Modelling the impact of JNJ-1802, a first-in-class dengue inhibitor blocking the NS3-NS4B interaction, on in-vitro DENV-2 dynamics.

Dengue virus (DENV) is a public health challenge across the tropics and subtropics. Currently, there is no licensed prophylactic or antiviral treatment for dengue. The novel DENV inhibitor JNJ-1802 can significantly reduce viral load in mice and non-human primates. Here, using a mechanistic viral kinetic model calibrated against viral RNA data from experimental in-vitro infection studies, we assess the in-vitro inhibitory effect of JNJ-1802 by characterising infection dynamics of two DENV-2 strains in the absence and presence of different JNJ-1802 concentrations. Viral RNA suppression to below the limit of detection was achieved at concentrations of >1.6 nM, with a median concentration exhibiting 50% of maximal inhibitory effect (IC50) of 1.23x10-02 nM and 1.28x10-02 nM for the DENV-2/RL and DENV-2/16681 strains, respectively. This work provides important insight into the in-vitro inhibitory effect of JNJ-1802 and presents a first step towards a modelling framework to support characterization of viral kinetics and drug effect across different host systems.

Multiscale model of hepatitis C virus dynamics in plasma and liver following combination therapy.

This work explores the application of a physiologically structured population (PSP) framework in modeling hepatitis C virus (HCV) kinetics. To do so, a model was developed for the viral RNA load in plasma and liver as observed in 15 patients treated with a combination therapy of pegylated interferon, ribavirin, and telaprevir. By including both intracellular and extracellular processes of the HCV lifecycle, the model provided a description of the treatment effect on the intracellular HCV lifecycle. Combining PSP models with a nonlinear mixed effects approach in a single model permits a natural inclusion of the direct-acting antiviral effect on intracellular processes, which can then be integrated with the viral kinetics within the host while accounting for the interindividual variability between patients. This should allow an exploration of the treatment effect within the entire chronic HCV-infected population.

Etravirine in treatment-experienced HIV-1-infected children 1 year to less than 6 years of age.

OBJECTIVE: To describe the pharmacokinetics, safety, and efficacy of etravirine (ETR) in HIV-infected children 1 to less than 6 years of age. DESIGN: Phase I/II, open-label, multicenter, dose-finding study. METHODS: Antiretroviral therapy (ART)-experienced children in two age cohorts (I: 2 to <6 years; II: 1 to less than 2 years) received weight-based ETR, swallowed whole or dispersed in liquid, with optimized ART including a ritonavir-boosted protease inhibitor. Intensive pharmacokinetics occurred 7-18 days after starting ETR. Participants with ETR AUC12h less than 2350 ng h/ml had a dose increase and repeat pharmacokinetics. RESULTS: Twenty-six children enrolled and 21 (15 in cohort I and 6 in cohort II) had evaluable intensive pharmacokinetics sampling at the final weight-based dose. On the final dose, the geometric mean ETR AUC12h was 3823 ng h/ml for cohort I and 3328 ng h/ml for cohort II. Seven children (33.3%) on the final dose, all taking ETR dispersed, had an AUC12  h less than 2350 ng h/ml and underwent a dose increase. ETR AUC12  h was 3.8-fold higher when ETR was swallowed whole vs. dispersed, P less than 0.0001. On the final dose, 75 and 33.3% in cohorts I and II, respectively, had HIV-1 RNA 400 copies/ml or less or at least 2 log reductions from baseline at week 48. Three children (11.5%) experienced a grade at least 3 adverse event related to ETR but only 1 discontinued. CONCLUSION: ETR was well tolerated. Predefined pharmacokinetics targets were met but overall exposures were low vs. historical data in adults, particularly in young children taking dispersed tablets. A high rate of viral efficacy was observed among those aged 2 to more than 6 years but not in those less than 2 years.

A robust simulator for physiologically structured population models.

A framework to simulate physiologically structured population (PSP) models on high performance compute (HPC) infrastructure is built. Based on the model of a single cell, billions of cells can be simulated in an efficient way, allowing fast simulation of the interaction of an entire organ with other body parts. Trough combination of three state-of-the-art algorithms, the simulation time is decreased with multiple orders of magnitude. First: PSP modelling exploits the fact that a lot of the cells act the same at the same time which results in multiple orders of magnitude speed-up. Secondly, speed-up is achieved by using an unconditionally stable, partial differential equation solver which allows to trade speed for precision and allows big time stepping. Third speed-up is due to the fact that the framework is designed with HPC cluster use in mind. The PSP simulator is mathematically derived to have maximal stability.Simulation results are validated and simulation speed and accuracy are measured.

The method of averaging applied to pharmacokinetic/pharmacodynamic indirect response models.

The computational effort required to fit the pharmacodynamic (PD) part of a pharmacokinetic/pharmacodynamic (PK/PD) model can be considerable if the differential equations describing the model are solved numerically. This burden can be greatly reduced by applying the method of averaging (MAv) in the appropriate circumstances. The MAv gives an approximate solution, which is expected to be a good approximation when the PK profile is periodic (i.e. repeats its values in regular intervals) and the rate of change of the PD response is such that it is approximately constant over a single period of the PK profile. This paper explains the basis of the MAv by means of a simple mathematical derivation. The NONMEM® implementation of the MAv using the abbreviated FORTRAN function FUNCA is described and explained. The application of the MAv is illustrated by means of an example involving changes in glycated hemoglobin (HbA1c%) following administration of canagliflozin, a selective sodium glucose co-transporter 2 inhibitor. The PK/PD model applied to these data is fitted with NONMEM® using both the MAv and the standard method using a numerical differential equation solver (NDES). Both methods give virtually identical results but the NDES method takes almost 8 h to run both the estimation and covariance steps, whilst the MAv produces the same results in less than 30 s. An outline of the NONMEM® control stream and the FORTRAN code for the FUNCA function is provided in the appendices.