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AimsCabotegravir delivered as a long-acting intramuscular injection has shown superior efficacy to oral tenofovir-emtricitabine as pre-exposure prophylaxis (PrEP) for HIV. Cabotegravir pharmacokinetics (PK), like those of other long-acting depot preparations, exhibit variability between individuals and between injection occasions. The aim of this study is to describe the population pharmacokinetics of long-acting cabotegravir (CAB-LA).MethodsUsing available PK measurements from 133 participants in the HIV Prevention Trials Network (HPTN) 077 trial, we analysed CAB-LA PK data using nonlinear mixed-effects modelling to develop a population PK model.ResultsA two-compartment model with first order absorption best described the CAB-LA PK. The analysis identified between-occasion variability (BOV, i.e., differences in PK within one individual from one injection to the next) as a significant covariate affecting the absorption rate, with an estimated contribution of BOV to PK variability on the absorption rate (ka ) of 38.5%. Sex and body weight were identified as significant covariates influencing the absorption rate and apparent clearance of CAB-LA after intramuscular injection at various doses and frequencies. Male participants had 67% higher ka than female participants. Serially adding to the model body weight on clearance, sex on ka , and BOV on ka led to a decrease in the objective function value (OFV) of 24.4, 36 and 321.4, respectively.ConclusionThe public availability of this model will facilitate and enable a wide variety of future clinically relevant simulations to inform the optimal use of CAB-LA.

pyDarwin is an open‐source Python package for nonlinear mixed‐effect model selection. pyDarwin combines machine‐learning algorithms and NONMEM to perform a global search for the optimal model in a user‐defined model search space. Compared with traditional stepwise search, pyDarwin provides an efficient platform for conducting an objective, robust, less labor‐intensive model selection process without compromising model interpretability. In this tutorial, we will begin by introducing the essential components and concepts within the package. Subsequently, we will provide an overview of the pyDarwin modeling workflow and the necessary files needed for model selection. To illustrate the entire process, we will conclude with an example utilizing quetiapine clinical data. [ABSTRACT FROM AUTHOR]

Keywords: Pharmacokinetics; olanzapine; antipsychotic; schizophrenia; Alzheimer's disease; clinical antipsychotic trials of intervention effectiveness; CATIE 157 PharmacokineticsSex, Race, and Smoking Impact Olanzapine Exposure SAGE Publications, Inc.200810.1177/0091270007310385 Kristin L.Bigos PhD Department of [...]

Objective: Antipsychotic drugs target dopamine and serotonin receptors as well as Kv11.1 potassium channels encoded by KCNH2. Variable patient responses and a wide range of side effects, however, limit their efficacy. Slow metabolizer status and gene variants in KCNH2 associated with increased expression of Kv11.1-3.1, an alternatively spliced isoform of Kv11.1, are correlated with improved responses to antipsychotic medications. Here, the authors test the hypothesis that these effects may be influenced by differential drug binding to Kv11.1 channel isoforms. Method: Drug block of Kv11.1 isoforms was tested in cellular electrophysiology assays. The effects of drug metabolism and KCNH2 genotypes on clinical responses were assessed in patients enrolled in the multicenter Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE). Results: Risperidone caused greater in vitro block of the alternatively spliced Kv11.1-3.1 isoform than full-length Kv11.1-1A channels, whereas its metabolite paliperidone and other atypical antipsychotics have similar potencies for the two isoforms. In the CATIE study (N=362), patients with genotypes associated with increased Kv11.1-3.1 expression (N=52) showed a better treatment response to risperidone compared with other drugs, but this association was dependent on metabolism status. Patients with KCNH2 risk genotypes and slow metabolizer status (approximately 7% of patients) showed marked improvement in symptoms when treated with risperidone compared with patients with fast metabolizer status or without the KCNH2 risk genotypes. Conclusions: These data support the hypothesis that Kv11.1 channels play a role in the therapeutic action of antipsychotic drugs, particularly risperidone, and further highlight the promise of optimizing response with genotype-guided therapy for schizophrenia patients. [ABSTRACT FROM AUTHOR]

Objective: Antidopaminergic drugs bind to hERG1 potassium channels encoded by the gene KCNH2, which accounts for the side effect of QT interval prolongation. KCNH2 has also been associated with schizophrenia risk, and risk alleles predict increased expression of a brain-selective isoform, KCNH2 3.1, that has unique physiological properties. The authors assessed whether genetic variation associated with KCNH2 3.1 expression influences the therapeutic effects of antipsychotic drugs. Method: The authors performed a pharmacogenetic analysis of antipsychotic treatment response in patients with schizophrenia using data from two independent studies: a National Institute of Mental Health (NIMH) double-blind, placebo-controlled inpatient crossover trial (N=54) and the multicenter outpatient Clinical Antipsychotic Trials in Intervention Effectiveness (CATIE) study (N=364). The KCNH2 genotype that was previously associated with increased expression of KCNH2 3.1 in the brain was treated as a predictor variable. Treatment-associated changes in symptoms were evaluated in both groups with the Positive and Negative Syndrome Scale. The authors also analyzed time to discontinuation in the olanzapine arm of the CATIE study. Results: In the NIMH study, individuals who were homozygous for the KCNH2 3.1 increased expression-associated T allele of rs1036145 showed significant improvement in positive symptoms, general psychopathology, and thought disturbance, while patients with other genotypes showed little change. In the CATIE study, analogous significant genotypic effects were observed. Moreover, individuals who were homozygous for the T allele at rs1036145 were one-fifth as likely to discontinue olanzapine. Conclusions: These consistent findings in two markedly different treatment studies support the hypothesis that hERG1-mediated effects of antipsychotics may not be limited to their potential cardiovascular side effects but may also involve therapeutic actions related to the brain-specific 3.1 isoform of KCNH2. [ABSTRACT FROM AUTHOR]

The paucity of research on gender-specific differences related to antidepressants is a significant public health deficiency and represents an understudied and necessary research area. The current data suggest that the pharmacokinetics of antidepressant drugs can be substantially different between men and women as a result of differences in both the metabolizing enzymes and the expression of P-glycoprotein MDR1. The data suggest that different pharmacodynamic responses are observed between premenopausal women and men. Women are more likely to respond better to an MAOI antidepressant compared to men. In addition, men respond better to TCAs than women in this age group, but differences diminish after menopause. Given the evidence of distinct gender-specific differences, it is critical that these differences be addressed more widely in research evaluating the administration of antidepressants in women.