant effects and differing set points pre- and post-transplant. Results PK were best described by 2-compartment models for both drugs. The Friberg semimechanistic neutropenia model was applied with a linear model for busulfan and a maximum efficacy model for treosulfan describing drug effects at various stages of neutrophil maturation. System parameters were consistent across both drugs. The HSCT was represented by an amount of progenitor cells enhancing the neutrophils' proliferation and maturation compartments. Alemtuzumab was found to enhance the proliferative rate under which the absolute neutrophil count begin to grow after HSCT. Conclusion A semimechanistic PKPD model linking exposure to either busulfan or treosulfan to the neutrophil reconstitution dynamics was successfully built. Alemtuzumab coadministration enhanced the neutrophil proliferative rate after HSCT. Treosulfan administration was suggested to be delayed with respect to time to HSCT, leaving less time between the end of the administration and stem cell infusion.

Identification of optimal schedules for combination drug administration relies on accurately estimating the correct pharmacokinetics, pharmacodynamics, and drug interaction effects. Misspecification of pharmacokinetics can lead to wrongly predicted timing or order of treatments, leading to schedules recommended on the basis of incorrect assumptions about absorption and elimination of a drug and its effect on tumor growth. Here, we developed a computational modeling platform and software package for combination treatment strategies with flexible pharmacokinetic profiles and multidrug interaction curves that are estimated from data. The software can be used to compare prespecified schedules on the basis of the number of resistant cells where drug interactions and pharmacokinetic curves can be estimated from user-provided data or models. We applied our approach to publicly available in vitro data of treatment with different tyrosine kinase inhibitors of BT-20 triple-negative breast cancer cells and of treatment with erlotinib of PC-9 non-small cell lung cancer cells. Our approach is publicly available in the form of an R package called ACESO ( https://github.com/Michorlab/aceso) and can be used to investigate optimum dosing for any combination treatment. Significance: These findings introduce a computational modeling platform and software package for combination treatment strategies with flexible pharmacokinetic profiles and multidrug interaction curves that are estimated from data.

Advanced melanoma remains a disease with poor prognosis. Several serologic markers have been investigated to help monitoring and prognostication, but to date only lactate dehydrogenase (LDH) has been validated as a standard prognostic factor biomarker for this disease by the American Joint Committee on Cancer. In this work, we built a semi-mechanistic model to explore the relationship between the time course of several circulating biomarkers and overall or progression free survival in advanced melanoma patients treated with adjuvant high-dose interferon-alpha 2b. Additionally, due to the adverse interferon tolerability, a semi-mechanistic model describing the side effects of the treatment in the absolute neutrophil counts is proposed in order to simultaneously analyze the benefits and toxic effects of this treatment. The results of our analysis suggest that the relative change from baseline of LDH was the most significant predictor of the overall survival of the patients. Unfortunately, there was no significant difference in the proportion of patients with elevated serum biomarkers between the patients who recurred and those who remained free of disease. Still, we believe that the modelling framework presented in this work of circulating biomarkers and adverse effects could constitute an additional strategy for disease monitoring in advance melanoma patients.

This study investigated plasma and brain disposition of quetiapine lipid core nanocapsules (QLNC) in naive and schizophrenic (SCZ-like) rats and developed a semimechanistic model to describe changes in both compartments following administration of the drug in solution (FQ) or nanoencapsulated. QLNC (1 mg/ml) presented 166 +/- 39 nm, low polydispersity, and high encapsulation (93.0% +/- 1.4%). A model was built using experimental data from total and unbound plasma and unbound brain concentrations obtained by microdialysis after administration of single intravenous bolus dose of FQ or QLNC to naive and SCZ-like rats. A two-compartment model was identifiable both in blood and in brain with a bidirectional drug transport across the blood-brain barrier (CLin, and CLout). SCZ-like rats' significant decrease in brain exposure with FQ (decrease in CLin) was reverted by QLNC, showing that nanocarriers govern quetiapine tissue distribution. Model simulations allowed exploring the potential of LNC for brain delivery. SIGNIFICANCE STATEMENT A population approach was used to simultaneously model total and unbound plasma and unbound brain quetiapine concentrations allowing for quantification of the rate and extent of the drug's brain distribution following administration of both free drug in solution or as nanoformulation to naive and SCZ-like rats. The model-based approach is useful to better understand the possibilities and limitations of this nanoformulation for drug delivering to the brain, opening the opportunity to use this approach to improve SCZ-treatment-limited response rates.

Antibiotic resistance to oral antibiotics recommended for pyelonephritis is increasing. The objective was to determine if there is a pharmacological basis to consider alternative treatments/novel dosing regimens for the oral treatment of pyelonephritis. A systematic review identified pharmacokinetic models of suitable quality for a selection of antibiotics with activity against Escherichia coli. MIC data was obtained for a population of E. coli isolates derived from patients with pyelonephritis. Pharmacokinetic/pharmacodynamic (PK/PD) simulations determined probability of target attainment (PTA) and cumulative fraction response (CFR) values for sub-populations of the E. coli population at varying doses. There are limited high-quality models available for the agents investigated. Pharmacokinetic models of sufficient quality for simulation were identified for amoxicillin, amoxicillin-clavulanic acid, cephalexin, ciprofloxacin, and fosfomycin trometamol. These antibiotics were predicted to have PTAs >= 0.85 at or below standard doses for the tested E. coli population including cephalexin 1500 mg 8 hourly for 22% of the population (MIC <= 4 mg/L) and ciprofloxacin 100 mg 12 hourly for 71% of the population (MIC <= 0.06 mg/L). For EUCAST-susceptible E. coli isolates, doses achieving CFRs >= 0.9 included amoxicillin 2500 mg 8 hourly, cephalexin 4000 mg 6 hourly, ciprofloxacin 200 mg 12 hourly, and 3000 mg of fosfomycin 24 hourly. Limitations in the PK data support carrying out additional PK studies in populations of interest. Oral antibiotics including amoxicillin, amoxicillin-clavulanic acid, and cephalexin have potential to be effective for a proportion of patients with pyelonephritis. Ciprofloxacin may be effective at lower doses than currently prescribed.

Complete remission (CR) after induction therapy is the first treatment goal in acute myeloid leukemia (AML) patients and has prognostic impact. Our purpose is to determine the correlation between the observed CR/CRi rate after idarubicin (IDA) and cytarabine (CYT) 3+ 7 induction and the leukemic chemosensitivity measured by an ex vivo test of drug activity. Bone marrow samples from adult patients with newly diagnosed AML were included in this study. Whole bone marrow samples were incubated for 48 h in well plates containing IDA, CYT, or their combination. Pharmacological response parameters were estimated using population pharmacodynamic models. Patients attaining a CR/CRi with up to two induction cycles of 3+ 7 were classified as responders and the remaining as resistant. A total of 123 patients fulfilled the inclusion criteria and were evaluable for correlation analyses. The strongest clinical predictors were the area under the curve of the concentration response curves of CYT and IDA. The overall accuracy achieved using MaxSpSe criteria to define positivity was 81%, predicting better responder (93%) than non-responder patients (60%). The ex vivo test provides better yet similar information than cytogenetics, but can be provided before treatment representing a valuable in-time addition. After validation in an external cohort, this novel ex vivo test could be useful to select AML patients for 3+ 7 regimen vs. alternative schedules.

AimsImmunotherapy is a rising alternative to traditional treatment in breast cancer (BC) patients in order to transform cold into hot immune enriched tumours and improve responses and outcome. A computational modelling approach was applied to quantify modulation effects of immunotherapy and chemotherapy response on tumour shrinkage and progression-free survival (PFS) in naive BC patients. MethodsEighty-three Her2-negative BC patients were recruited for neoadjuvant chemotherapy with or without immunotherapy based on dendritic cell vaccination. Sequential tumour size measurements were modelled using nonlinear mixed effects modelling and linked to PFS. Data from another set of patients (n=111) were used to validate the model. ResultsTumour size profiles over time were linked to biomarker dynamics and PFS. The immunotherapy effect was related to tumour shrinkage (P < .05), with the shrinkage 17% (95% confidence interval: 2-23%) being higher in vaccinated patients, confirmed by the finding that pathological complete response rates in the breast were higher in the vaccinated compared to the control group (25.6% vs 13.6%; P=.04). The whole tumour shrinkage time profile was the major prognostic factor associated to PFS (P < .05), and therefore, immunotherapy influences indirectly on PFS, showing a trend in decreasing the probability of progression with increased vaccine effects. Tumour subtype was also associated with PFS (P < .05), showing that luminal A BC patients have better prognosis. ConclusionsDendritic cell-based immunotherapy is effective in decreasing tumour size. The semi-mechanistic validated model presented allows the quantification of the immunotherapy treatment effects on tumour shrinkage and establishes the relationship between the dynamics of tumour size and PFS.

Standard bolus-dosed antibiotic prophylaxis may not inhibit growth of antibiotic resistant colonic bacteria, a cause of SSIs after colorectal surgery. An alternative strategy is continuous administration of antibiotic throughout surgery, maintaining concentrations of antibiotics that inhibit growth of resistant bacteria. This study is a pilot comparing bolus-continuous infusion with bolus-dosed cefuroxime prophylaxis in colorectal surgery. This is a pilot randomised controlled trial in which participants received cefuroxime bolus-infusion (intervention arm) targeting free serum cefuroxime concentrations of 64mg/L, or 1.5g cefuroxime as a bolus dose four-hourly (standard arm). Patients in both arms received metronidazole (500mg intravenously). Eligible participants were adults undergoing colorectal surgery expected to last for over 2h. Results were analysed on an intention-to-treat basis. The study was successfully piloted, with 46% (90/196) of eligible patients recruited and 89% (80/90) of participants completing all components of the protocol. A trialled bolus-continuous dosing regimen was successful in maintaining free serum cefuroxime concentrations of 64mg/L. No serious adverse reactions were identified. Rates of SSIs (superficial and deep SSIs) were lower in the intervention arm than the standard treatment arm (24% (10/42) vs. 30% (13/43)), as were infection within 30days of operation (41% (17/43) vs 51% (22/43)) and urinary tract infections (2% (1/42) vs. 9% (4/43)). Th

Introduction. Acute intermittent porphyria (AIP) is characterized by hepatic over-production of the heme precursors when aminolevulinic acid (ALA)-synthase 1 is induced by endogenous or environmental factors. The aim of this study was to develop a semi-mechanistic computational model to characterize urine accumulation of heme precursors during acute attacks based on experimental pharmacodynamics data and support the development of new therapeutic strategies. Methods: Male AIP mice received recurrent phenobarbital challenge starting on days 1, 9, 16 and 30. 24-h urine excretion of ALA, porphobilinogen (PBG) and porphyrins from challenges Dl, D9 and D30 constituted the training data set to build the mechanistic model using the population approach. In a second study, porphyrin and porphyrin precursor excretion from challenge D16 were used as a validation data set. Results: The computational model presented the following features: (i) urinary excretion of ALA, PBG and porphyrins was governed by unmeasured circulating heme precursor amounts, (ii) the circulating amounts of ALA and PBG were the precursors of circulating amounts of PBG and porphyrins, respectively, and (iii) the phenobarbital effect linearly increased the synthesis of circulating ALA and PBG levels. The model displayed good parameter precision (coefficient of variation below 32% in all parameters), and adequately described the experimental data. Finally, a theoretical hemin effect was implemented to illustrate the applicability of the model to dosage optimization in drug therapies. Conclusions: A semi-mechanistic disease model was successfully developed to describe the temporal evolution of urinary heme precursor excretion during recurrent biochemical-induced acute attacks in AIP mice. This model represents the first computational approach to explore and optimize current and new therapies.

This report provides a brief description of the 2018 Red Iberoamericana de Farmacometria (RedIF) Congress that took place in Guadalajara (Mexico) on November 7-9, 2018. The meeting aimed to foster modeling and simulation (M&S) approaches for drug development, regulatory sciences, and clinical application in Latin America. The organizations that cosponsored the meeting were the following: University of Guadalajara, International Society of Pharmacometrics (ISoP), International Pharmaceutical Federation (FIP), Clinic of Chronic Diseases and Special Procedures (CECyPE), Zurich Pharma, Pharmet (Pharmometrica), Lixoft, and ICON.

The liver is a well-known immunotolerogenic environment, which provides the adequate setting for liver infectious pathogens persistence such as the hepatitis B virus (HBV). Consequently, HBV infection can derive in the development of chronic disease in a proportion of the patients. If this situation persists in time, chronic hepatitis B (CHB) would end in cirrhosis, hepatocellular carcinoma and eventually, the death of the patient. It is thought that this immunotolerogenic environment is the result of complex interactions between different elements of the immune system and the viral biology. Therefore, the purpose of this work is to unravel the mechanisms implied in the development of CHB and to design a tool able to help in the study of adequate therapies. Firstly, a conceptual framework with the main components of the immune system and viral dynamics was constructed providing an overall insight on the pathways and interactions implied in this disease. Secondly, a review of the literature was performed in a modular fashion: (i) viral dynamics, (ii) innate immune response, (iii) humoral and (iv) cellular adaptive immune responses and (v) tolerogenic aspects. Finally, the information collected was integrated into a single topological representation that could serve as the plan for the systems pharmacology model architecture. This representation can be considered as the previous unavoidable step to the construction of a quantitative model that could assist in biomarker and target identification, drug design and development, dosing optimization and disease progression analysis.

Background Perioperative chemotherapy (CT) or neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced gastric (GC) or gastroesophageal junction cancer (GEJC) has been shown to improve survival compared to an exclusive surgical approach. However, most patients retain a poor prognosis due to important relapse rates. Population pharmacokinetic-pharma-codynamic (PK/PD) modeling may allow identifying at risk-patients. We aimed to develop a mechanistic PK/PD model to characterize the relationship between the type of neoadjuvant therapy, histopathologic response and survival times in locally advanced GC and GEJC patients. Methods Patients with locally advanced GC and GEJC treated with neoadjuvant CT with or without preoperative CRT were analyzed. Clinical response was assessed by CT-scan and EUS. Pathologic response was defined as a reduction on pTNM stage compared to baseline cTNM. Metastasis development risk and overall survival (OS) were described using the population approach with NONMEM 7.3. Model evaluation was performed through predictive checks. Results A low correlation was observed between clinical and pathologic TNM stage for both T (R = 0.32) and N (R = 0.19) categories. A low correlation between clinical and pathologic response was noticed (R = -0.29). The OS model adequately described the observed survival rates. Disease recurrence, cTNM stage >= 3 and linitis plastica absence, were correlated to a higher risk of death. Conclusion Our model adequately described clinical response profiles, though pathologic response could not be predicted. Although the risk of disease recurrence and survival were linked, the identification of alternative approaches aimed to tailor therapeutic strategies to the individual patient risk warrants further research.

In a recent multicenter population pharmacokinetic study of ciprofloxacin administered to children suffering from complicated urinary tract infection (cUTI), the apparent volume of distribution (V) and total plasma clearance (CL) were decreased by 83.6% and 41.5% respectively, compared to healthy children. To understand these differences, a physiologically-based pharmacokinetic model (PBPK) for ciprofloxacin was developed for cUTI children. First, a PBPK model in adults was developed, modified incorporating age-dependent functions and evaluated with paediatric data generated from a published model in healthy children. Then, the model was then adapted to a cUTI paediatric population according to the degree of renal impairment (KF) affecting renal clearance (CLRenal,) and CYP1A2 clearance (CLCYP1A2). Serum and urine samples obtained from 22 cUTI children were used for model evaluation. Lastly, a parameter sensitivity analysis identified the most influential parameters on V and CL. The PBPK model predicted the ciprofloxacin exposure in adults and children, capturing age-related pharmacokinetic changes. Plasma concentrations and fraction excreted unchanged in urine (f(e)) predictions improved in paediatric cUTI patients once CLrenal and CLCYP1A2 were corrected by KF. The presented PBPK model for ciprofloxacin demonstrates its adequacy to simulate different dosing scenarios to obtain PK predictions in a healthy population from 3 months old onwards. Model adaptation of CLRenal and CLCYP1A2 according to KF explained partially the differences seen in the plasma drug concentrations and f(e) vs time profiles between healthy and cUTI children. Nevertheless, it is necessary to further investigate the disease-related changes in cUTI to improve model predictions.

Background and Objectives Lurbinectedin is an inhibitor of RNA polymerase II currently under clinical development for intravenous administration as a single agent and in combination with other anti-tumor agents for the treatment of several tumor types. The objective of this work was to develop a population-pharmacokinetic model in this patient setting and to elucidate the main predictors to guide the late stages of development. Methods Data from 443 patients with solid and hematologic malignancies treated in six phase I and three phase II trials with lurbinectedin as a single agent or combined with other agents were included in the analysis. The potential influence of demographic, co-treatment, and laboratory characteristics on lurbinectedin pharmacokinetics was evaluated. Results The final population-pharmacokinetic model was an open three-compartment model with linear distribution and linear elimination from the central compartment. Population estimates for total plasma clearance, and apparent volume at steady state were 11.2 L/h and 438 L, respectively. Inter-individual variability was moderate for all parameters, ranging from 20.9 to 51.2%. High alpha-1-acid glycoprotein and C-reactive protein, and low albumin reduced clearance by 28, 20, and 20%, respectively. Co-administration of cytochrome P450 3A inhibitors reduced clearance by 30%. Combinations with other anti-tumor agents did not modify the pharmacokinetics of lurbinectedin significantly. Conclusion The population-pharmacokinetic model indicated neither a dose nor time dependency, and no clinically meaningful pharmacokinetic differences were found when co-administered with other anticancer agents. A chronic inflammation pattern characterized by decreased albumin and increased C-reactive protein and alpha-1-acid glycoprotein levels led to high lurbinectedin exposure. Co-administration of cytochrome P450 3A inhibitors increased lurbinectedin exposure.

ObjectivesTo evaluate the relationship between pharmacokinetic descriptors of dexmedetomidine (predicted area under the curve during the procedure, predicted plasma level at the end of the procedure, and duration of procedure) and sedation depth (proportion of time with bispectral index <85 during the procedure) with recovery time after ambulatory procedures.Materials and methodsClinical observational study of patients undergoing oral and maxillofacial ambulatory surgery with dexmedetomidine as sole sedative agent. Patients received a loading dose of dexmedetomidine (0.25-1gkg(-1)) followed by a maintenance infusion (0.2-1.4gkg(-1)h(-1)) to keep a bispectral index <85 until 5min before the end of the procedure, and were transferred to a post-anesthesia care unit until criteria for discharge were met.ResultsData from 75 patients was analyzed. Sedation depth was directly associated with recovery time (Pearson correlation coefficient [r]=0.26; p=0.024). Around 7% of the variation in recovery time was explained by the proportion of time with bispectral index <85. No association with procedure duration (r=0.01; p=0.9), predicted area under the curve (r=0.1; p=0.4), or predicted plasma level of dexmedetomidine at the end of the procedure (r=0.12; p=0.3) with recovery time was observed.ConclusionsSedation depth with dexmedetomidine could play a role in increasing recovery time after oral and maxillofacial ambulatory surgery. In our study, the pharmacokinetic descriptors of dexmedetomidine did not seem to influence recovery time.Clinical relevanceSedation depth with dexmedetomidine could play a role in increasing recovery time after ambulatory procedures.

The aim of this evaluation was to predict tumour response to gemcitabine in patients with advanced pancreas or ovarian cancer using pre-clinical data obtained from xenograft tumour-bearing mice. The approach consisted of building a translational model combining pre-clinical pharmacokinetic-pharmacodynamic (PKPD) models and parameters, with dosing paradigms used in the clinics along with clinical PK models to derive tumour profiles in humans driving overall survival. Tumour growth inhibition simulations were performed using drug effect parameters obtained from mice, system parameters obtained from mice after appropriate scaling, patient PK models for gemcitabine and carboplatin, and the standard dosing schedules given in the clinical scenario for both types of cancers. Tumour profiles in mice were scaled by body weight to their equivalent values in humans. As models for survival in humans showed that tumour size was the main driver of the hazard rate, it was possible to describe overall survival in pancreatic and ovarian cancer patients. Simulated tumour dynamics in pancreatic and ovarian cancer patients were evaluated using available data from clinical trials. Furthermore, calculated metrics showed values (maximal tumour regression [0-17%] and tumour size ratio at week 12 with respect to baseline [-9, -4.5]) in the range of those predicted with the clinical PKPD models. The model-informed Drug Discovery and Development paradigm has been successfully applied retrospectively to gemcitabine data, through a semi-mechanistic translational approach, describing the time course of the tumour response in patients from pre-clinical studies.

Motivation The literature on complex diseases is abundant but not always quantitative. This is particularly so for Inflammatory Bowel Disease (IBD), where many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. We propose the elaboration and validation of a logic network for IBD able to capture the information available in the literature that will facilitate the identification/validation of therapeutic targets. Results In this article, we propose a logic model for Inflammatory Bowel Disease (IBD) which consists of 43 nodes and 298 qualitative interactions. The model presented is able to describe the pathogenic mechanisms of the disorder and qualitatively describes the characteristic chronic inflammation. A perturbation analysis performed on the IBD network indicates that the model is robust. Also, as described in clinical trials, a simulation of anti-TNF alpha, anti-IL2 and Granulocyte and Monocyte Apheresis showed a decrease in the Metalloproteinases node (MMPs), which means a decrease in tissue damage. In contrast, as clinical trials have demonstrated, a simulation of anti-IL17 and anti-IFN gamma or IL10 overexpression therapy did not show any major change in MMPs expression, as corresponds to a failed therapy. The model proved to be a promising in silico tool for the evaluation of potential therapeutic targets, the identification of new IBD biomarkers, the integration of IBD polymorphisms to anticipate responders and non-responders and can be reduced and transformed in quantitative model/s.

A semi-physiological two compartment pharmacokinetic model with two active metabolites (primary (PM) and secondary metabolites (SM)) with saturable and non-saturable pre-systemic efflux transporter, intestinal and hepatic metabolism has been developed. The aim of this work is to explore in several scenarios which analyte (parent drug or any of the metabolites) is the most sensitive to changes in drug product performance (i.e. differences in in vivo dissolution) and to make recommendations based on the simulations outcome. A total of 128 scenarios (2 Biopharmaceutics Classification System (BCS) drug types, 2 levels of K-M Pgp, in 4 metabolic scenarios at 2 dose levels in 4 quality levels of the drug product) were simulated for BCS class II and IV drugs. Monte Carlo simulations of all bioequivalence studies were performed in NONMEM 7.3. Results showed the parent drug (PD) was the most sensitive analyte for bioequivalence trials in all the studied scenarios. PM and SM revealed less or the same sensitivity to detect differences in pharmaceutical quality as the PD. Another relevant result is that mean point estimate of C-max and AUC methodology from Monte Carlo simulations allows to select more accurately the most sensitive analyte compared to the criterion on the percentage of failed or successful BE studies, even for metabolites which frequently show greater variability than PD.

Numerous problems encountered in computational biology can be formulated as optimization problems. In this context, optimization of drug release characteristics or dosing schedules for anticancer agents has become a prominent area not only for the development of new drugs, but also for established drugs. However, in complex systems, optimization of drug exposure is not a trivial task and cannot be efficiently addressed through trial-error simulation exercises. Finding a solution to those problems is a challenging task which requires more advanced strategies like optimal control theory. In this work, we perform an optimal control analysis on a previously developed computational model for the testosterone effects of triptorelin in prostate cancer patients with the goal of finding optimal drug-release characteristics. We demonstrate how numerical control optimization of non-linear models can be used to find better therapeutic approaches in order to improve the final outcome of the patients.

Background Volasertib, a potent and selective polo-like kinase inhibitor, has shown to increase response rates and improve survival with a clinically manageable safety profile, administered alone and in combination with cytarabine in patients with acute myeloid leukaemia. Objectives The objectives of this analysis were to describe the pharmacokinetics of volasertib and cytarabine, administered as single agents or in combination. Methods Three thousand, six hundred and six plasma volasertib concentrations from 501 patients receiving either volasertib alone, or in combination with cytarabine, and 826 plasma cytarabine concentrations from 650 patients receiving cytarabine as multiple subcutaneous injections per cycle either alone, or in combination with volasertib, were analysed using NONMEM Version 7.3. Covariates evaluated included demographic and disease-related parameters. Results The pharmacokinetics of volasertib were found to be dose independent from 150 to 550 mg. Body surface area and ethnicity showed significant effects in all the patients. This is reflected as an increase in drug exposure for Japanese patients, although this finding has to be interpreted with caution because only 7% of patients were part of that population group. Volasertib showed low-to-mild inter-individual variability in total clearance. For the case of cytarabine, its pharmacokinetics was affected by body surface area. Finally, volasertib and cytarabine did not influence the pharmacokinetic characteristics of each other. Conclusions The pharmacokinetics of volasertib in patients with acute myeloid leukaemia alone or in combination with cytarabine is predictable and associated with low-to-mild patient variability with the exception of the high variability associated with the volume of distribution of the central compartment, having no effect on the area under the plasma concentration-time curve.

The aim of this evaluation was to characterize the impact of the tumour size (TS) effects driven by the anticancer drug gemcitabine on overall survival (OS) in patients with advanced pancreatic cancer by building and validating a predictive semi-mechanistic joint TS-OS model. TS and OS data were obtained from one phase II and one phase III study where gemcitabine was administered (1000-1250 mg/kg over 30-60 min i.v infusion) as single agent to patients (n=285) with advanced pancreatic cancer. Drug exposure, TS and OS were linked using the population approach with NONMEM 7.3. Pancreatic tumour progression was characterized by exponential growth (doubling time = 67 weeks), and tumour response to treatment was described as a function of the weekly area under the gemcitabine triphosphate concentration vs time curve (AUC), including treatment-related resistance development. The typical predicted percentage of tumour growth inhibition with respect to no treatment was 22.3% at the end of 6 chemotherapy cycles. Emerging resistance elicited a 57% decrease in drug effects during the 6th chemotherapy cycle. Predicted TS profile was identified as main prognostic factor of OS, with tumours responders' profiles improving median OS by 30 weeks compared to stable-disease TS profiles. Results of NCT00574275 trial were predicted using this modelling framework, thereby validating the approach as a prediction tool in clinical development. Our analyses show that despite the advanced stage of the disease in this patient population, the modelling framework herein can be used to predict the likelihood of treatment success using early clinical data.

Marketed formulations of erythropoietin (EPO) ior (R) EPOCIM, MIRCERA (R) and two newly developed pegylated-EPO analogues (PEG-EPO 32 and 40 kDa) formulations were intravenously administered to New Zealand rabbits. A semi-mechanistic Pharmacokinetic/Pharmacodynamic (PK/PD) model describing in a simultaneous and integrated form the time course of reticulocytes, red blood cells and hemoglobin was built to account for the time course of hematopoiesis stimulation after erythropoietin administration. Data analysis was performed based on the population approach with the software NONMEM version 7.3. Erythropoietin disposition of each of the administered formulations was best described with a two compartment model and linear elimination. Different formulations show different clearance and apparent volume of distribution of the central compartment but share estimates of inter-compartmental clearance and apparent peripheral volume of distribution. A semi-mechanistic model including cell proliferation, maturation, and homeostatic regulation provided a good description of the data regardless the type of erythropoietin formulation administered. The system-, and drug-related parameters showed consistency and differed across formulations, respectively. A single IV administration of PEG-EPO 32 and 40 kDa formulations in New Zealand rabbits achieves a median change of 27% and 22% on RET levels, and of 47% and 63% on RBC and HGB levels, respectively compared to MIRCERA (R). The administration of new branched PEG-chains formulations improves PK and PD properties of EPO, in terms of increasing elimination halflives and pharmacological activity on RET, RBC and HGB compared to commercially available formulations (ior (R) EPOCIM and MIRCERA (R)).

Xenograft mice are largely used to evaluate the efficacy of oncological drugs during preclinical phases of drug discovery and development. Mathematical models provide a useful tool to quantitatively characterize tumor growth dynamics and also optimize upcoming experiments. To the best of our knowledge, this is the first report where unperturbed growth of a large set of tumor cell lines (n=28) has been systematically analyzed using a previously proposed model of nonlinear mixed effects (NLME). Exponential growth was identified as the governing mechanism in the majority of the cell lines, with constant rate values ranging from 0.0204 to 0.203 day(-1). No common patterns could be observed across tumor types, highlighting the importance of combining information from different cell lines when evaluating drug activity. Overall, typical model parameters were precisely estimated using designs in which tumor size measurements were taken every 2 days. Moreover, reducing the number of measurements to twice per week, or even once per week for cell lines with low growth rates, showed little impact on parameter precision. However, a sample size of at least 50 mice is needed to accurately characterize parameter variability (i.e., relative S.E. values below 50%). This work illustrates the feasibility of systematically applying NLME models to characterize tumor growth in drug discovery and development, and constitutes a valuable source of data to optimize experimental designs by providing an a priori sampling window and minimizing the number of samples required.

Pharmacokinetic modeling, traditionally using drug exposure, is widely used to support decision-making in translational medicine and patient care. The development of mechanistic computational models that integrate drug concentrations at the site of action making use of existing knowledge opens a new paradigm in optimal dosing. (C) 2018 AACR.

MOTIVATION: Literature on complex diseases is abundant but not always quantitative. Many molecular pathways are qualitatively well described but this information cannot be used in traditional quantitative mathematical models employed in drug development. Tools for analysis of discrete networks are useful to capture the available information in the literature but have not been efficiently integrated by the pharmaceutical industry. We propose an expansion of the usual analysis of discrete networks that facilitates the identification/validation of therapeutic targets. RESULTS: In this article, we propose a methodology to perform Boolean modeling of Systems Biology/Pharmacology networks by using SPIDDOR (Systems Pharmacology for effIcient Drug Development On R) R package. The resulting models can be used to analyze the dynamics of signaling networks associated to diseases to predict the pathogenesis mechanisms and identify potential therapeutic targets.

In this work, a semimechanistic tumor growth-response model for gemcitabine in pancreatic (administered as single agent) and ovarian (given as single agent and in combination with carboplatin) cancer in mice was developed. Tumor profiles were obtained from nude mice, previously inoculated with KP4, ASPC1, MIA PACA2, PANC1 (pancreas), A2780, or SKOV3 x luc (ovarian) cell lines, and then treated with different dosing schedules of gemcitabine and/or carboplatin. Data were fitted using the population approach with Nonlinear Mixed Effect Models 7.2. In addition to cell proliferation, the tumor progression model for both types of cancer incorporates a carrying capacity representing metabolite pool for DNA synthesis required to tumor growth. Analysis of data from the treated groups revealed that gemcitabine exerted its tumor effects by promoting apoptosis as well as decreasing the carrying capacity compartment. Pharmacodynamic parameters were cell-specific and overall had similar range values between cancer types. In pancreas, a linear model was used to describe both gemcitabine effects with parameter values between 3.26 x 10(-2) and 4.2 x 10(-1) L/(mg x d). In ovarian cancer, the apoptotic effect was driven by an E-MAX model with an efficacy/potency ratio of 5.25-8.65 L/(mg x d). The contribution of carboplatin to tumor effects was lower than the response exerted by gemcitabine and was incorporated in the model as an inhibition of the carrying capacity. The model developed was consistent in its structure across different tumor cell lines and two tumor types where gemcitabine is approved. Simulation-based evaluation diagnostics showed that the model performed well in all experimental design scenarios, including dose, schedule, and tumor type.

This commentary provides an overview of recent examples of pharmacometrics applied during the clinical development of two antagonists of the programmed death-1 (PD-1) cell surface receptor, pembrolizumab and nivolumab. Despite the remarkable achievements obtained in predicting the correct dosing schedule from different quantitative approaches, data indicated a great degree of heterogeneity in tumor response. To achieve therapeutic goals the search for predictive biomarkers associated with a lack of response and mechanism-based combination studies are warranted.

Background: Deep brain stimulation electrodes can record oscillatory activity from deep brain structures, known as local field potentials. The authors' objective was to evaluate and quantify the effects of dexmedetomidine (0.2 mu g.kg(-1).h(-1)) on local field potentials in patients with Parkinson disease undergoing deep brain stimulation surgery compared with control recording (primary outcome), as well as the effect of propofol at different estimated peak effect site concentrations (0.5, 1.0, 1.5, 2.0, and 2.5 mu g/ml) from control recording. Methods: A nonrandomized, nonblinded controlled clinical trial was carried out to assess the change in local field potentials activity over time in 10 patients with Parkinson disease who underwent deep brain stimulation placement surgery (18 subthalamic nuclei). The relationship was assessed between the activity in nuclei in the same patient at a given time and repeated measures from the same nucleus over time. Results: No significant difference was observed between the relative beta power of local field potentials in dexmedetomidine and control recordings (- 7.7; 95% CI, - 18.9 to 7.6). By contrast, there was a significant decline of 12.7% (95% CI, - 21.3 to - 4.7) in the relative beta power of the local field potentials for each increment in the estimated peak propofol concentrations at the effect site relative to the control recordings. Conclusions: Dexmedetomidine (0.2 mu g.kg(-1).h(-1)) did not show effect on local field potentials compared with control recording. A significant deep brain activity decline from control recording was observed with incremental doses of propofol.

Objective: To describe quantitatively the variability associated to the pharmacokinetic (PK) processes of clarithromycin (CLA) in Mexican hospitalized patients with respiratory infection and to determine whether the 6-beta-hydroxycortisol (6 beta-OHC)/cortisol ratio, among other factors would partially explain such variability. Materials and Methods: Fifty three patients aged >18 years with respiratory disease treated with CLA were included in the study. An average of 3 blood samples per patient were obtained at approximately the following Times After Dosing (TAD): 0.5, 1.25, 2, 3, 4, 6, 9 and 12 h. Clarithromycin was given orally or i.v., twice daily at the dose of 500 mg. Around the same times at which blood samples were collected, one urine sample was obtained for determining the 6 beta-OHC/cortisol ratio. The serum concentration vs time data of CLA were modeled using the population approach with NONMEM 7.2. Results: A one-compartment disposition model with first-order rate of absorption and concentration independent distribution and elimination provided a reasonable description of the data. Absolute bioavailability of CLA was not different from 1 (p>0.05). The population estimate of total clearance was 14.6 L h(-1), lower than that reported previously for healthy volunteers. Final population model included body weight as the unique covariate affecting the apparent volume of distribution. Conclusion: The study population showed a total clearance lower than that reported for healthy volunteers from other countries, probably due to the low activity of CYP3A determined in this population. However, the CYP3A activity level did not result as a significative covariable of the CLA total clearance.

Aim: Development of EGF-liposomes (LP-EGF) for selective molecules delivery in tumors expressing EGFR. Material & methods: In vitro cellular interaction of EGF-LP and nontargeted liposomes (LP-N) was assayed at 37 and 4°C in cells expressing different EGFR levels. Receptor-mediated uptake was investigated by competition with a monoclonal antibody anti-EGFR. Selective intracellular drug delivery and efficacy was tested by oxaliplatin encapsulation. In vivo biodistribution of LP-N and LP-EGF was done in xenograft model. Results: LP-EGF was internalized by an active and selective mechanism through EGFR without receptor activation. Oxaliplatin LP-EGF decreased IC50 between 48 and 13% in cell EGFR+. LP-EGF was accumulated in tumor over 72 h postdosing, while LP-N in spleen. Conclusion: LP-EGF represents an attractive nanosystem for cancer therapy or diagnosis.

The objective of this work was to establish the quantitative relationship between Lanreotide Autogel® (LAN) on serum chromogranin A (CgA) and progression-free survival (PFS) in patients with nonfunctioning gastroenteropancreatic neuroendocrine tumors (GEP-NETs) through an integrated pharmacokinetic/pharmacodynamic (PK/PD) model. In CLARINET, a phase III, randomized, double-blind, placebo-controlled study, 204 patients received deep subcutaneous injections of LAN 120 mg (n¿=¿101) or placebo (n¿=¿103) every 4 weeks for 96 weeks. Data for 810 LAN and 1298 CgA serum samples (n¿=¿632 placebo and n¿=¿666 LAN) were used to develop a parametric time-to-event model to relate CgA levels and PFS (76 patients experienced disease progression: n¿=¿49 placebo and n¿=¿27 LAN). LAN serum profiles were described by a one-compartment disposition model. Absorption was characterized by two parallel pathways following first- and zero-order kinetics. As PFS data were considered informative dropouts, CgA and PFS responses were modeled jointly. The LAN-induced decrease in CgA levels was described by an inhibitory E MAX model. Patient age and target lesions at baseline were associated with an increment in baseline CgA. Weibull model distribution showed that decreases in CgA from baseline reduced the hazard of disease progression significantly (P¿<¿0.001). Covariates of tumor location in the pancreas and tumor hepatic tumor load were associated with worse prognosis (P¿<¿0.001). We established a semimechanistic PK/PD model to better understand the effect of LAN on a surrogate endpoint (serum CgA) and ultimately the clinical endpoint (PFS) in treatment-naive patients with nonfunctioning GEP-NETs.

BACKGROUND AND OBJECTIVES: Lanreotide Autogel (lanreotide Depot in the USA) has demonstrated anti-tumor activity and control of the symptoms associated with hormone hypersecretion in patients with neuroendocrine tumors. The objectives of this study were to describe the pharmacokinetics of lanreotide Autogel administered 4-weekly by deep subcutaneous injections of 60, 90, or 120 mg in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs), to quantify the magnitude of inter-patient variability (IPV), and to identify those patient characteristics that impact on pharmacokinetics. METHODS: Analyses were based on pooled data from clinical trials. A total of 1541 serum concentrations from 290 patients were analyzed simultaneously by the population approach using NONMEM version 7.2. Covariates evaluated included demographics, renal and hepatic function markers, and disease-related parameters. RESULTS: Serum profiles were described by a one-compartment disposition model in which the absorption process was characterized by two parallel pathways following first- and zero-order kinetics. The estimated apparent volume of distribution was 18.3 L. The estimated apparent total serum clearance for a typical 74 kg patient was 513 L/day, representing a substantial difference in clearance in this population of patients with respect to healthy volunteers that could not be explained by any of the covariates tested. Body weight was the only covariate to show a statistically significant effect on the pharmacokinetic profile, but due to the overlap between the pharmacokinetic profiles of patients with lower or higher body weights the effect of body weight on clearance was not considered clinically relevant. The IPV was low for clearance (27%) and moderate to high for volume of distribution (150%) and the absorption constant (61%). CONCLUSIONS: Using two mechanisms of absorption, the pharmacokinetics of lanreotide Autogel were well-described in patients with GEP-NET. None of the patient characteristics tested were of clinical relevance to potential dose adjustment in clinical practice.

Population pharmacokinetic analysis of lithium during therapeutic drug monitoring and drug compliance assessment was performed in 54 patients and 246 plasma concentrations levels were included in this study. Patients received several treatment cycles (1-9) and one plasma concentration measurement for each patient was obtained always before starting next cycle (pre-dose) at steady state. Data were analysed using the population approach with NONMEM version 7.2. Lithium measurements were described using a two-compartment model (CL/F=0.41 L h(-1), V-1/F=15.3 L, Q/F=0.61 L h(-1), and V-2/F = 15.8 L) and the most significant covariate on lithium CL was found to be creatinine clearance (reference model). Lithium compliance was analysed using inter-occasion variability or Markovian features (previous lithium measurement as ordered categorical covariate) on bioavailability parameter. Markov-type model predicted the lithium compliance in the next cycle with higher success rate (79.8%) compared to IOV model (65.2%) and reference model (43.2%). This model becomes an efficient tool, not only being able to adequately describe the observed outcome, but also to predict the individual drug compliance in the next cycle. Therefore, Bipolar disorder patients can be classified regarding their probability to become extensive or poor compliers in the next cycle and then, individual probabilities lower than 0.5 highlight the need of intensive monitoring, as well as other pharmaceutical care measurements that might be applied to enhance drug compliance for a better and safer lithium treatment. (C) 2016 Elsevier B.V. and ECNP. All rights reserved.

AIM: The aim of the present study was to characterize the pharmacokinetic/pharmacodynamic (PK/PD) properties of the active components of axomadol and to quantify their contribution to observed the pupillometric and analgesic (measured through the cold pressor test) effects linking the PD engagement biomarker with clinical response. METHODS: Healthy subjects (n = 74) received either placebo or axomadol orally at doses ranging from 66 mg to 225 mg following multiple dosing regimens in two separate clinical trials. Plasma concentrations of the two enantiomers of axomadol and their metabolites, and PD responses were measured at specific times. The population analysis was performed using NONMEM 7.2. RESULTS: The kinetics of the parent drug and its metabolite could be described simultaneously using an extra compartment mimicking the liver, where the metabolite is formed. The SS parent compound elicited a plasma concentration-dependent increase in pupil diameter, with estimates (percentage relative standard errors) of maximal effect (Emax ) and plasma concentration exerting a half-maximal effect (C50 ) of 0.79 (17.4) mm, and 90.7 (27) ng ml(-1) , respectively. The predicted effect site concentrations of the RR O-demethyl metabolite decreased the pupil diameter linearly, with an estimate of the slope of 0.00967 (18.7) mm·ml ng(-1) . An additive model, integrating the net effect on pupil diameter, described adequately the reduction in pain with a linear function. The PK/PD model revealed that each 0.5 mm change in pupil diameter is associated with a 10% decrease in cold pressor area under the concentration-time curve effects. CONCLUSIONS: The PK/PD analysis performed enabled the individual contributions of the active compounds to the observed effects to be identified and quantified. These effects were in accordance with the known mechanisms of action - namely, opioid agonism and noradrenaline reuptake inhibition.

Predictive biomarkers can play a key role in individualized disease monitoring. Unfortunately, the use of biomarkers in clinical settings has thus far been limited. We have previously shown that mechanism-based pharmacokinetic/pharmacodynamic modeling enables integration of nonvalidated biomarker data to provide predictive model-based biomarkers for response classification. The biomarker model we developed incorporates an underlying latent variable (disease) representing (unobserved) tumor size dynamics, which is assumed to drive biomarker production and to be influenced by exposure to treatment. Here, we show that by integrating CT scan data, the population model can be expanded to include patient outcome. Moreover, we show that in conjunction with routine medical monitoring data, the population model can support accurate individual predictions of outcome. Our combined model predicts that a change in disease of 29.2% (relative standard error 20%) between two consecutive CT scans (i.e., 6-8 weeks) gives a probability of disease progression of 50%. We apply this framework to an external dataset containing biomarker data from 22 small cell lung cancer patients (four patients progressing during follow-up). Using only data up until the end of treatment (a total of 137 lactate dehydrogenase and 77 neuron-specific enolase observations), the statistical framework prospectively identified 75% of the individuals as having a predictable outcome in follow-up visits. This included two of the four patients who eventually progressed. In all identified individuals, the model-predicted outcomes matched the observed outcomes. This framework allows at risk patients to be identified early and therapeutic intervention/monitoring to be adjusted individually, which may improve overall patient survival.

Despite advances in biomedical research that have deepened our understanding of cancer hallmarks, resulting in the discovery and development of targeted therapies, the success rates of oncology drug development remain low. Opportunities remain for objective dose selection informed by exposure-response understanding to optimize the benefit-risk balance of novel therapies for cancer patients. This review article discusses the principles and applications of modeling and simulation approaches across the lifecycle of development of oncology therapeutics. Illustrative examples are used to convey the value gained from integration of quantitative clinical pharmacology strategies from the preclinical-translational phase through confirmatory clinical evaluation of efficacy and safety.

AIMS: The aims of this study were (i) to develop a population pharmacokinetic (PK) model of tacrolimus in a Mexican renal transplant paediatric population (n¿=¿53) and (ii) to test the influence of different covariates on its PK properties to facilitate dose individualization. METHODS: Population PK and variability parameters were estimated from whole blood drug concentration profiles obtained at steady-state using the non-linear mixed effect modelling software NONMEM® Version 7.2. RESULTS: Tacrolimus PK profiles exhibited high inter-patient variability (IPV). A two compartment model with first order input and elimination described the tacrolimus PK profiles in the studied population. The relationship between CYP3A5 genotype and tacrolimus CL/F was included in the final model. CL/F in CYP3A5*1/*1 and *1/*3 carriers was approximately 2- and 1.5-fold higher than in CYP3A5*3/*3 carriers (non-expressers), respectively, and explained almost the entire IPV in CL/F. Other covariates retained in the final model were the tacrolimus dose and formulation type. Limustin® showed markedly lower concentrations than the rest of the formulations. CONCLUSIONS: Population PK modelling of tacrolimus in paediatric renal transplant recipients identified the tacrolimus formulation type as a significant covariate affecting the blood concentrations and confirmed the previously reported significant effect of CYP3A5 genotype on CL/F. It allowed the design of a proposed dosage based on the final model that is expected to help to improve tacrolimus dosing.

The antibiotics used for prophylaxis in colorectal surgery must maintain appropriate plasma concentrations during the entire surgery to avoid surgical site infections caused by aerobes and anaerobes; cefuroxime plus metronidazole is one of the combinations used. The aim of this study was to evaluate the adequacy of cefuroxime plus metronidazole administration as prophylaxis in colorectal surgery. In total, 63 patients electively undergoing rectal or colon surgery were administered 1500mg of cefuroxime and 1500mg of metronidazole in 15-min and 1-h infusions, respectively, prior to surgery. Blood samples were withdrawn during and after surgery for determination of plasma concentrations by high-performance liquid chromatography. Population pharmacokinetic models were developed using NONMEM 7.2.0. Pharmacokinetic/pharmacodynamic (PK/PD) simulations were performed to explore the ability of different dosage regimens to achieve the pharmacodynamic targets. Pharmacokinetics for both antibiotics were best described by a two-compartment model. Elimination of cefuroxime was conditioned by creatinine clearance (CLCr). The half-life of cefuroxime was 1.5h for patients with normal renal function and 4.9h in patients with renal impairment. Elimination and distribution of metronidazole were affected by patient body weight (BW). PK/PD analysis revealed that a single-dose protocol of 1500mg of cefuroxime and metronidazole is adequate in short surgeries (¿2h). However, for longer surgeries, recommendations are suggested depending on the patient's CLCr and BW. Additional doses of cefuroxime are needed for patients with moderate renal impairment or those presenting normal renal function. For metronidazole, an additional dose is needed for patients with a BW of 90kg.

The current work integrates cell-cycle dynamics occurring in the bone marrow compartment as a key element in the structure of a semimechanistic pharmacokinetic/pharmacodynamic model for neutropenic effects, aiming to describe, with the same set of system-and drug-related parameters, longitudinal data of neutropenia gathered after the administration of the anticancer drug diflomotecan (9,10-difluoro-homocamptothecin) under different dosing schedules to patients (n = 111) with advanced solid tumors. To achieve such an objective, the general framework of the neutropenia models was expanded, including one additional physiologic process resembling cell cycle dynamics. The main assumptions of the proposed model are as follows: within the stem cell compartment, proliferative and quiescent cells coexist, and only cells in the proliferative condition are sensitive to drug effects and capable of following the maturation chain. Cell cycle dynamics were characterized by two new parameters, F-Prol (the fraction of proliferative [ Prol] cells that enters into the maturation chain) and k(cycle) (first-order rate constant governing cell cycle dynamics within the stem cell compartment). Both model parameters were identifiable as indicated by the results from a bootstrap analysis, and their estimates were supported by date from the literature. The estimates of F-Prol and k(cycle) were 0.58 and 1.94 day(-1), respectively. The new model could properly describe the neutropenic effects of diflomotecan after very different dosing scenarios, and can be used to explore the potential impact of dosing schedule dependencies on neutropenia prediction.

The development of individualized therapies poses a major challenge in oncology. Significant hurdles to overcome include better disease monitoring and early prediction of clinical outcome. Current clinical practice consists of using Response Evaluation Criteria in Solid Tumors (RECIST) to categorize response to treatment. However, the utility of RECIST is restricted due to limitations on the frequency of measurement and its categorical rather than continuous nature. We propose a population modeling framework that relates circulating biomarkers in plasma, easily obtained from patients, to tumor progression levels assessed by imaging scans (i.e., RECIST categories). We successfully applied this framework to data regarding lactate dehydrogenase (LDH) and neuron specific enolase (NSE) concentrations in patients diagnosed with small cell lung cancer (SCLC). LDH and NSE have been proposed as independent prognostic factors for SCLC. However, their prognostic and predictive value has not been demonstrated in the context of standard clinical practice. Our model incorporates an underlying latent variable ("disease level") representing (unobserved) tumor size dynamics, which is assumed to drive biomarker production and to be influenced by exposure to treatment; these assumptions are in agreement with the known physiology of SCLC and these biomarkers. Our model predictions of unobserved disease level are strongly correlated with disease progression measured by RECIST criteria. In conclusion, the proposed framework enables prediction of treatment outcome based on circulating biomarkers and therefore can be a powerful tool to help clinicians monitor disease in SCLC.

Population modeling of tumor size dynamics has recently emerged as an important tool in pharmacometric research. A series of new mixed-effects models have been reported recently, and we present herein a synthetic view of models with published mathematical equations aimed at describing the dynamics of tumor size in cancer patients following anticancer drug treatment. This selection of models will constitute the basis for the Drug Disease Model Resources (DDMoRe) repository for models on oncology.

We have estimated the pharmacological sensitivity and synergism of 125 individual patient samples for all drugs and combination treatments for acute myeloid leukemia in the context of the overall patient population. Each ex vivo pharmacological profile identifies drugs and treatments for which the patient's malignant cells are particularly sensitive or resistant, assisting in the selection of individualized treatments. Background: We have evaluated the ex vivo pharmacology of single drugs and drug combinations in malignant cells of bone marrow samples from 125 patients with acute myeloid leukemia using a novel automated flow cytometry-based platform (ExviTech). We have improved previous ex vivo drug testing with 4 innovations: identifying individual leukemic cells, using intact whole blood during the incubation, using an automated platform that escalates reliably data, and performing analyses pharmacodynamic population models. Patients and Methods: Samples were sent from 24 hospitals to a central laboratory and incubated for 48 hours in whole blood, after which drug activity was measured in terms of depletion of leukemic cells. Results: The sensitivity of single drugs is assessed for standard efficacy (E-MAX) and potency (EC50) variables, ranked as percentiles within the population. The sensitivity of drug-combination treatments is assessed for the synergism achieved in each patient sample. We found a large variability among patient samples in the dose-response curves to a single drug or combination treatment. Conclusion: We hypothesize that the use of the individual patient ex vivo pharmacological profiles may help to guide a personalized treatment selection.

Objectives: To evaluate the pharmacokinetics of piperacillin/tazobactam in critically ill patients undergoing continuous renal replacement therapy (CRRT) and to assess the success of the therapy against susceptible bacteria. Patients and methods: Sixteen patients undergoing CRRT with different degrees of renal function were included in the study. Blood and ultrafiltrate samples were drawn after administration of piperacillin/tazobactam (4/0.5 g) every 4, 6 or 8 h. The data were analysed by a population approach using NONMEM 7.2. The probability of target attainment (PTA) of maintaining free piperacillin levels above the MIC during the entire dosing interval was estimated by simulation of intermittent and continuous infusions. Results: The pharmacokinetics of piperacillin and tazobactam were best described by two-compartment models where the elimination of both drugs was conditioned by renal [dependent on creatinine clearance (CLCR)], non-renal and extracorporeal clearances. A 20 min infusion of piperacillin/tazobactam administered every 6 h provided high PTAs against MICs <= 32 mg/L in patients with severe renal failure. In patients with normal or moderate renal function PTAs >= 90% were only obtained up to MICs <= 8 mg/Lwith short infusions. However, simulating continuous infusion, higher probabilities of success were obtained against MICs of 32 and 16 mg/L when CLCR was 50 and 100 mL/min, respectively. Conclusions: Population pharmacokinetic models have been developed and validated for piperacillin and tazobactam. Based on the pharmacokinetic/pharmacodynamic analysis, dosing recommendations are given considering the residual renal function of the patient and the MIC for the isolated bacteria.

The formalin-induced rat model of nociception involves moderate continuous pain. Formalin-induced pain results in a typical repetitive flinching behaviour, which displays a biphasic pattern characterised by peaks of pain. Here we described the time course of pain response and the analgesic effect of gabapentin using a semi-mechanistic modelling approach. Male Sprague-Dawley rats received gabapentin (10-100 mg/kg) or placebo 1 h prior to the formalin injection, as per standard protocol. A reduction in the frequency of the second peak of flinching was used as a behavioural measure of gabapentin-mediated anti-nociception. The flinching response was modelled using a mono-exponential function to characterise the first peak and an indirect response model with a time variant synthesis rate for the second. PKPD modelling was performed using a population approach in NONMEM v.7.1.2. The time course of the biphasic response was adequately described by the proposed model, which included separate expressions for each phase. Gabapentin was found to reversibly decrease, but not suppress the flinching frequency of the second response peak only. The mean IC50 estimate was 7,510 ng/ml, with relative standard error (RSE%) of 40%. A compartmental, semi-mechanistic model provides the basis for further understanding of the formalin-induced flinching response and consequently to better characterisation of the properties of gabapentin, such as the potency in individual animals. Moreover, despite high exposure levels, model predictions show that gabapentin does not completely suppress behavioural response in the formalin-induced pain model.

To develop a semi-mechanistic population pharmacokinetic/pharmacodynamic (PKPD) model for the selective bradycardic agent cilobradine describing simultaneously the heart rate (HR) measured at rest and just after the end of exercise sharing the same set of PKPD parameters. Healthy subjects received cilobradine orally once daily over 2 weeks at 0.25-5 mg doses or placebo. Plasma drug concentrations and HR were measured at rest and following 3 min of exercise over the entire study period. PK and HR data were analyzed using the population approach with NONMEM VII. Plasma disposition of cilobradine was described with a three compartment model. Cilobradine showed dose proportional and time independent pharmacokinetics. HR response was drug concentration dependent and appeared with a significant delay with respect to PK profiles, a phenomenon modeled using two transit compartments. Perturbation in HR at rest as a consequence of exercise was described assuming that physiological processes controlling cardiac frequency were constantly increased over the period of exercise only. The selected model provides a useful modeling tool for cases where the PD response measured is the result of a temporal experimental induced perturbation.

Immunotherapy is a growing therapeutic strategy in oncology based on the stimulation of innate and adaptive immune systems to induce the death of tumour cells. In this paper, we have developed a population semi-mechanistic model able to characterize the mechanisms implied in tumour growth dynamic after the administration of CyaA-E7, a vaccine able to target antigen to dendritic cells, thus triggering a potent immune response. The mathematical model developed presented the following main components: (1) tumour progression in the animals without treatment was described with a linear model, (2) vaccine effects were modelled assuming that vaccine triggers a non-instantaneous immune response inducing cell death. Delayed response was described with a series of two transit compartments, (3) a resistance effect decreasing vaccine efficiency was also incorporated through a regulator compartment dependent upon tumour size, and (4) a mixture model at the level of the elimination of the induced signal vaccine (k(2)) to model tumour relapse after treatment, observed in a small percentage of animals (15.6%). The proposed model structure was successfully applied to describe antitumor effect of IL-12, suggesting its applicability to different immune-stimulatory therapies. In addition, a simulation exercise to evaluate in silico the impact on tumour size of possible combination therapies has been shown. This type of mathematical approaches may be helpful to maximize the information obtained from experiments in mice, reducing the number of animals and the cost of developing new antitumor immunotherapies.

BACKGROUND: The presence of the A118G single nucleotide polymorphism in the OPRM1 gene as well as noxious stimulation might affect the requirements of remifentanil for patients undergoing ultrasonographic endoscopy under sedation-analgesia with propofol and remifentanil. Bispectral index (BIS) was used as a surrogate measure of effect. METHOD: A total of 207 patients were screened for A118G and randomly received different combinations of propofol and remifentanil, changed depending on the nausea response to endoscopy tube introduction. Nonlinear mixed effects modelling was used to establish the relation between propofol and remifentanil with respect to BIS and to investigate the influence of A118G or noxious stimulation. The value of k e0 for propofol and remifentanil was estimated to avoid the hysteresis between predicted effect site concentration (Ce) and BIS. RESULTS: Data from 176 patients were analysed. Eleven were recessive homozygous for A118G (OPRM = 1). A total of 165 patients were either dominant homozygous or heterozygous and considered normal (OPRM = 0). The estimated values of k e0 for propofol and remifentanil were 0.122 and 0.148 min(-1). Propofol and remifentanil were synergistic with respect to the BIS ([alpha] = 1.85). EC50 estimate for propofol was 3.86 ug/ml and for remifentanil 19.6 ng/ml in normal patients and 326 ng/ml in OPRM = 1 patients. BIS increases around 4% for the same effect site concentrations with noxious stimulation. CONCLUSIONS: Predicted effect site concentration of remifentanil ranging 1-5 ng/ml synergistically potentiates the effects of propofol on the BIS but has no effect in A118G patients. Noxious stimulation increases BIS values by 4% at the same concentrations of propofol and remifentanil.

The aims of this work were as follows: 1) to develop a semi-mechanistic pharmacodynamic model describing tumor shrinkage after administration of a previously developed antitumor vaccine (CyaA-E7) in combination with CpG (a TLR9 ligand) and/or cyclophosphamide (CTX), and 2) to assess the translational capability of the model to describe tumor effects of different immune-based treatments. Population approach with NONMEM version 7.2 was used to analyze the previously published data. These data were generated by injecting 5 x 10(5) tumor cells expressing human papillomavirus (HPV)-E7 proteins into C57BL/6 mice. Large and established tumors were treated with CpG and/or CTX administered alone or in combination with CyaA-E7. Applications of the model were assessed by comparing model-based simulations with preclinical and clinical outcomes obtained from literature. CpG effects were modeled: 1) as an amplification of the immune signal triggered by the vaccine and 2) by shortening the delayed response of the vaccine. CTX effects were included through a direct decrease of the tumor-induced inhibition of vaccine efficacy over time, along with a delayed induction of tumor cell death. A pharmacodynamic model, built based on plausible biologic mechanisms known for the coadjuvants, successfully characterized tumor response in all experimental scenarios. The model developed was satisfactory applied to reproduce clinical outcomes when CpG or CTX was used in combination with different vaccines. The results found after simulation exercise indicated that the contribution of the coadjuvants to the tumor response elicited by vaccines can be predicted for other immune-based treatments.

Background: Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL). CEL dynamics are considered unpredictable and are characterized by high intra- and interpatient variability. Here, a population approach (nonlinear mixed-effects models) was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics. Methods and Findings: We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month's CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment. Conclusions: The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the interpatient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies.

nterleukin-12 (IL12) is a cytokine with potential applications in the treatment of cancer given the potent immune response that it triggers, in part due to its ability to stimulate expression of interferon-gamma (IFN gamma). To avoid the toxicity associated with systemic exposure to IL12, a high-capacity adenoviral vector carrying a liver-specific, mifepristone-inducible IL12 expression system (HC-Ad/RUmIL12) has been developed. However, the maintenance of IL12 expression at therapeutic levels is compromised by the inhibitory effect of IFN gamma on inducible systems. The aim of this work is to develop a semi-mechanistic model to characterize the relationship between IL12 and IFN gamma in wild-type and knock-out mice for the IFN gamma receptor treated with HC-Ad/RUmIL12 under different dosing regimens in order to better understand the key mechanisms controlling the system. Rapid binding was considered to account for target-mediated disposition exhibited by both cytokines (equilibrium dissociation constant were 18 and 2.28 pM for IL12 and IFN gamma, respectively). The final model included: (1) IFN gamma receptor turnover, (2) irreversible free cytokine elimination from the serum compartment, (3) internalization of the IL12 receptor complex, (4) IL12 expression upregulated by the co-administration of the adenoviral vector and mifepristone and downregulated by the IFN gamma receptor, and (5) synthesis of IFN gamma controlled by the relative increments in the bound IL12. In conclusion, a model simultaneously describing the kinetics of IL12 and IFN gamma in the context of gene therapy was developed and validated with additional data. The model was applied to design an experimental dosing protocol intended to maintain sustained therapeutic IL12 levels.

Purpose: To characterize the pharmacokinetic profile of elomotecan, a novel homocamptothecin analog, evaluate the dose-limiting toxicities, and establish the relationship between exposure and toxicity in the first Phase I study in patients with advanced malignant solid tumors. Preliminary antitumor efficacy results are also provided. Design: Elomotecan was administered as a 30-min intravenous infusion at doses ranging from 1.5 to 75 mg once every 3 weeks to 56 patients with advanced solid tumors. Plasma concentration data and adverse effects were modeled using the population approach. Results: Elomotecan showed linear pharmacokinetics, and clearance was decreased with age. The model predicts a 47 and 61 % reduction in CL for patients aged 60 and 80 years, respectively, when compared with younger patients (30 years). Neutropenia represented the dose-limiting toxicity. The maximum tolerated dose and the recommended dose (RD) were 75 and 60 mg, respectively. Elomotecan elicited a 20, 5, 2, and 2 % severe (grade 4) neutropenia, asthenia, nausea, and vomiting at the RD, respectively. Of the subjects in the RD cohort, 41.7 % had a stable disease mean duration of 123.6 ± 43.4 days. Conclusions: The pharmacokinetic parameters and the toxicity pattern of elomotecan suggest that this novel homocamptothecin analog should be further explored in the clinical setting using a dose of 60 mg administered as a 30-min intravenous infusion, once every 3 weeks.

In this work, the Film Method (FM), Reverse-Phase Evaporation (REV), and the Heating Method (HM) were applied to prepare PEG-coated liposomes of oxaliplatin with natural neutral and cationic lipids, respectively. The formulations developed with the three methods, showed similar physicochemical characteristics, except in the loading of oxaliplatin, which was statistically lower (P < 0.05) using the HM. The incorporation of a semi-synthetic lipid in the formulation developed by FM, provided liposomes with a particle size of 115 nm associated with the lowest polydispersity index and the highest drug loading, 35%, compared with the other two lipids, suggesting aft increase in the membrane stability. That stability was also evaluated according to the presence of cholesterol, the impact of the temperature, and the application of different cryoprotectants during the lyophilization. The results indicated long-term stability of the developed formulation, because after its intravenous in vivo administration to HT-29 tumor bearing mice was able to induce an inhibition of tumor growth statistically higher (P < 0.05) than the inhibition caused by the free drug. In conclusion, the FM was the simplest method in comparison with REV and HM to develop in vivo stable and efficient PEG-coated liposomes of oxaliplatin with a loading higher than those reported for REV. (C) 2012 Elsevier B.V. All rights reserved.

Interferon alpha linked to apolipoprotein A-I has been recently proposed as an improved interferon-based therapy. In the present study, we aimed to develop a computational model to gain further insight into the in vivo behaviour of this new fusion protein. In order to facilitate in vivo evaluation of interferon and the fusion protein without altering their biological properties, green fluorescent protein was incorporated into their structures. Kinetic and dynamic behaviour of both compounds was successfully described after plasmid hydrodynamic administration and in situ synthesis of the studied proteins. Results from the modelling exercise showed that apolipoprotein A-I conferred a modified kinetic behaviour, varying molecule distribution and prolonging half-life without altering liver dynamic performance. However, differences in the gene expression activity were observed at brain level between both compounds. Those differences could be explained by modifications in the dynamic, but also in the biodistribution properties, which would be worth evaluating in future experiments. Therefore, the modelling approach provided a global comprehension of a complex system and allowed us to compare the in vivo behaviour of both compounds and to identify critical aspects that might be important to understand the system better and suggests a need for new model-based experiments.

The objectives of the current work were to develop a predictive population pharmacokinetic (PK)/pharmacodynamic (PD) model for the testosterone (TST) effects of triptorelin (TRP) administered in sustained-release (SR) formulations to patients with prostate cancer and determine the minimal required triptorelin serum concentration (C(TRP_min)) to keep the testosterone levels of the patients below or equal to the level of castration (TST ¿ 0.5 ng/ml). A total of eight healthy male volunteers and 74 patients with prostate cancer received one or two doses of triptorelin injected subcutaneously or intramuscularly. Five different triptorelin formulations were tested. Pharmacokinetic (serum concentration of triptorelin) and pharmacodynamic (TST levels in serum) data were analyzed by using the population approach with NONMEM software (http://www.iconplc.com/technology/products/nonmem/). The PK/PD model was constructed by assembling the agonist nature of triptorelin with the competitive reversible receptor binding interaction with the endogenous agonist, a process responsible for the initial and transient TST flare-up, and triggering down-regulation mechanisms described as a decrease in receptor synthesis. The typical population values of K(D), the receptor equilibrium dissociation constant of triptorelin, and C(TRP_min) to keep 95% of the patients castrated were 0.931 and 0.0609 ng/ml, respectively. The semimechanistic nature of the model renders the predictions of the effect of triptorelin on TST possible regardless the type of SR formulation administered, while exploring different designs during the development of new delivery systems.

Purpose: Flibanserin is being developed for treating hypoactive sexual desire disorder in women; the main side effect is sedation. The analysis objective was to relate flibanserin plasma concentrations with acute sedative effects using a population pharmacokinetic/pharmacodynamic (PK/PD) model. Methods: The population model was developed with NONMEM based on data from 24 healthy volunteers. 'Drowsiness' was serially assessed by a Visual Analogue Scale (VAS) on a baseline day and after morning oral administration of 100 mg flibanserin together with PK sampling. Results: PK was best described by a three-compartment disposition model and transit compartments accounting for the lag time in absorption. VAS 'drowsiness' baseline profiles were modeled using linear splines with three breakpoints located at clock times at first and last observation, and at the median of the observation time across subjects. The drug effect followed a sigmoidal E model using predicted effect site concentrations (C). The VAS vs. C relationship was very steep and effect site and plasma concentration-time profiles were very similar thus suggesting little delay between the occurrence of maximum flibanserin plasma concentrations and drowsiness. Conclusions: At effect site concentrations lower than ~200 ng/mL that are reached approximately 4 h after administration, flibanserin shows hardly any effect on the VAS 'drowsiness' scale.

To elucidate whether a dose of 2 g cefoxitin as a prophylactic agent in patients undergoing elective colorectal surgery is able to maintain free drug concentrations above the minimum inhibitory concentration of the microorganisms involved in surgical site infection. This was a prospective study involving 56 patients electively undergoing rectal or colon surgery. All plasma concentration-time data were analyzed simultaneously using the population approach to estimate population pharmacokinetic parameters and study the influence of the subjects' demographic characteristics, disease status, surgical procedure, and clinical laboratory values on the pharmacokinetic properties of cefoxitin. A one-compartment open model was chosen to describe plasma concentrations of cefoxitin. Since cefoxitin is eliminated almost entirely via the kidney, creatinine clearance was identified as a covariate of cefoxitin clearance. The relationship between total cefoxitin clearance (CL) and creatinine clearance (CLCR) was best described using a nonlinear model [CL = 11.5 x (CLCR/77)(0.52)]. The population apparent volume of distribution was 12 L. Computer simulations carried out to determine the probability to maintain free plasma concentrations above 8 mg/L (the concentration threshold for susceptible bacteria) 2 h after drug administration revealed that this probability decreased from 84% in patients with a CLCR of 40 mL/min to 28% in patients with a CLCR of 100 mL/min. To ensure cefoxitin target concentrations during surgery, we recommend that cefoxitin be administered every 1.5 h in patients with a CLCR a parts per thousand yen60 mL/min and every hour if the CLCR is a parts per thousand yen100 mL/min. Administration by continuous infusion preceded by a bolus injection should also be considered.

The model-based approach was undertaken to characterize the interaction between the peripheral and central antinociceptive effects exerted by lumiracoxib. The effects of intraplantar and intrathecal administrations and of fixed ratio combinations of lumiracoxib simultaneously administered by these two routes were evaluated using the formalin test in rats. Pain-related behavior data, quantified as the number of flinches of the injected paw, were analyzed using a population approach with NONMEM 7. The pain response during the first phase of the formalin test, which was insensitive to lumiracoxib, was modeled using a monoexponential decay. The second phase, which was sensitive to lumiracoxib, was described incorporating synthesis and degradation processes of pain mediators that were recruited locally after tissue injury. Upregulation at the local level and in the central nervous system (CNS) was set to be proportional to the predicted levels of pain mediators in the local (injured) compartment. Results suggest a greater role of upregulated COX-2(Local) in generating the pain response compared to COX-2(CNS). Drug effects were described as inhibition of upregulated COX-2. The model adequately described the time course of nociception after formalin injection in the absence or presence of lumiracoxib administered locally and/or spinally. Data suggest that the overall response is the additive outcome of drug effects at the peripheral and central compartments, with predominance of peripheral mechanisms. Application of modeling opens new perspectives for understanding the overall mechanism of action of analgesic drugs.

The aim of this investigation was to compare the performance of a commonly used semi-mechanistic model for drug-related neutropenia with other semi-mechanistic models published in the literature. METHODS: After their implementation in NONMEM VI, five semi-mechanistic models were assessed using the pharmacokinetic and absolute neutrophil count data obtained from 95 patients with non-small cell lung cancer receiving either 200 mg on day 1 or 50 or 60 mg on days 1, 2 and 3 of a 21-day treatment course with the new Plk-1 inhibitor BI 2536. The model performance was compared by means of predictive (visual and numerical) checks, precision in the parameter estimates and objective function-based measures. Details of model parameterization, model stability and run times are also provided. RESULTS: The time course of the drug plasma concentrations was described by a three compartment model with a first-order elimination rate. With respect to neutropenia, all models were successfully implemented in NONMEM and provided reasonable fits for the median (although not all models described all percentiles of the data well), and in general precise parameter estimates. CONCLUSION: In the current evaluation performed in a single drug, none of the models showed superior performance compared to the most commonly used model first described by Friberg et al.

The impact of age and gender on Ochratoxin A (OTA) distribution in kidney and liver were studied. OTA was quantified in kidney and liver of young and mature rats of both sexes. Data was fit simultaneously using the population approach with NONMEM program. Fed and fasted mature males showed a 30% decrease and an 11% increase in relative bioavailability, respectively, in comparison with the rest of the groups. The OTA concentrations reached in kidney and liver were very similar between both organs. The models that best fit to data were the ones that considered that distribution of OTA to kidney and liver occurs from the central compartment and that elimination occurs mainly from the liver compartment. The kinetic analysis revealed that both, the apparent volume of distribution of the central compartment (V/F) and the apparent volume of distribution of the liver and kidney compartments (V(L,K)/F) increased significantly with body weight. Thus, the sex differences observed in organs distribution are a reflection of the differences in relative bioavailability observed in adult males, as a consequence of the fed and fasted conditions and to the significant higher body weight of mature males which directly affected the V/F and V(L,K)/F.

ACKGROUND: The increasing demand for anesthetic procedures in the gastrointestinal endoscopy area has not been followed by a similar increase in the methods to provide and control sedation and analgesia for these patients. In this study, we evaluated different combinations of propofol and remifentanil, administered through a target-controlled infusion system, to estimate the optimal concentrations as well as the best way to control the sedative effects induced by the combinations of drugs in patients undergoing ultrasonographic endoscopy. METHODS: One hundred twenty patients undergoing ultrasonographic endoscopy were randomized to receive, by means of a target-controlled infusion system, a fixed effect-site concentration of either propofol or remifentanil of 8 different possible concentrations, allowing adjustment of the concentrations of the other drug. Predicted effect-site propofol (C(e)pro) and remifentanil (C(e)remi) concentrations, parameters derived from auditory evoked potential, autoregressive auditory evoked potential index (AAI/2) and electroencephalogram (bispectral index [BIS] and index of consciousness [IoC]) signals, as well as categorical scores of sedation (Ramsay Sedation Scale [RSS] score) in the presence or absence of nociceptive stimulation, were collected, recorded, and analyzed using an Adaptive Neuro Fuzzy Inference System. The models described for the relationship between C(e)pro and C(e)remi versus AAI/2, BIS, and IoC were diagnosed for inaccuracy using median absolute performance error (MDAPE) and median root mean squared error (MDRMSE), and for bias using median performance error (MDPE). The models were validated in a prospective group of 68 new patients receiving different combinations of propofol and remifentanil. The predictive ability (P(k)) of AAI/2, BIS, and IoC with respect to the sedation level, RSS score, was also explored. RESULTS: Data from 110 patients were analyzed in the training group. The resulting estimated models had an MDAPE of 32.87, 12.89, and 8.77; an MDRMSE of 17.01, 12.81, and 9.40; and an MDPE of -1.86, 3.97, and 2.21 for AAI/2, BIS, and IoC, respectively, in the absence of stimulation and similar values under stimulation. P(k) values were 0.82, 0.81, and 0.85 for AAI/2, BIS, and IoC, respectively. The model predicted the prospective validation data with an MDAPE of 34.81, 14.78, and 10.25; an MDRMSE of 16.81, 15.91, and 11.81; an MDPE of -8.37, 5.65, and -1.43; and P(k) values of 0.81, 0.8, and 0.8 for AAI/2, BIS, and IoC, respectively. CONCLUSION: A model relating C(e)pro and C(e)remi to AAI/2, BIS, and IoC has been developed and prospectively validated. Based on these models, the (C(e)pro, C(e)remi) concentration pairs that provide an RSS score of 4 range from (1.8 ¿g·mL(-1), 1.5 ng·mL(-1)) to (2.7 ¿g·mL(-1), 0 ng·mL(-1)). These concentrations are associated with AAI/2 values of 25 to 30, BIS of 71 to 75, and IoC of 72 to 76. The presence of noxious stimulation increases the requirements of C(e)pro and C(e)remi to achieve the same degree of sedative effects.

BACKGROUND: The onset and offset of action of anesthetic gases might be delayed by respiratory changes and gas exchange alterations present in obese patients. In this study, we assessed the influence of obesity on the hysteresis between sevoflurane and its effect as measured by the bispectral index (BIS). Because the use of positive end-expiratory pressure (PEEP) in obese patients has improved gas exchange, we also assessed the influence of PEEP on hysteresis. METHODS: Fifteen obese and 15 normal-weight patients, ASA physical status I and II, 20 to 50 years old, scheduled to undergo general anesthesia for elective laparoscopic surgery, were prospectively studied. Anesthesia was induced with propofol and maintained with sevoflurane and fentanyl. At the end of surgery and after stable BIS values of 60 to 65, the inspired concentration of sevoflurane was increased to 5 vol% for 5 minutes or until BIS was <40 and then decreased. Sevoflurane transitions were performed once in normal-weight subjects (without PEEP) and twice in obese patients (one without PEEP and one with a PEEP of 8 cm H2O). The hysteresis between sevoflurane end-tidal concentrations and BIS during these transition periods was modeled with an inhibitory Emax model using a population pharmacokinetic/pharmacodynamic (PK/PD) approach with NONMEM VI. A descriptive analysis of sevoflurane inspired and expired concentrations, BIS values, and time to reach different BIS end points was also used to compare the PK and PD characteristics. RESULTS: All patients completed the study. The data were adequately fit with the PK/PD model. The hysteresis expressed as the effect-site elimination rate constant was not influenced by body mass index or PEEP (P > 0.05). Neither obesity nor PEEP showed any influence on the PK/PD descriptors. CONCLUSIONS: Our results do not support the hypothesis that obesity prolongs induction or recovery times when sevoflurane, a poorly soluble anesthetic, is used to maintain anesthesia from 90 to 120 minutes.

Introduction: Acute otitis media is the most common respiratory tract infection in infancy and early childhood that is managed with antimicrobial agents. Ninety-three per cent of the cases diagnosed in Spain are treated with antibiotics, and Streptococcus pneumoniae and untypeable Haemophilus influenzae are the most frequently isolated pathogens. The aim of this work was to evaluate the usefulness of amoxicillin, amoxicillin/clavulanate and ceftriaxone for the empirical treatment of acute otitis media, looking at the pharmacokinetic variability and the antimicrobial susceptibility of paediatric strains of the two main pathogens responsible for AOM in Spain, Streptococcus pneumoniae and Haemophilus influenzae. Methods: Free-drug plasma concentrations were simulated and the probability of target attainment at each minimum inhibitory concentration and the cumulative fraction of response (CFR) were determined. Microbiological susceptibility information was extracted from SAUCE 3 surveillance. Results: CFR with amoxicillin varied from 83% to 96% against S. pneumoniae and from 78% to 86% against H. influenzae. CFR was always >85% with amoxicillin/clavulanate. With the 3-day ceftriaxone regimen, the probability of achieving free concentrations above MIC at 72 hours significantly increased compared to the single dose, with which CFR ranged from 70% to 84%. Conclusions: High-dose amoxicillin (at least 80 mg/kg/day) should be the first-line therapy in uncomplicated infections, whereas amoxicillin/clavulanate (40 mg/kg/day) should be the choice when additional coverage for H. influenzae is desired. Administration of 3 daily doses of ceftriaxone increases bacteriological eradication probability when compared with one-day regimen, although additional clinical evaluations are necessary to establish the best target attainment with ceftriaxone.

To describe the neutropenic response of BI 2536 a polo-like kinase 1 inhibitor in patients with cancer using a semi-mechanistic model. (2) To explore by simulations (a) the neutropenic effects for the maximum tolerated dose (MTD) and the dose at which dose-limiting toxicity occurred, (b) the possibility to reduce the cycle duration without increasing neutropenia substantially, and (c) the impact of the initial absolute neutrophil count (ANC) on the degree of neutropenia for different doses. BI 2536 was administered as intravenous infusion over 60 min in the dose range from 25 to 250 mg. Three different administration schedules were explored: (a) day 1, (b) days 1, 2, and 3 or (c) days 1 and 8 within a 3 week treatment cycle. BI 2536 plasma concentrations and ANC obtained during the first treatment cycle from 104 patients were analysed using the population approach with NONMEM VI. Neutropenia was described by a semi-mechanistic model resembling proliferation at the stem cell compartment, maturation, degradation, and homeostatic regulation. BI 2536 acts decreasing proliferation rate. Simulations showed that (1) all MTD doses showed an acceptable risk of neutropenia, (2) when BI 2536 is given as 200 mg single administration, cycle duration can be reduced from 3 to 2 weeks, and (3) baseline ANC might be considered to individualise the dose of BI 2536. A semi-mechanistic population model was applied to describe the neutropenic effects of BI 2536. The model was used for simulations to support further clinical development.