Clinical Pharmacology & Therapeutics最新文献

Despite growing knowledge of pregnancy-induced changes in physiology that may alter maternal and fetal pharmacokinetics, evidence-based antenatal doses are lacking for most drugs. Pharmacokinetic modeling and expanding clinical data in pregnancy may support antenatal doses. We aimed to develop and pilot a comprehensive and user-driven Framework for Dose Selection in Pregnancy to support the clinical implementation of a best-evidence antenatal dose for sertraline. After initial development and evaluation by experts, the framework prototype was piloted to formulate an antenatal dosing strategy for sertraline in depression and anxiety disorders. Next, the framework was reviewed and assessed for usability by a multidisciplinary working committee of end-users comprising healthcare practitioners, experts from other disciplines including pharmacometrics, reproductive toxicology and medical ethics, alongside pregnant women and a partner. The resulting framework encompasses the following: rationale for drug selection, a comprehensive analysis of pharmacokinetic and dose-related efficacy and safety data, and implementation aspects including feasibility and desirability of the recommended antenatal dose based on a structured maternal and fetal benefit-risk assessment. An antenatal dose recommendation for sertraline, as a case study, was formulated using this approach and endorsed for clinical use by the working committee. Future applications of the framework for other drugs can further demonstrate its suitability for developing best evidence, acceptable and clinically feasible antenatal doses.

The measurement of endogenous biomarkers in plasma and urine before and after administration of an investigational drug in a clinical study may provide an early indication of its drug-drug interaction (DDI) potential via a specific pathway. In the first international harmonized guideline on drug interaction studies, the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M12, endogenous biomarkers have been recognized as an emerging approach in the transporter- and enzyme-based DDI risk assessment. Clinical Pharmacology Roundtable Conference 2024 held at Pharmaceuticals and Medical Devices Agency (PMDA) brought together experts from regulatory agencies, academia, and industries to discuss potential advantages and challenges of the biomarkers approach in drug development and regulatory decision making. This meeting report facilitates stakeholders involved in drug development in better understanding the utility of biomarker approaches and promotes early implementation of biomarker-informed DDI evaluation in regulatory use.

The use of partial residual plots (PRPs) was explored as a model diagnostic tool in Model-based Meta-Analysis (MBMA). Mathematical derivations illustrating the concepts were followed by an MBMA example using publicly available literature data of anti-depressive treatments with fluoxetine and venlafaxine. An E_max dose-response model was identified for venlafaxine while a constant drug effect combining all dose levels vs. placebo was identified for fluoxetine. The larger the mean baseline Hamilton Depression Rating (HAMD) score, the larger the expected drug effect (P = 0.0122), based on the likelihood ratio test. Mean baseline HAMD score (range) was 25.4 (23.5, 29.4) and 20.8 (15, 26) while mean placebo change from baseline (range) was -9.02 (-12.2, -4.8) and - 6.22 (-10.9, -1.3) for venlafaxine and fluoxetine, respectively. Average baseline HAMD score appeared larger for venlafaxine compared to fluoxetine, albeit a wider range for fluoxetine. Placebo response seemed lower but also more variable in fluoxetine compared to venlafaxine studies. Observed data points tended to deviate from model predictions when the mean baseline HAMD and placebo response values associated with those data points differed substantially from the corresponding values used for the model prediction. Normalizing observed data addressed this, providing a "like-to-like" comparison with model predictions in PRP when assessing the effect of one covariate (dose) after normalizing for other covariates/effects (placebo response and mean baseline). PRPs provide a robust integrated diagnostic tool in MBMA that uses all data to show the correlation between response and any covariate while controlling for other covariates included in the model.

Recent advances have significantly enhanced our understanding of the role of membrane transporters in drug disposition, particularly focusing on their influence on pharmacokinetics, and consequently, pharmacodynamics. The relevance of these transporters in clinical pharmacology is well acknowledged. Recent research has also underscored the critical role of membrane transporters as targets in human diseases, including their involvement in rare genetic disorders. This review focuses on transporters for water-soluble B vitamins, such as thiamine, riboflavin, and biotin, essential cofactors for metabolic enzymes. Mutations in transporters, such as SLC19A3 (thiamine), SLC52A2, and SLC52A3 (riboflavin), and SLC5A6 (multiple B vitamins including pantothenic acid and biotin) are linked to severe neurological disorders due to their role in the blood-brain barrier, which is crucial for brain vitamin supply. Current treatments, mainly involving vitamin supplementation, often result in variable response. This review also provides a short perspective on the role of the transporters in the blood-cerebrospinal fluid barrier and highlights the potential development of pharmacologic treatments for rare disorders associated with mutations in these transporters.