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Purpose The exposure–response relationships for efficacy and safety of ipatasertib, a selective AKT kinase inhibitor, were characterized using data collected from 1101 patients with metastatic castration-resistant prostate cancer in the IPATential150 study (NCT03072238). Methods External validation of a previously developed population pharmacokinetic model was performed using the observed pharmacokinetic data from the IPATential150 study. Exposure metrics of ipatasertib for subjects who received ipatasertib 400 mg once-daily orally in this study were generated as model-predicted area under the concentration–time curve at steady state (AUCSS). The exposure–response relationship with radiographic progression-free survival (rPFS) was evaluated using Cox regression and relationships with safety endpoints were assessed using logistic regression. Results A statistically significant correlation between ipatasertib AUCSS and improved survival was found in patients with PTEN-loss tumors (hazard ratio [HR]: 0.92 per 1000 ng h/mL AUCSS, 95% confidence interval [CI] 0.87–0.98, p = 0.011). In contrast, an improvement in rPFS was seen in subjects receiving ipatasertib treatment (HR: 0.84, 95% CI 0.71–0.99, p = 0.038) but this effect was not associated with ipatasertib AUCSS in the intention-to-treat population. Incidences of some adverse events (AEs) had statistically significant association with ipatasertib AUCSS (serious AEs, AEs leading to discontinuation, and Grade ≥ 2 hyperglycemia), while others were associated with only ipatasertib treatment (AEs leading to dose reduction, Grade ≥ 3 diarrhea, and Grade ≥ 2 rash). Conclusions The exposure–efficacy results indicated that patients receiving ipatasertib may continue benefiting from this treatment at the administered dose, despite some variability in exposures, while the exposure–safety results suggested increased risks of AEs with ipatasertib treatment and/or increased ipatasertib exposures.

Purpose:Model-based tumor growth inhibition (TGI) metrics are increasingly incorporated into go/no-go decisions in early clinical studies. To apply this methodology to new investigational combinations requires independent evaluation of TGI metrics in recently completed Phase III trials of effective immunotherapy.Patients and Methods:Data were extracted from IMpower150, a positive, randomized, Phase III study of first-line therapy in 1,202 patients with non–small cell lung cancer. We resampled baseline characteristics and longitudinal sum of longest diameters of tumor lesions of patients from both arms, atezolizumab+ bevacizumab+chemotherapy (ABCP) versus BCP, to mimic Phase Ib/II studies of 15 to 40 patients/arm with 6 to 24 weeks follow-up. TGI metrics were estimated using a bi-exponential TGI model. Effect sizes were calculated as TGI metrics geometric mean ratio (GMR), objective response rate (ORR) difference (d), and progression-free survival (PFS), hazard ratio (HR) between arms. Correct and incorrect go decisions were evaluated as the probability to achieve desired effect sizes in ABCP versus BCP and BCP versus BCP, respectively, across 500 replicated subsamples for each design.Results:For 40 patients/24 weeks follow-up, correct go decisions based on probability tumor growth rate (KG) GMR 0.10, and PFS HR Conclusions:Model-based estimate of KG GMR is an exploratory endpoint that informs early clinical decisions for combination studies.

Purpose:Model-based tumor growth inhibition (TGI) metrics are increasingly incorporated into go/no-go decisions in early clinical studies. To apply this methodology to new investigational combinations requires independent evaluation of TGI metrics in recently completed Phase III trials of effective immunotherapy.Patients and Methods:Data were extracted from IMpower150, a positive, randomized, Phase III study of first-line therapy in 1,202 patients with non–small cell lung cancer. We resampled baseline characteristics and longitudinal sum of longest diameters of tumor lesions of patients from both arms, atezolizumab+ bevacizumab+chemotherapy (ABCP) versus BCP, to mimic Phase Ib/II studies of 15 to 40 patients/arm with 6 to 24 weeks follow-up. TGI metrics were estimated using a bi-exponential TGI model. Effect sizes were calculated as TGI metrics geometric mean ratio (GMR), objective response rate (ORR) difference (d), and progression-free survival (PFS), hazard ratio (HR) between arms. Correct and incorrect go decisions were evaluated as the probability to achieve desired effect sizes in ABCP versus BCP and BCP versus BCP, respectively, across 500 replicated subsamples for each design.Results:For 40 patients/24 weeks follow-up, correct go decisions based on probability tumor growth rate (KG) GMR 0.10, and PFS HR Conclusions:Model-based estimate of KG GMR is an exploratory endpoint that informs early clinical decisions for combination studies.

Summary Long-term use of vismodegib is associated with treatment-emergent adverse drug reactions in clinical trials of patients with locally advanced basal cell carcinoma (laBCC) and metastatic BCC (mBCC). Treatment interruptions have been recommended for management of adverse drug reactions, but there is no clear guidance on the duration of those interruptions. A model-based evaluation was conducted to assess the impact of treatment interruptions on vismodegib efficacy. A tumor growth–inhibition model was developed and model-based simulations were performed to assess the proportion of patients achieving ≥30% reduction from baseline in tumor size (ie, proportion of responders) for various dosing schedules. The most conservative simulated scenario compared an intermittent dosing schedule of 12 weeks of vismodegib treatment followed by 8-week dosing interruption (repeated four times for a total duration of 80 weeks) versus 80 weeks of continuous dosing, which predicted a decrease in responders of –4.7% from 90.7% in laBCC and –3.7% from 63.0% in mBCC. These results demonstrated maintenance of vismodegib efficacy with the intermittent dosing schedule and support the recently approved recommendations of treatment interruptions of up to 8 weeks to manage tolerability in laBCC or mBCC patients in the vismodegib US prescribing information.

Intravenous (IV) atezolizumab is approved for non–small cell lung and other cancers. Subcutaneous (SC) atezolizumab coformulated with recombinant human hyaluronidase, a permeation enhancer for SC dispersion and absorption, is being developed to improve treatment options, reduce burden, and increase efficiency for patients and practitioners. IMscin001 (NCT03735121), a 2‐part, open‐label, global, multicenter, phase 1b/3 study, is evaluating the pharmacokinetics (PK), safety, and efficacy of SC atezolizumab. The part 1 (phase 1b) objective was determination of an SC atezolizumab dose yielding a serum trough concentration (Ctrough) comparable with IV. Patients enrolled in 3 cohorts received SC atezolizumab 1800 mg (thigh) once (cohort 1), 1200 mg (thigh) every 2 weeks for 3 cycles (cohort 2), or 1800 mg (abdomen) every 3 weeks cycle 1, then cycles 2 and 3 (thigh) every 3 weeks (cohort 3). In subsequent cycles, IV atezolizumab 1200 mg every 3 weeks was administered until loss of clinical benefit. SC atezolizumab 1800 mg every 3 weeks and 1200 mg every 2 weeks provided similar Ctrough and area under the curve values in cycle 1 to the corresponding IV atezolizumab reference, was well tolerated, and exhibited a safety profile consistent with the established IV formulation. Exposure following SC injection in the abdomen was lower (20%, 28%, and 27% for Ctrough, maximum concentration, and area under the concentration‐time curve from time 0 to day 21, respectively) than in the thigh. Part 1 SC and IV PK data were analyzed using a population PK modeling approach, followed by simulations. Part 2 (phase 3) will now be initiated to demonstrate that SC atezolizumab PK exposure is not lower than that of IV.

AIMS: Methoxy polyethylene glycol‐epoetin beta (continuous erythropoietin receptor activator, C.E.R.A.) is used for the treatment of anaemia in adults with chronic kidney disease (CKD). Patients treated with shorter‐acting erythropoiesis‐stimulating agents up to three times weekly can be switched to once‐monthly C.E.R.A.. Doses can be adjusted on a monthly basis based on haemoglobin (Hb) levels during the preceding period. A model‐based approach was applied to optimise C.E.R.A. development, more specifically the confirmatory trial of the paediatric plan. METHODS: Pharmacokinetic and pharmacodynamic data from a phase II paediatric study and phase II and III adult studies were analysed together using modelling and simulation to determine the pharmacokinetic/pharmacodynamic characteristics of C.E.R.A. in a broad population. Model‐based simulations of C.E.R.A. treatment outcomes in paediatric patients were performed, notably when administered subcutaneously and compared to clinical and real‐world data. RESULTS: Age and body weight explained differences in pharmacokinetics, while the pharmacodynamic characteristics of C.E.R.A. were similar between adult and paediatric populations. Simulated Hb levels (mean and 95% prediction interval 10.9 [10.6, 11.2] g dL(−1)) and C.E.R.A. doses (median and 95% prediction interval 105 [72, 159] μg) 20 weeks after switching to subcutaneous C.E.R.A. were confirmed by observed real‐world data from International Pediatric Dialysis Network registries (mean Hb was 10.8 g dL(−1) and median C.E.R.A. dose was 100 μg). CONCLUSIONS: These analyses have facilitated optimisation of the C.E.R.A. development programme in paediatric patients with anaemia of CKD to provide this patient population with faster access to the drug while avoiding unnecessary clinical trial exposure and related monitoring burden in children.

Sildenafil (REVATIO®) was approved for the treatment of adult Pulmonary Arterial Hypertension (PAH) in the US and the EU. A pediatric study has been performed and sildenafil was approved in the EU for pediatric PAH. The long-term extension of this study revealed good survival but also an increased mortality with the high dose of sildenafil compared to lower doses. As a consequence, FDA required Pfizer to evaluate REVATIO®’s effect on the risk of death in adults with PAH. Following FDA’s rationale a survival model was developed to characterize the exposure–mortality relationship and assess its potential impact on an ongoing survival trial in adults in the context of confounding factors. Clinical trial simulations were performed to assess the design of the survival trial in adults (AFFILIATE, NCT02060487), expected to last approximately 8 years according to both assumptions: absence or presence of an exposure–mortality relationship and to quantify the impact of confounding factors on its readout. Simulations showed that the trial would be robust in most conditions. But its interpretation will depend on the number of confounding factors such as additional treatments attempting to control disease progression. Clinical trial identifier NCT00159913 for STARTS-1, NCT00159874 for STARTS-2

Ipatasertib is a selective AKT kinase inhibitor currently in development for the treatment of several solid tumors, including breast and prostate cancers. This study was undertaken to characterize pharmacokinetics profiles of ipatasertib and its metabolite M1 (G-037720), and to understand the sources of variability. Population pharmacokinetic models of ipatasertib and M1 were developed separately using data from 342 individuals with cancer from five Phase I and II studies. The final population pharmacokinetic models for ipatasertib and M1 were three-compartmental, with first-order elimination and sequential zero- and first-order absorption. Ipatasertib bioavailability and M1 formation increased after multiple dosing resulting in an increase in exposure beyond that expected from accumulation alone. Covariate effects of ipatasertib include decreased oral clearance with increasing age and with coadministration of abiraterone, as well as decreased bioavailability with increasing weight. For ages of 37 and 80 years, steady-state area under the curve (AUCss ) were predicted to be 81% and 109% of the typical population value (64 years), respectively. For body weights of 49 and 111 kg, AUCss were predicted to be 132% and 78% of the typical population value (75 kg), respectively. The small magnitude of changes in ipatasertib exposure is not likely to be clinically relevant. For M1, the peripheral distribution volume and intercompartmental clearance increased with increasing weight. Coadministration of abiraterone was estimated to increase M1 exposure by 61% at steady-state. Mild and moderate renal impairment, mild hepatic impairment and race were not identified as significant covariates in the final models for ipatasertib and M1. This article is protected by copyright. All rights reserved.

Background: Tumor growth inhibition (TGI)-overall survival (OS) models predict OS distributions and study outcomes (OS hazard ratio (HR)) in a number of cancers and settings (Bruno, Clin Cancer Res 2020;26:1787-95). Model-derived TGI metrics such as tumor growth rate (KG) have been considered as a promising early endpoint compared to classical response criteria (Gong J Clin Oncol 2020; doi: 10.1200/JCO.2020.38.15_suppl.9541). This work is assessing the validity of tumor growth rate estimates to inform GO/noGO decisions for Phase Ib studies. Methods: We resampled baseline characteristics and longitudinal sum of longest diameters (SLD, RECIST 1.1) from a positive Phase III study (IMpower150, Socinski, N Engl J Med 2018;378:2288-301) to mimic a Phase Ib study of 15, 30, or 40 patients per arm (atezolizumab +bevacizumab+carboplatin+paclitaxel (A+BCP) vs. BCP) with 10 months recruitment and 6 or 3 months follow-up (FU) after the last patient recruited. Effect sizes across A+BCP vs. BCP or BCP vs. BCP were calculated as geometric mean ratio (GMR) for KG, difference (d) in objective response rate (ORR), and HR for progression-free survival (PFS) and simulated OS. For this, individual KG were estimated using a bi-exponential model (Claret, Clin Cancer Res 2018;24:3292-8); ORR and PFS were estimated per RECIST 1.1, OS was simulated using a previously published TGI-OS model (Chan CPT:PSP 2021; doi.org/10.1002/psp4.12686) with 400 patients per arm bootstrapped from the 15, 30 or 40 patients of the resampled subsamples. Correct and incorrect Go decisions were based on the probability (prob) to achieve target effect sizes in A+BCP vs. BCP and BCP vs. BCP, respectively, across 500 replicated subsamples. Results: To not exceed an incorrect Go decision of 20% and for 40 patients/6 months FU, correct Go based on prob(KG GMR0.10), prob(OS HR Conclusions: This evaluation suggests that model-based estimates of on-treatment tumor growth rate could be used as an exploratory endpoint to inform early clinical decisions. Expansion of this work is planned in other settings e.g. single-arm studies commonly used in early oncology clinical development. Citation Format: René Bruno, Mathilde Marchand, Kenta Yoshida, Phyllis Chan, Haocheng Li, Wei Zou, Francois Mercier, Pascal Chanu, Benjamin Wu, Anthony Lee, Chunze Li, Jin Y. Jin. Tumor dynamic model-based decision support for phase Ib immunotherapy combination studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5176.

Purpose The established two-analyte integrated population pharmacokinetic model was applied to assess the impact of intrinsic/extrinsic factors on the pharmacokinetics (PK) of polatuzumab vedotin (pola) in patients with non-Hodgkin lymphoma (NHL) following bodyweight-based dosing. Methods Model simulations based on individual empirical Bayes estimates were used to evaluate the impact of intrinsic/extrinsic factors as patient subgroups on Cycle 6 exposures. Intrinsic factors included bodyweight, age, sex, hepatic and renal functions. Extrinsic factors included rituximab/obinutuzumab or bendamustine combination with pola and manufacturing process. The predicted impact on exposures along with the established exposure-response relationships were used to assess clinical relevance. Results No clinically meaningful differences in Cycle 6 pola exposures were found for the following subgroups: bodyweight 100–146 kg versus 38–versus versus male, mild hepatic impairment versus normal, mild-to-moderate renal impairment versus normal. Co-administration of rituximab/obinutuzumab or bendamustine, and change in the pola manufacturing process, also had no meaningful impact on PK. Conclusions In patients with NHL, bodyweight-based dosing is adequate, and no further dose adjustment is recommended for the heavier subgroup (100–146 kg). In addition, no dose adjustments are recommended for other subgroups based on intrinsic/extrinsic factors evaluated.

Exposure-response relationships were investigated to assess the risk/benefit of polatuzumab vedotin (pola) + bendamustine-rituximab (pola + BR) in relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL). Analyses were conducted in pivotal study GO29365 (NCT02257567; BR/pola + BR/pola + BG [BG: bendamustine-obinutuzumab]; 1.8 mg/kg pola, every 3 weeks [Q3W], six cycles), and supportive studies DCS4968g (NCT01290549) and GO27834 (NCT01691898) (pola/pola + R/pola + G; 0.1-2.4 mg/kg pola Q3W; eight-cycle landmark), separately. Exposure was characterized as simulated cycle-6 AUC and

A two‐analyte integrated population pharmacokinetic (PK) model that simultaneously describes concentrations of antibody‐conjugated monomethyl auristatin E (acMMAE) and unconjugated MMAE following repeated administrations of polatuzumab vedotin (pola) was developed based on data from four clinical studies of pola in patients with non‐Hodgkin lymphoma. A two‐compartment model with a nonspecific, time‐dependent linear clearance, a linear time‐dependent exponentially declining clearance, and a Michaelis–Menten clearance provided a good fit of the acMMAE plasma PK profiles. All three acMMAE elimination pathways contributed to the input to the central compartment of unconjugated MMAE, which was also described by a two‐compartment model. Population PK parameters, covariate effects, and interindividual variability of model parameters were estimated. The impact of clinically relevant covariates on PK exposures of each analyte were quantified and reported to support key label claims.

BackgroundC.E.R.A. indicated in Chronic Kidney Disease adult patients to correct and maintain hemoglobin (Hb) levels is approved in Europe and US since 2007; pediatric development is ongoing. A 20-week open-label Phase II study (NH19707) of intravenous (IV) C.E.R.A. in patients aged 5–17 years was conducted and data collected was analysed with adult data1. Objectives were to determine the pharmacokinetic/pharmacodynamic (PK/PD) characteristics of C.E.R.A. in a broad population, to simulate treatment outcomes of C.E.R.A. administered IV and subcutaneous (SC) in pediatric patients and compare them to NH19707 data and Real World Data (RWD).MethodsPK and Hb data from 63 pediatric patients were pooled with 400 adult patients IV and SC data and analysed using models previously developed in adults2. Simulations of treatment outcomes with C.E.R.A. administered IV and SC were performed. Assumptions on SC bioavailability in pediatric patients were based on previous darbepoetin data3. Model inferences were challenged versus RWD obtained in 158 pediatric patients receiving C.E.R.A. SC (N=126) or IV (N=32) from registries maintained by the International Pediatric Dialysis Network (IPDN, www.pedpd.org).ResultsThe adult PK and PK/PD models adequately described the pediatric data and indicated a similar exposure-response relationship in both populations. C.E.R.A. doses were adjusted to Hb levels during the simulation process to reflect clinical practice; simulated Hb levels matched observations. Furthermore, simulated median monthly C.E.R.A. doses following Hb stabilization were 105 µg (95% prediction interval 72–159 µg) for SC and 84 µg (60–123 µg) for IV, in good agreement with those reported in the IPDN registry: 100 µg and 80.4 µg, respectively.ConclusionThe PK/PD characteristics of C.E.R.A. are similar between adult and pediatric populations. Simulations of clinical outcomes in accordance with clinical trial data and RWD provided sufficient clinical evidence to support pediatric plans optimization subsequently approved by FDA and EMA.References1.Fischbach M, Wühl E, Reigner SCM, Morgan Z, Schaefer F. Efficacy and long-term safety of C.E.R.A. maintenance in pediatric hemodialysis patients with anemia of CKD. Clin J Am Soc Nephrol. 2018;13(1):81–90.Chanu P, Gieschke R, Charoin JE, Pannier A, Reigner B. Population pharmacokinetic/pharmacodynamic model for C.E.R.A. in both ESA-naïve and ESA-treated CKD patients with renal anemia. Journal of Clinical Pharmacology. J Clin Pharmacol. 2010;50(5):507–520.3.Amgen Inc. ARANESP® (darbepoetin alfa) prescribing information.Disclosure(s)Chanu P is employee and holds stocks in F Hoffmann-La Roche Ltd, was employee of Certara Consulting Services, Certara, Princeton, NJ, USA and contractor to F Hoffmann-La Roche Ltd at the time of this work. Weichert A is employee of F Hoffmann-La Roche Ltd. Schaefer F has received consulting and speaker honoraria from F Hoffmann-La Roche Ltd. Meyer Reigner S is employee of F Hoffmann-La Roche Ltd. Reigner B is employee and holds stocks in F Hoffmann-La Roche Ltd. Frey N is employee of F Hoffmann-La Roche Ltd.

The phase III trial comparing onartuzumab + erlotinib vs. erlotinib in the second- and third-line non-small cell lung cancer (NSCLC) did not meet its primary endpoint of overall survival (OS). The objective was to assess whether doses higher than the phase III dose (15 mg/kg) might yield better efficacy without compromising the safety profile. Data were from 636 patients from the phase II and III NSCLC studies. Tumor growth inhibition (TGI) models were fit to longitudinal tumor size data to estimate individual TGI metrics including time to tumor re-growth (TTG). Cox regression models were developed for time-to-event endpoints (progression-free survival (PFS), OS, and TTG) to investigate relationships with baseline prognostic factors and onartuzumab exposure. Incidence of adverse events was modeled by logistic regression. In the final models, higher onartuzumab exposure was associated with longer PFS, but not with longer OS. Longer OS was associated with higher baseline albumin, longer TTG, smaller number of metastatic sites, female gender, lower ECOG score, and younger age. TTG was the only TGI metric retained in the final OS model. Onartuzumab exposure was not significantly associated with TTG after adjusting for prognostic factors. Higher Cmin was associated with increased incidence of infusion reactions and peripheral edema. Higher onartuzumab exposure was not significantly associated with improved OS after adjusting for prognostic factors and TTG, and there was a trend of unknown clinical significance toward increased incidence of infusion reactions and peripheral edema. These results did not support testing higher onartuzumab doses.

To assess the link between early tumor shrinkage (ETS) and progression-free survival (PFS) based on historical first-line metastatic renal cell carcinoma (mRCC) data. Tumor size data from 921 patients with first-line mRCC who received interferon-alpha, sunitinib, sorafenib or axitinib in two Phase III studies were modeled. The relationship between model-based estimates of ETS at week 8 as well as the baseline prognostic factors and PFS was tested in multivariate log-logistic models. Model performance was evaluated using simulations of PFS distributions and hazard ratio (HR) across treatments for the two studies. In addition, an external validation was conducted using data from an independent Phase II RCC study. The relationship between expected HR of an investigational treatment vs. sunitinib and the differences in ETS was simulated. A model with a nonlinear ETS-PFS link was qualified to predict PFS distribution by ETS quartiles as well as to predict HRs of sunitinib vs. interferon-alpha and axitinib vs. sorafenib. The model also performed well in simulations of an independent study of axitinib (external validation). The simulations suggested that if a new investigational treatment could further reduce the week 8 ETS by 30 % compared with sunitinib, an expected HR [95 % predictive interval] of the new treatment vs. sunitinib would be 0.59 [0.46, 0.79]. A model has been developed that uses early changes in tumor size to predict the HR for PFS differences between treatment arms for first-line mRCC. Such a model may have utility in predicting the outcome of ongoing studies (e.g., as part of interim futility analyses), supporting early decision making and future study design for investigational agents in development for this indication.

This study aimed to develop a population pharmacokinetic/pharmacodynamic (PK/PD) model for C.E.R.A., a continuous erythropoietin receptor activator. C.E.R.A. is administered via intravenous (IV) and subcutaneous (SC) routes once every 2 weeks (Q2W) or once every 4 weeks (Q4W), respectively, to correct or maintain hemoglobin levels in chronic kidney disease (CKD) patients. Population models were specified to describe C.E.R.A. (PK) and hemoglobin (PD) concentrations over time, using data from 3 phase III, open-label, randomized, parallel-group, multicenter studies that examined IV or SC C.E.R.A. administration Q2W and Q4W in erythropoiesis-stimulating agent (ESA)-naive and ESA-treated patients. C.E.R.A. PK was described by a 1-compartment model: drug clearance = 0.75 L/d, volume of distribution = 4.72 L, and half-life = 105 hours in accordance with previous reported values. The PD model, a life span sequential PK/PD model, adequately described hemoglobin data. Dosing schedule, administration route, and study type did not affect drug-related PD parameters or system-specific parameters (eg, red blood cell life span). This model adequately described C.E.R.A.'s PK and PD properties according to C.E.R.A. posology, thus permitting simulations exploring alternative drug administration scenarios. It supports use of C.E.R.A. IV and SC; Q2W for anemia correction in ESA-Naïve CKD patients and monthly administration in the hemoglobin maintenance phase.

Oseltamivir is a potent, selective, oral neuraminidase inhibitor for the treatment and prophylaxis of influenza. Plasma concentrations of the active metabolite, oseltamivir carboxylate, are increased in the presence of probenecid, suggesting that the combination could allow for the use of reduced doses of oseltamivir. To investigate this proposal, we developed a population pharmacokinetic model and simulated the pharmacokinetics of candidate combination regimens of oral oseltamivir (45 mg and 30 mg twice a day) plus oral probenecid (500 mg/6 hourly). Probenecid plus oseltamivir 45 mg achieved all the pharmacokinetic parameters expected of oseltamivir alone, but combination with oseltamivir 30 mg and dose interval extension approaches did not. An oseltamivir-probenecid combination may compromise tolerability and enhance the potential for drug interactions. In addition, increased dosing requirements may affect compliance and attainment of optimal oseltamivir exposure, potentially facilitating the emergence of viral strains with reduced susceptibility to oseltamivir. These factors, set alongside increased capacity for oseltamivir production, should be carefully considered before an oseltamivir-probenecid combination is used.

International audience; We propose a model that characterizes and links the complexity and diversity of clinically observed hepatitis C viral kinetics to sustained virologic response (SVR)--the primary clinical end point of hepatitis C treatment, defined as an undetectable viral load at 24 weeks after completion of treatment)--in patients with chronic hepatitis C (CHC) who have received treatment with peginterferon α-2a ± ribavirin. The new attributes of our hepatitis C viral kinetic model are (i) the implementation of a cure/viral eradication boundary, (ii) employment of all hepatitis C virus (HCV) RNA measurements, including those below the lower limit of quantification (LLOQ), and (iii) implementation of a population modeling approach. The model demonstrated excellent positive (99.3%) and negative (97.1%) predictive values for SVR as well as high sensitivity (96.6%) and specificity (99.4%). The proposed viral kinetic model provides a framework for mechanistic exploration of treatment outcome and permits evaluation of alternative CHC treatment options with the ultimate aim of developing and testing hypotheses for personalizing treatments in this disease.