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Background and aims RO7062931 is an N-acetylgalactosamine (GalNAc)-conjugated single-stranded locked nucleic acid oligonucleotide complementary to HBV RNA. GalNAc conjugation targets the liver through the asialoglycoprotein receptor (ASGPR). This two-part phase 1 study evaluated the safety, pharmacokinetics, and pharmacodynamics of RO7062931 in healthy volunteers and patients with chronic hepatitis B (CHB) who were virologically suppressed. Approach and results Part 1 was a single ascending dose study in healthy volunteers randomized to receive a single RO7062931 dose (0.1-4.0 mg/kg), or placebo. Part 2 was a multiple ascending dose study in patients with CHB randomized to receive RO7062931 at 0.5, 1.5, or 3.0 mg/kg or placebo every month for a total of 2 doses (Part 2a) or RO7062931 at 3.0 mg/kg every 2 weeks, 3.0 mg/kg every week (QW), or 4.0 mg/kg QW or placebo for a total of 3-5 doses (Part 2b). Sixty healthy volunteers and 59 patients received RO7062931 or placebo. The majority of adverse events (AEs) reported were mild in intensity. Common AEs included self-limiting injection site reactions and influenza-like illness. Supradose-proportional increases in RO7062931 plasma exposure and urinary excretion occurred at doses ≥3.0 mg/kg. In patients with CHB, RO7062931 resulted in dose-dependent and time-dependent reduction in HBsAg versus placebo. The greatest HBsAg declines from baseline were achieved with the 3.0 mg/kg QW dose regimen (mean nadir ~0.5 log10 IU/mL) independent of HBeAg status. Conclusions RO7062931 is safe and well tolerated at doses up to 4.0 mg/kg QW. Supradose-proportional exposure at doses of 3.0-4.0 mg/kg was indicative of partial saturation of the ASGPR-mediated liver uptake system. Dose-dependent declines in HBsAg demonstrated target engagement with RO7062931.

The pharmacokinetics (PK) of RO7049389, a new hepatitis B virus (HBV) core protein allosteric modulator of class I, and of its active metabolite M5 were studied in fasted and fed conditions after single and multiple once-a-day and twice-a-day doses in healthy subjects and patients with HBV. The nonlinearity of the pharmacokinetics, the large variability, the small sample size per dose arms, the higher plasma exposure in Asians, and the heterogeneity in patient baseline characteristics seen in phase I studies made the ethnic sensitivity assessment and the selection of the recommended phase II dose difficult. A population PK model, simultaneously modeling RO7049389 and M5, was developed to characterize the complex PK, quantify ethnicity (i.e., Asian vs. non-Asian) and gender effects on the PK of RO7049389 and M5, and infer the quantity of RO7049389 in liver relative to plasma. Exposures in the liver are of particular importance for dose selection since the liver is the site of action of the compound. The model described and reproduced the population PK profiles as well as the between-subject variability of RO7049389 and its metabolite. It could show that the PK is similar between healthy subjects and in HBV patients, once the ethnicity and gender effects are accounted for. The model predicts that, despite a large difference in the plasma exposure of RO7049389 between Asians and non-Asians, the exposure in the liver is comparable, allowing the use of the same dose to treat Asian and non-Asian patients. This model provides a valuable basis to develop this new anti-HBV drug and to define optimal dosing.

Aim Pharmacologic effects were analysed to determine a dose recommendation for oseltamivir in immunocompromised (IC) adults with influenza. Methods Quantitative clinical pharmacology methods were applied to data from 160 adult IC patients (aged 18-78 years) from two studies (NV20234, 150 patients; NV25118, 10 patients) who received oseltamivir 75-200 mg twice daily for up to 10 days. An established population-pharmacokinetic (PK) model with additional effects on oseltamivir and oseltamivir carboxylate (OC) clearance described the PK characteristics of oseltamivir in IC patients versus otherwise healthy (OwH) patients from previous clinical trials. Estimated PK parameters were used to evaluate exposure-response relationships for virologic endpoints (time to cessation of viral shedding, viral load measures and treatment-emergent resistance). A drug-disease model characterized the viral kinetics of influenza accounting for the effect of OC on viral production. Results Oseltamivir clearance was 32.5% lower (95% confidence interval [CI], 26.1-38.8) and OC clearance was 33.7% lower (95% CI, 23.2-44.1) in IC versus OwH patients. No notable exposure-response relationships were identified for exposures higher than those achieved after conventional dose oseltamivir 75 mg, which appeared to be close to the maximum effect of oseltamivir. Simulations of the drug-disease model predicted that initiating treatment within 48 hours of symptom onset had maximum impact, and a treatment duration of 10 days was favourable over 3-5 days to limit viral rebound. Conclusions Our findings support the use of conventional-dose oseltamivir 75 mg twice daily for 10 days in the treatment of IC adult patients with influenza.

Additional results using our modelling framework with other datasets, the SARS-CoV-2 serial interval distributions that we used, and results from a simulation study.

During infectious disease outbreaks, inference of summary statistics characterizing transmission is essential for planning interventions. An important metric is the time-dependent reproduction number (Rt), which represents the expected number of secondary cases generated by each infected individual over the course of their infectious period. The value ofRtvaries during an outbreak due to factors such as varying population immunity and changes to interventions, including those that affect individuals' contact networks. While it is possible to estimate a single population-wideRt, this may belie differences in transmission between subgroups within the population. Here, we explore the effects of this heterogeneity onRtestimates. Specifically, we consider two groups of infected hosts: those infected outside the local population (imported cases), and those infected locally (local cases). We use a Bayesian approach to estimateRt, made available for others to use via an online tool, that accounts for differences in the onwards transmission risk from individuals in these groups. Using COVID-19 data from different regions worldwide, we show that different assumptions about the relative transmission risk between imported and local cases affectRtestimates significantly, with implications for interventions. This highlights the need to collect data during outbreaks describing heterogeneities in transmission between different infected hosts, and to account for these heterogeneities in methods used to estimateRt.This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

AIMS To optimise the dosing regimen of oseltamivir for immunocompromised (IC) paediatric patients (

To aid understanding of the effect of antiviral treatment on population-level influenza transmission, we used a novel pharmacokinetic–viral kinetic transmission model to test the correlation between nasal viral load and infectiousness, and to evaluate the impact that timing of treatment with the antivirals oseltamivir or baloxavir has on influenza transmission. The model was run under three candidate profiles whereby infectiousness was assumed to be proportional to viral titer on a natural-scale, log-scale, or dose–response model. Viral kinetic profiles in the presence and absence of antiviral treatment were compared for each individual (N = 1000 simulated individuals); subsequently, viral transmission mitigation was calculated. The predicted transmission mitigation was greater with earlier administration of antiviral treatment, and with baloxavir versus oseltamivir. When treatment was initiated 12–24 hours post symptom onset, the predicted transmission mitigation was 39.9–56.4% for baloxavir and 26.6–38.3% for oseltamivir depending on the infectiousness profile. When treatment was initiated 36–48 hours post symptom onset, the predicted transmission mitigation decreased to 0.8–28.3% for baloxavir and 0.8–19.9% for oseltamivir. Model estimates were compared with clinical data from the BLOCKSTONE post-exposure prophylaxis study, which indicated the log-scale model for infectiousness best fit the observed data and that baloxavir affords greater reductions in secondary case rates compared with neuraminidase inhibitors. These findings suggest a role for baloxavir and oseltamivir in reducing influenza transmission when treatment is initiated within 48 hours of symptom onset in the index patient.

Prompt antiviral treatment has the potential to reduce influenza virus transmission to close contacts, but rigorous data on the magnitude of treatment effects on transmission are limited. Animal model data indicate that rapid reductions in viral replication after antiviral treatment reduce the risk of transmission. Observational and clinical trial data with oseltamivir and other neuraminidase inhibitors indicate that prompt treatment of household index patients seems to reduce the risk of illness in contacts, although the magnitude of the reported effects has varied widely across studies. In addition, the potential risk of transmitting drug-resistant variants exists with all approved classes of influenza antivirals. A controlled trial examining baloxavir treatment efficacy to reduce transmission, including the risk of transmitting virus with reduced baloxavir susceptibility, is currently in progress. If reduced transmission risk is confirmed, modeling studies indicate that early treatment could have major epidemiologic benefits in seasonal and pandemic influenza.

Accurate prediction of COVID-19 cases can optimize clinical trial recruitment, inform mitigation strategies and facilitate rapid medication development. Here we present a country-specific, modified Susceptible, Exposed, Infectious, Removed (SEIR) model of SARS-CoV-2 transmission using data from the Johns Hopkins University COVID-19 Dashboard. Inter-country differences in initial exposure, cultural/environmental factors, reporting requirements and stringency of mitigation strategies were incorporated. Asymptomatic patients and super-spreaders were also factored into our model. Using these data, our model estimated 65.8% of cases as asymptomatic; symptomatic and asymptomatic people were estimated to infect 2.12 and 5.83 other people, respectively. An estimated 9.55% of cases were super-spreaders with a 2.11-fold higher transmission rate than average. Our model estimated a mean maximum infection rate of 0.927 cases/day (inter-country range, 0.63–1.41) without mitigation strategies. Mitigation strategies with a stringency index value of ≥60% were estimated to be required to reduce the reproduction ratio below 1. It was predicted that cases over the next 2 months would differ between countries, with certain countries likely to experience an accelerated accumulation of cases. Together, results from our model can guide distribution of diagnostic tests, impact clinical trial development, support medication development and distribution and inform mitigation strategies to reduce COVID-19 spread.Key FindingsPredicting COVID-19 cases can inform medication development and mitigation strategiesWe created a modified SEIR model of SARS-CoV-2 transmissionWe integrated asymptomatic cases, super-spreaders and hotspots that drive viral spreadMitigation strategies with a stringency index of ≥60% are required to reduce the RR below 1Some countries may experience an accelerated accumulation of cases in the coming months

International audience; The paucity of experimental data makes both inference and prediction particularly challenging in viral dynamic models. In the presence of several candidate models, a common strategy is model selection (MS), in which models are fitted to the data but only results obtained with the "best model" are presented. However, this approach ignores model uncertainty, which may lead to inaccurate predictions. When several models provide a good fit to the data, another approach is model averaging (MA) that weights the predictions of each model according to its consistency to the data. Here, we evaluated by simulations in a nonlinear mixed-effect model framework the performances of MS and MA in two realistic cases of acute viral infection, i.e., (1) inference in the presence of poorly identifiable parameters, namely, initial viral inoculum and eclipse phase duration, (2) uncertainty on the mechanisms of action of the immune response. MS was associated in some scenarios with a large rate of false selection. This led to a coverage rate lower than the nominal coverage rate of 0.95 in the majority of cases and below 0.50 in some scenarios. In contrast, MA provided better estimation of parameter uncertainty, with coverage rates ranging from 0.72 to 0.98 and mostly comprised within the nominal coverage rate. Finally, MA provided similar predictions than those obtained with MS. In conclusion, parameter estimates obtained with MS should be taken with caution, especially when several models well describe the data. In this situation, MA has better performances and could be performed to account for model uncertainty.

AIM The aim of the study was to simplify the dosing regimen of peginterferon alfa-2a in paediatric patients with chronic hepatitis C. METHODS A population pharmacokinetic (PK) model was developed using PK data from 14 children aged 2-8 years and 402 adults. Simulations were produced to identify a simplified dosing regimen that would provide exposures similar to those observed in the paediatric clinical trials and in the range known to be safe/efficacious in adults. Model predictions were evaluated against observed adult and paediatric data to reinforce confidence of the proposed dosing regimen. RESULTS The final model was a two compartment model with a zero order resorption process. Covariates included a linear influence of body surface area (BSA) on apparent oral clearance (CL/F) and a linear influence of body weight on apparent volume of distribution of the central compartment (V1 /F). A simplified dosing regimen was developed which is expected to provide exposures in children aged ≥5 years similar to the dosing formula used in the paediatric clinical trial and within the range that is safe/efficacious in adults. This simplified regimen is approved in the EU and in other countries for the treatment of chronic hepatitis C in treatment-naive children/adolescents aged ≥5 years in combination with ribavirin. CONCLUSION Pre-existing adult PK data were combined with relatively limited paediatric PK data to develop a PK model able to predict exposure in both populations adequately. This provided increased confidence in characterizing PK in children and helped in the development of a simplified dosing regimen of peginterferon alfa-2a in paediatric patients.

BackgroundViral kinetic models have proven useful in characterizing treatment effectiveness during HCV therapy with interferon (IFN) as well as with direct-acting antivirals (DAAs).MethodsHere we use a pharmacokinetic/viral kinetic (PK/VK) model to describe HCV RNA kinetics during treatment with setrobuvir, a non-nucleosidic inhibitor of the HCV NS5B polymerase enzyme. Using PK data from three studies in healthy volunteers and PK and VK data from a Phase I study, where setrobuvir was administered for 3 days, we fitted a two-compartment PK model with first-order absorption and lag-time, an Emax pharmacodynamics model and a standard biphasic VK model.ResultsSetrobuvir's EC50and Hill coefficient and the viral clearance rate were significantly different ( P=0.014, PConclusionsUnderstanding the combined effects of PK/VK on the performance of a non-nucleoside polymerase inhibitor such as setrobuvir could provide valuable insights into their use in combination with other DAAs as well as to optimize future therapy. Further, our work suggests that patients infected with subtype 1a would need higher doses than those infected with subtype 1b to achieve the same effectiveness. Whether this is true for other non-nucleoside polymerase inhibitors needs to be examined.

Background We conducted a phase II study of oral capecitabine rapidly disintegrating tablets given concurrently with radiation therapy (RT) to assess progression-free survival (PFS) in children with newly diagnosed diffuse intrinsic pontine gliomas (DIPG). Patients and methods Children 3-17 years with newly diagnosed DIPG were eligible. Capecitabine, 650 mg/m2 /dose BID (maximum tolerated dose [MTD] in children with concurrent radiation), was administered for 9 weeks starting the first day of RT. Following a 2-week break, three courses of capecitabine, 1,250 mg/m2 /dose BID for 14 days followed by a 7-day rest, were administered. As prospectively designed, 10 evaluable patients treated at the MTD on the phase I trial were included in the phase II analyses. The design was based on comparison of the PFS distribution to a contemporary historical control (n = 140) with 90% power to detect a 15% absolute improvement in the 1-year PFS with a type-1 error rate, α = 0.10. Results Forty-four patients were evaluable for the phase II objectives. Capecitabine and RT was well tolerated with low-grade palmar plantar erythrodyesthesia, increased alanine aminotransferase, cytopenias, and vomiting the most commonly reported toxicities. Findings were significant for earlier progression with 1-year PFS of 7.21% (SE = 3.47%) in the capecitabine-treated cohort versus 15.59% (SE = 3.05%) in the historical control (P = 0.007), but there was no difference for overall survival (OS) distributions (P = 0.30). Tumor enhancement at diagnosis was associated with shorter PFS and OS. Capecitabine was rapidly absorbed and converted to its metabolites. Conclusion Capecitabine did not improve the outcome for children with newly diagnosed DIPG.

BackgroundViral kinetic models have proven useful to characterize treatment effectiveness during HCV therapy with interferon (IFN) or with direct-acting antivirals.MethodsWe use a pharmacokinetic/viral kinetic (PK/VK) model to describe HCV RNA kinetics during treatment with danoprevir, a protease inhibitor. In a Phase I study, danoprevir monotherapy was administered for 14 days in ascending doses ranging from 200 to 600 mg per day to 40 patients of whom 32 were treatment-naive and 8 were non-responders to prior pegylated IFN-α/ribavirin treatment.ResultsIn all patients, a biphasic decline of HCV RNA during therapy was observed. A two-compartment PK model and a VK model that considered treatment effectiveness to vary with the predicted danoprevir concentration inside the second compartment provided a good fit to the viral load data. A time-varying effectiveness model was also used to fit the viral load data. The antiviral effectiveness increased in a dose-dependent manner, with a 14-day time-averaged effectiveness of 0.95 at the lowest dose (100 mg twice daily) and 0.99 at the highest dose (200 mg three times daily). Prior IFN non-responders exhibited a 14-day time-averaged effectiveness of 0.98 (300 mg twice daily). The second phase decline showed two different behaviours, with 30% of patients exhibiting a rapid decline of HCV RNA, comparable to that seen with other protease inhibitors (>0.3 day-1), whereas the viral decline was slower in the other patients.ConclusionsOur results are consistent with the modest SVR rates from the INFORM-SVR study where patients were treated with a combination of mericitabine and ritonavir-boosted danoprevir.

BackgroundModelling HCV RNA decline kinetics under therapy has proven useful for characterizing treatment effectiveness.MethodsHere we model HCV viral kinetics (VK) in 72 patients given a combination of danoprevir, a protease inhibitor, and mericitabine, a nucleoside polymerase inhibitor, for 14 days in the INFORM-1 trial. A biphasic VK model with time-varying danoprevir and mericitabine effectiveness and Bliss independence for characterizing the interaction between both drugs provided the best fit to the VK data.ResultsThe average final antiviral effectiveness of the drug combination varied between 0.998 for 100 mg three times daily of danoprevir and 500 mg twice daily of mericitabine and 0.9998 for 600 mg twice daily of danoprevir and 1,000 mg twice daily of mericitabine. Using the individual parameters estimated from the VK data collected over 2 weeks, we were not able to reproduce the low sustained virological response rates obtained in a more recent study where patients were treated with a combination of mericitabine and ritonavir-boosted danoprevir for 24 weeks.ConclusionsThis suggests that drug-resistant viruses emerge after 2 weeks of treatment and that longer studies are necessary to provide accurate predictions of longer treatment outcomes.

A population drug-disease model was developed to describe the time course of influenza virus with and without oseltamivir treatment and to investigate opportunities for antiviral combination therapy. Data included viral titers from 208 subjects, across 4 studies, receiving placebo and oseltamivir at 20 to 200 mg twice daily for 5 days. A 3-compartment mathematical model, comprising target cells infected at rate β, free virus produced at rate p and cleared at rate c , and infected cells cleared at rate δ, was implemented in NONMEM with an inhibitory Hill function on virus production ( p ), accounting for the oseltamivir effect. In congruence with clinical data, the model predicts that the standard 75-mg regimen initiated 2 days after infection decreased viral shedding duration by 1.5 days versus placebo; the 150-mg regimen decreased shedding by an additional average 0.25 day. The model also predicts that initiation of oseltamivir sooner postinfection, specifically at day 0.5 or 1, results in proportionally greater decreases in viral shedding duration of 5 and 3.5 days, respectively. Furthermore, the model suggests that combining oseltamivir (acting to subdue virus production rate) with an antiviral whose activity decreases viral infectivity (β) results in a moderate additive effect dependent on therapy initiation time. In contrast, the combination of oseltamivir with an antiviral whose activity increases viral clearance ( c ) shows significant additive effects independent of therapy initiation time. The utility of the model for investigating the pharmacodynamic effects of novel antivirals alone or in combination on emergent influenza virus strains warrants further investigation.

The aim of the study was to simplify the dosing regimen of peginterferon alfa-2a in paediatric patients with chronic hepatitis C.A population pharmacokinetic (PK) model was developed using PK data from 14 children aged 2-8 years and 402 adults. Simulations were produced to identify a simplified dosing regimen that would provide exposures similar to those observed in the paediatric clinical trials and in the range known to be safe/efficacious in adults. Model predictions were evaluated against observed adult and paediatric data to reinforce confidence of the proposed dosing regimen.The final model was a two compartment model with a zero order resorption process. Covariates included a linear influence of body surface area (BSA) on apparent oral clearance (CL/F) and a linear influence of body weight on apparent volume of distribution of the central compartment (V1 /F). A simplified dosing regimen was developed which is expected to provide exposures in children aged ≥5 years similar to the dosing formula used in the paediatric clinical trial and within the range that is safe/efficacious in adults. This simplified regimen is approved in the EU and in other countries for the treatment of chronic hepatitis C in treatment-naive children/adolescents aged ≥5 years in combination with ribavirin.Pre-existing adult PK data were combined with relatively limited paediatric PK data to develop a PK model able to predict exposure in both populations adequately. This provided increased confidence in characterizing PK in children and helped in the development of a simplified dosing regimen of peginterferon alfa-2a in paediatric patients.

A new subcutaneous (s.c.) trastuzumab formulation provides savings in terms of time and is preferred by patients and health care professionals relative to standard intravenous (i.v.) administration due to simpler and more rapid administration (2-5 minutes). Selection of the s.c. dose was based on a pharmacokinetic bridging approach that aimed to achieve noninferior trastuzumab serum trough concentrations (Ctrough) vs. reference i.v. administration. Using population modeling and simulation, we showed that a fixed 600-mg trastuzumab s.c. dose, administered thrice-weekly (Q3W) without a loading dose, would provide Ctrough (predose Cycle 8) and area under the time-concentration curve (AUC0-21 days, Cycle 7) at least as high as Q3W i.v. administration. The model was retrospectively validated using observed pharmacokinetic data from an independent phase III study of (neo)adjuvant trastuzumab (HannaH). These results provide a strong pharmacokinetic rationale for the trastuzumab s.c. 600-mg fixed dose, supported by the noninferior efficacy of this regimen vs. reference i.v. administration.CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e87; doi:10.1038/psp.2013.63; advance online publication 2 January 2014.

Volume 59, no. 9, p. [5388–5395][1], 2015. Page 5391, Table 2: It was brought to our attention that there was an inadvertent error in reporting the residual error term (σerror, Table 2) in our model. The minor error is isolated and has no impact on the stated objectives of the paper, the

AIMS: A descriptive survey of published population pharmacokinetic and/or pharmacodynamic (PK/PD) analyses from 2002 to 2004 was conducted and an evaluation made of how model building was performed and reported. METHODS: We selected 324 articles in Pubmed using defined keywords. A data abstraction form (DAF) was then built comprising two parts: general characteristics including article identification, context of the analysis, description of clinical studies from which the data arose, and model building, including description of the processes of modelling. The papers were examined by two readers, who extracted the relevant information and transmitted it directly to a MySQL database, from which descriptive statistical analysis was performed. RESULTS: Most published papers concerned patients with severe pathology and therapeutic classes suffering from narrow therapeutic index and/or high PK/PD variability. Most of the time, modelling was performed for descriptive purposes, with rich rather than sparse data and using NONMEM software. PK and PD models were rarely complex (one or two compartments for PK; E(max) for PD models). Covariate testing was frequently performed and essentially based on the likelihood ratio test. Based on a minimal list of items that should systematically be found in a population PK-PD analysis, it was found that only 39% and 8.5% of the PK and PD analyses, respectively, published from 2002 to 2004 provided sufficient detail to support the model-building methodology. CONCLUSIONS: This survey allowed an efficient description of recent published population analyses, but also revealed deficiencies in reporting information on model building.

Model evaluation is an important issue in population analyses. We aimed to perform a systematic review of all population pharmacokinetic and/or pharmacodynamic analyses published between 2002 and 2004 to survey the current methods used to evaluate models and to assess whether those models were adequately evaluated. We selected 324 articles in MEDLINE using defined key words and built a data abstraction form composed of a checklist of items to extract the relevant information from these articles with respect to model evaluation. In the data abstraction form, evaluation methods were divided into three subsections: basic internal methods (goodness-of-fit [GOF] plots, uncertainty in parameter estimates and model sensitivity), advanced internal methods (data splitting, resampling techniques and Monte Carlo simulations) and external model evaluation. Basic internal evaluation was the most frequently described method in the reports: 65% of the models involved GOF evaluation. Standard errors or confidence intervals were reported for 50% of fixed effects but only for 22% of random effects. Advanced internal methods were used in approximately 25% of models: data splitting was more often used than bootstrap and cross-validation; simulations were used in 6% of models to evaluate models by a visual predictive check or by a posterior predictive check. External evaluation was performed in only 7% of models. Using the subjective synthesis of model evaluation for each article, we judged the models to be adequately evaluated in 28% of pharmacokinetic models and 26% of pharmacodynamic models. Basic internal evaluation was preferred to more advanced methods, probably because the former is performed easily with most software. We also noticed that when the aim of modelling was predictive, advanced internal methods or more stringent methods were more often used.

Model evaluation is an important issue in population analyses. We aimed to perform a systematic review of all population pharmacokinetic and/or pharmacodynamic analyses published between 2002 and 2004 to survey the current methods used to evaluate models and to assess whether those models were adequately evaluated. We selected 324 articles in MEDLINE using defined key words and built a data abstraction form composed of a checklist of items to extract the relevant information from these articles with respect to model evaluation. In the data abstraction form, evaluation methods were divided into three subsections: basic internal methods (goodness-of-fit [GOF] plots, uncertainty in parameter estimates and model sensitivity), advanced internal methods (data splitting, resampling techniques and Monte Carlo simulations) and external model evaluation. Basic internal evaluation was the most frequently described method in the reports: 65% of the models involved GOF evaluation. Standard errors or confidence intervals were reported for 50% of fixed effects but only for 22% of random effects. Advanced internal methods were used in approximately 25% of models: data splitting was more often used than bootstrap and cross-validation; simulations were used in 6% of models to evaluate models by a visual predictive check or by a posterior predictive check. External evaluation was performed in only 7% of models. Using the subjective synthesis of model evaluation for each article, we judged the models to be adequately evaluated in 28% of pharmacokinetic models and 26% of pharmacodynamic models. Basic internal evaluation was preferred to more advanced methods, probably because the former is performed easily with most software. We also noticed that when the aim of modelling was predictive, advanced internal methods or more stringent methods were more often used.