Clinical Pharmacology & Therapeutics最新文献

Ketamine provides the highest safety profile among sedatives for procedural sedation and analgesia in the pediatric emergency setting. However, it can cause vomiting and recovery agitation. No studies have examined epigenetic factors, such as microRNAs, for predicting the occurrence of these adverse events. Neuronal-derived extracellular vesicle microRNA profiles were studied to predict the occurrence of ketamine-induced vomiting and recovery agitation in children. For this aim, a single-center prospective pharmacoepigenetic study was performed and 50 children who underwent procedural sedation with intravenous ketamine as the only sedative drug were enrolled between October 2019 and November 2022. MiRNA profiling in plasma neural-derived extracellular vesicles was analyzed through next-generation sequencing and measured before treatment with ketamine. Twenty-two patients experienced vomiting or recovery agitation. Among the 16 differentially expressed microRNAs, the upregulated miR-15a-5p and miR-484 targeted genes related to N-methyl-D-aspartate (NMDA) receptor activity, including glutamate ionotropic receptor NMDA type subunit 2A (GRIN2A). Preliminary data confirmed lower GRIN2A levels in patients who developed these events. Downregulated miR-126-3p and miR-24-3p targeted AMPA receptor-associated genes. Functional analyses of gene targets revealed the enrichment of glutamatergic and neurotrophins signaling. Recovery agitation was associated with this network. Vomiting was related to dopaminergic and cholinergic systems. Three miRNAs (miR-18a-3p, miR-484, and miR-548az-5p) were identified as predictive biomarkers (AUC 0.814; 95% CI: 0.632-0.956) for ketamine-induced vomiting and recovery agitation. MicroRNA profiles can predict the development of ketamine-induced vomiting or recovery agitation in children. This study contributes to the understanding of the mechanisms underlying ketamine-induced adverse events.

BLOODPAC is a public-private consortium that develops best practices, coordinates clinical and translational research, and manages the BLOODPAC Data Commons to broadly support the liquid biopsy community and accelerate regulatory review to aid patient accessibility. BLOODPAC previously recommended 11 preanalytical minimal technical data elements (MTDEs) for BLOODPAC-sponsored studies and data submitted to BLOODPAC Data Commons. The current landscape analysis evaluates the overlap of the BLOODPAC MTDEs with current best practices, guidelines, and standards documents related to clinical and research liquid biopsy applications. Our findings indicate an existing high degree of concordance among these documents. Where differences exist, the BLOODPAC preanalytical MTDEs can be considered a minimal practicable set for organizations to utilize. These MTDEs were developed following extensive examination of best practices and iterative conversations with the U.S. FDA. BLOODPAC recommends the use of these MTDEs in submissions to data commons and to support liquid biopsy clinical trials and research globally.

Around 50% of the drugs used in children have never been tested for safety and efficacy in this vulnerable population. Immature drug elimination pathways can lead to drug toxicity when pediatric doses are determined using empirical methods such as body-surface area or body-weight-normalized adult dosing. In the absence of clinical data, physiologically-based pharmacokinetic (PBPK) modeling has emerged as a useful tool to predict drug pharmacokinetics in children. These models utilize developmental physiological data, including age-dependent differences in the abundance of drug-metabolizing enzymes and transporters (DMET), to mechanistically extrapolate adult pharmacokinetic data to children. The reported abundance data of hepatic DMET proteins in subcellular fractions isolated from frozen tissue are prone to high technical variability. Therefore, we carried out the proteomics-based quantification of hepatic drug transporters and conjugating enzymes in 50 pediatric and 8 adult human hepatocyte samples. Out of the 34 studied proteins, 28 showed a significant increase or decrease with age. While MRP6, OAT7, and SULT1E1 were highest in < 1-year-old samples, the abundance of P-gp and UGT1A4 was negligible in < 1-year-old samples and increased significantly after 1 year of age. Incorporation of the age-dependent abundance data in PBPK models can help improve pediatric dose prediction, leading to safer drug pharmacotherapy in children.

In the relentless pursuit of optimizing drug development, the intricate process of determining the ideal dosage unfolds. This involves “dose-finding” studies, crucial for providing insights into subsequent registration trials. However, the challenges intensify when tackling rare diseases. The complexity arises from poorly understood pathophysiologies, scarcity of appropriate animal models, and limited natural history understanding. The inherent heterogeneity, coupled with challenges in defining clinical end points, poses substantial challenges, hindering the utility of available data. The small affected population, low disease awareness, and restricted healthcare access compound the difficulty in conducting dose-finding studies. This white paper delves into critical dose selection aspects, focusing on key therapeutic areas, such as oncology, neurology, hepatology, metabolic rare diseases. It also explores dose selection challenges posed by pediatric rare diseases as well as novel modalities, including enzyme replacement therapies, cell and gene therapies, and oligonucleotides. Several examples emphasize the pivotal role of clinical pharmacology in navigating the complexities associated with these diseases and emerging treatment modalities.

The inhibition of renal transport proteins organic cation transporter 2 (OCT2), multidrug and toxin extrusion proteins (MATE1, MATE2-K), and organic anion transporters (OAT1, OAT3) causes clinically relevant drug-drug interactions (DDI). Endogenous biomarkers could be used to improve risk prediction of such renal DDIs. While a number of biomarkers for renal DDIs have been described so far, multiple criteria for valid biomarkers have frequently not been investigated, for example, specificity, metabolism, or food effects. Therefore, there is a need for novel biomarkers of renal DDIs. Here, we investigated the global metabolomic effects following the administration of two classical inhibitors of renal transport proteins [cimetidine (OCT2/MATEs), probenecid (OATs)] in human plasma and urine of healthy volunteers. Additionally, we investigated metabolomic effects of two inhibitors of other transporters [verapamil (P-glycoprotein), rifampin (organic anion transporting polypeptides)] as controls. This analysis shows that both cimetidine and probenecid affect compounds involved in caffeine metabolism, carnitines, and sulfates. Hierarchical cluster analysis of the effects of all four inhibitors on endogenous compounds identified multiple promising new sensitive and specific biomarker candidates for OCT2/MATE- or OAT-mediated DDIs. For OCT2/MATEs, 5-amino valeric acid betaine (median log₂-fold change of estimated renal elimination: -3.62) presented itself as a promising candidate. For OATs, estimated renal elimination of 7-methyluric acid and cinnamoylglycine (median log₂-fold changes -3.10 and -1.92, respectively) was both sensitive and specific. This study provides comprehensive information on metabolomic effects of transport protein inhibition in humans and identifies putative new sensitive and specific biomarkers for renal transporter-mediated DDIs.

Many new opportunities surround rare pediatric disease drug development, thanks to key advances in regulatory thinking and in the scientific community. As rare disease drug development brings challenges to the developers in terms of limited understanding of natural history, heterogeneity in drug response, as well as difficulty recruiting patients in pivotal trials, there has never been a greater need for quantitative integration. To understand how International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) member companies approach pediatric rare disease drug development, the rare pediatric subteam of the Clinical Pharmacology Leadership Group (CPLG) sponsored Pediatrics Working Group conducted a baseline survey to assess the four main pillars of this quantitative innovation, namely, biomarkers and surrogate end points, statistical methodologies, model-informed drug development, as well as public–private partnerships. The survey was administered by IQ and yielded 13 evaluable responders from represented companies. This article presents the key findings from this baseline identifying survey, highlighting the key blind spots, and providing insightful expert opinions to address those gaps. In summary, we call an urgent attention to the community on the opportunities to enhance integration and within-industry learnings from this analysis on aspects related to platform studies, end-to-end quantitative integration, and sharing of trial-level placebo data for better understanding of disease progression and more efficient trial designs. We collectively hope that these findings will stimulate discussion and debate around cross-industry sharing and collaboration to better delineate principles and further enhance the efficiency of rare pediatric disease drug development.