Bayesian approach to investigate a two-state mixed model of COPD exacerbations The article [Bayesian approach to investigate a two-state mixed model of COPD exacerbations], written by [Anna Largajolli, Misba Beerahee, Shuying Yang], was originally published electronically on the publisher’s internet portal (currently SpringerLink) on [13 June 2019] without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on [November 2019] to © The Author(s) [2019] and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Cabozantinib exposure–response analyses of efficacy and safety in patients with advanced hepatocellular carcinoma Abstract Cabozantinib, a multi-kinase inhibitor, is approved in the United States and European Union for treatment of patients with hepatocellular carcinoma following prior sorafenib treatment. In the Phase III CELESTIAL trial, hepatocellular carcinoma patients receiving cabozantinib showed longer overall survival (OS) and progression-free survival (PFS) than those receiving placebo. The approved cabozantinib (Cabometyx®) dose is 60 mg once daily with allowable dose modifications to manage adverse events (AE). Time-to-event Cox proportional hazard exposure–response (ER) models were developed to characterize the relationship between predicted cabozantinib exposure and the likelihood of various efficacy and safety endpoints. The ER models were used to predict hazard ratios (HR) for efficacy and safety endpoints for starting doses of 60, 40, or 20 mg daily. Statistically significant relationships between cabozantinib exposure and efficacy and safety endpoints were observed. For efficacy endpoints, predicted HR were lower for OS and PFS at 40 and 60 mg relative to the 20 mg dose: HR for death (OS) are 0.84 (40 mg) and 0.70 (60 mg); HR for disease progression/death (PFS) are 0.73 (40 mg) and 0.62 (60 mg). For safety endpoints, predicted HR were lower for palmar-plantar erythrodysaesthesia (PPE), diarrhea, and hypertension at 20 or 40 mg relative to the 60 mg dose: HR for PPE are 0.31 (20 mg) and 0.66 (40 mg); HR for diarrhea are 0.61 (20 mg) and 0.86 (40 mg); HR for hypertension are 0.46 (20 mg) and 0.76 (40 mg). The rate of dose modifications was predicted to increase in patients with lower cabozantinib apparent clearance. OS and PFS showed the greatest benefit at the 60 mg dose. However, higher cabozantinib exposure was predicted to increase the likelihood of AE and subsequent dose reductions appeared to decrease these risks.

Impact of Phase 1 study design on estimation of QT interval prolongation risk using exposure–response analysis Abstract The International Council for Harmonisation (ICH) guidelines have been revised allowing for modeling of concentration-QT (C-QT) data from Phase I dose-escalation studies to be used as primary analysis for QT prolongation risk assessment of new drugs. This work compares three commonly used Phase I dose-escalation study designs regarding their efficiency to accurately identify drug effects on QT interval through C-QT modeling. Parallel group design and 4-period crossover designs with sequential or interleaving cohorts were evaluated. Clinical trial simulations were performed for each design and across different scenarios (e.g. different magnitudes of drug effect, QT variability), assuming a pre-specified linear mixed effect (LME) model for the relationship between drug concentration and change from baseline QT (ΔQT). Analyses suggest no systematic bias in either the predictions of placebo-adjusted ΔQT (ΔΔQT) or the LME model parameter estimates across all evaluated designs. Additionally, false negative rates remained similar and adequately controlled across all evaluated designs. However, compared to the crossover designs, the parallel design had significantly less power to correctly exclude a clinically significant QT effect, especially in the presence of substantial intercept inter-individual variability. In such cases, parallel design is associated with increased uncertainty around ΔΔQT prediction, mainly attributed to the uncertainty around the estimation of the treatment-specific intercept in the model. Throughout all the evaluated scenarios, the crossover design with interleaving cohorts had consistently the best performance characteristics. The results from this investigation will further facilitate informed decision-making during Phase I study design and the interpretation of the associated C-QT modeling output.

Pharmacokinetics-pharmacodynamics of sertraline as an antifungal in HIV-infected Ugandans with cryptococcal meningitis Abstract The ASTRO-CM dose-finding pilot study investigated the role of adjunctive sertraline for the treatment of HIV-associated cryptococcal meningitis in HIV-infected Ugandan patients. The present study is a post hoc pharmacokinetic-pharmacodynamic analysis of the ASTRO-CM pilot study to provide insight into sertraline exposure–response–outcome relationships. We performed a population pharmacokinetic analysis using sertraline plasma concentration data and correlated various predicted PK-PD indices with the percentage change in log10 CFU/mL from baseline. Sertraline clearance was 1.95-fold higher in patients receiving antiretroviral (ART), resulting in 49% lower drug exposure. To quantify the clinical benefit of sertraline, we estimated rates of fungal clearance from cerebrospinal fluid (CSF) of ASTRO-CM patients using Poisson model and compared the clearance rates to a historical control study (COAT) in which patients received standard Cryptococcus therapy of amphotericin B (0.7–1.0 mg/kg per day) and fluconazole (800 mg/day) without sertraline. Adjunctive sertraline significantly increased CSF fungal clearance rate compared to COAT trial and sertraline effect was dose-independent with no covariate found to affect fungal clearance including ART. Study findings suggest sertraline response could be mediated by different mechanisms than directly inhibiting the initiation of protein translation as previously suggested; this is supported by the prediction of unbound sertraline concentrations is unlikely to reach MIC concentrations in the brain. Study findings also recommend against the use of higher doses of sertraline, especially those greater than the maximum FDA-approved daily dose (200 mg/day), since they unlikely provide any additional benefits and come with greater costs and risk of adverse events.

Tumor necrosis factor-mediated disposition of infliximab in ulcerative colitis patients Abstract Ulcerative Colitis (UC) is an inflammatory bowel disease typically affecting the colon. Patients with active UC have elevated tumor necrosis factor (TNF) concentrations in serum and colonic tissue. Infliximab is a monoclonal antibody directed against TNF and binds with high affinity. Target-mediated drug disposition (TMDD) is reported for monoclonal antibodies meaning that their pharmacokinetics are affected by high target affinity. Here, a TMDD model is proposed to describe the interaction between infliximab and TNF in UC patients. Data from 20 patients with moderate to severe UC was used. Patients received standard infliximab induction therapy (5 mg kg−1) at week 0, followed by infusions at week 2 and 6. IFX, anti-drug antibodies and TNF serum concentrations were measured at day 0 (1 h after infusion), 1, 4, 7, 11, 14, 18, 21, 28 and 42. A binding model, TMDD model, and a quasi-steady state (QSS) approximation were evaluated using nonlinear mixed effects modeling (NONMEM). A two-compartment model best described the concentration–time profiles of infliximab. Typical clearance of infliximab was 0.404 L day−1 and increased with the presence of anti-drug antibodies and with lower albumin concentrations. The TMDD-QSS model best described the pharmacokinetic and pharmacodynamics data. Estimate for TNF baseline (Bmax was 19.8 pg mL−1 and the dissociation constant (Kss) was 13.6 nM. This model could eventually be used to investigate the relationship between suppression of TNF and the response to IFX therapy.

Computational framework for predictive PBPK-PD-Tox simulations of opioids and antidotes Abstract The primary goal of this work was to develop a computational tool to enable personalized prediction of pharmacological disposition and associated responses for opioids and antidotes. Here we present a computational framework for physiologically-based pharmacokinetic (PBPK) modeling of an opioid (morphine) and an antidote (naloxone). At present, the model is solely personalized according to an individual’s mass. These PK models are integrated with a minimal pharmacodynamic model of respiratory depression induction (associated with opioid administration) and reversal (associated with antidote administration). The model was developed and validated on human data for IV administration of morphine and naloxone. The model can be further extended to consider different routes of administration, as well as to study different combinations of opioid receptor agonists and antagonists. This work provides the framework for a tool that could be used in model-based management of pain, pharmacological treatment of opioid addiction, appropriate use of antidotes for opioid overdose and evaluation of abuse deterrent formulations.

Mathematical modeling of the glucagon challenge test Abstract A model for the homeostasis of glucose through the regulating hormones glucagon and insulin is described. It contains a subsystem that models the internalization of the glucagon receptor. Internalization is a mechanism in cell signaling, through which G-protein coupled receptors are taken from the surface of the cell to the endosome. The model is used to interpret data from a glucagon challenge test in which subjects have been under treatment with a novel glucagon receptor anti-sense drug which is aimed at reducing the number of receptors in the liver. It is shown how the receptor internalization results in tolerance of the blood glucose concentration to glucagon-induced hyperglycemia. We quantify the reduction of the number of receptors using the model and the data before and after treatment.

Cardiac risk assessment based on early Phase I data and PK-QTc analysis is concordant with the outcome of thorough QTc trials: an assessment based on eleven drug candidates Abstract Cardiac safety assessment is a key regulatory requirement for almost all new drugs. Until recently, one evaluation aspect was via a specifically designated, expensive, and resource intensive thorough QTc study, and a by-time-point analysis using an intersection–union test (IUT). ICH E14 Q&A (R3) (http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E14/E14_Q_As_R3__Step4.pdf) allows for analysis of the PK-QTc relationship using early Phase I data to assess QTc liability. In this paper, we compared the cardiac risk assessment based on the early Phase I analysis with that from a thorough QTc study across eleven drug candidate programs, and demonstrate that the conclusions are largely the same. The early Phase I analysis is based upon a linear mixed effect model with known covariance structure (Dosne et al. in Stat Med 36(24):3844–3857, 2017). The treatment effect was evaluated at the supratherapeutic Cmax as observed in the thorough QTc study using a non-parametric bootstrap analysis to generate 90% confidence intervals for the treatment effect, and implementation of the standardized methodology in R and SAS software yielded consistent results. The risk assessment based on the concentration–response analysis on the early Phase I data was concordant with that based on the standard analysis of the thorough QTc study for nine out of the eleven drug candidates. This retrospective analysis is consistent with and supportive of the conclusion of a previous prospective analysis by Darpo et al. (Clin Pharmacol Ther 97(4):326–335, 2015) to evaluate whether C-QTc analysis can detect QTc effects in a small study with healthy subjects.

Concentration–response modeling of ECG data from early-phase clinical studies to assess QT prolongation risk of contezolid (MRX-I), an oxazolidinone antibacterial agent Abstract The effects of contezolid (MRX-I, an oxazolidinone antibacterial agent) on cardiac repolarization were evaluated retrospectively using a population modeling approach in a Phase I study incorporating single ascending dose, multiple ascending dose, and food effect assessments. Linear mixed effect models were used to assess the relationships between MRX-I plasma concentrations and QT/QTc/∆QTc (baseline-adjusted), in which different correction methods for heart rate have been included. The upper bound of the one-sided 95% confidence interval (CI) for predicted ∆∆QTc was < 10 ms (ms) at therapeutic doses of MRX-I. Model performance/suitability was determined using diagnostic evaluations, which indicated rationality of one-stage concentration-QT model, as well as C-QT model suggested by Garnett et al. The finding demonstrated that MRX-I may have no clinical effects on the QT interval. Concentration-QT model may be an alternative to conventional thorough QT studies.