Clinical Pharmacology & Therapeutics最新文献

Clinical research has historically failed to include representative levels of historically underrepresented populations and these inequities continue to persist. Ensuring representativeness in clinical trials is crucial for patients to receive clinically appropriate treatment and have equitable access to novel therapies; enhancing the generalizability of study results; and reducing the need for post-marketing commitments focused on underrepresented groups. As demonstrated by recent legislation and guidance documents, regulatory agencies have shown an increased interest in understanding how novel therapies will impact the patient population that will receive them. Despite these efforts, a systematic approach to measure and optimize representativeness remains underdeveloped. Here, we introduce the novel Population Optimization, Representativeness Evaluation, and Fine-tuning Framework, designed to quantify and enhance representativeness. Our framework includes methods for evaluating overall and subgroup representativeness, identifying drivers of non-representativeness, and optimizing eligibility criteria to achieve representative populations. We demonstrate our framework by selecting patients who met the eligibility criteria for nine oncology clinical trials from a nationwide electronic health record-derived de-identified database and quantifying the representativeness of each trial's eligible population. This framework addresses gaps in current literature by providing a comprehensive, data-driven approach to enhance the representativeness of clinical trials, thereby supporting regulatory and internal decision-making processes. This framework is adaptable to various disease indications and can be extended to evaluate enrolled study samples, ensuring that clinical trials are representative.

Rare disease drug development is often challenging due to limited understanding of disease biology, heterogeneity, and small patient populations, among other reasons. For a new molecular entity to be approved for marketing under a new drug application or original biologics license application by the FDA's Center for Drug Evaluation and Research, the product should be shown to be both safe and effective. In some cases, one adequate and well-controlled clinical trial and confirmatory evidence are sufficient to establish substantial evidence of effectiveness. This important topic is the focus of a September 2023 draft guidance entitled Demonstrating Substantial Evidence of Effectiveness Based on One Adequate and Well-Controlled Clinical Investigation and Confirmatory Evidence. Most non-oncologic rare disease marketing applications (67%) approved between 2020 and 2023 utilized a single adequate and well-controlled trial plus confirmatory evidence to demonstrate effectiveness. Though different types of confirmatory evidence were utilized in different applications, mechanistic or pharmacodynamic evidence was used to support 77.5% of recent rare disease marketing applications that were approved based on one adequate and well-controlled trial plus confirmatory evidence. The quantity of confirmatory evidence necessary to support effectiveness may vary across development programs. Early and frequent discussions with the Agency to align on the developmental plan will facilitate efficient drug development and regulatory assessment.

The ICH M12 Guideline on Drug Interaction Studies is the result of a harmonization process led by global regulatory and industry experts with experience in drug-drug interaction (DDI) assessments and interpretation. The Expert Working Group (EWG) built on areas of regional consensus and identified solutions to topics lacking initial consensus. This article describes the topics addressed in the guideline, with emphasis on areas that required extensive discussion. It mentions topics that were the subject of comments during the public consultation period. The scope of the guideline is pharmacokinetic DDIs mediated by metabolic enzymes and drug transporters. It describes in vitro and clinical DDI studies and predictive modeling evaluations conducted during drug development. The understanding of DDI liability, in the context of the intended patient population, guides the development of risk management strategies. In the in vitro area, this article describes the considerations that support the use of experimentally measured fraction unbound for drugs with > 99% protein binding, modification of several in vitro criteria used to recommend a clinical DDI study and modification of DDI assessment for metabolites. Areas of close attention by the EWG for clinical evaluation included the use of endogenous biomarker studies, the use of nested DDI studies, and the establishment of no-effect boundaries. The article indicates the value of describing a general process for evaluating UGT-mediated DDIs, although specific criteria are not available. The guideline describes the current understanding of the role of predictive modeling in DDI evaluation. The topics described in this article can stimulate further growth in the science of DDI assessments.

Major depressive disorder is a common disorder in pregnancy. Although citalopram/escitalopram is the second most frequently prescribed antidepressant for pregnant people, information about its pharmacokinetics in pregnancy is limited. We investigated plasma (S)-citalopram concentration to dose (C/D) ratios across pregnancy and postpartum and the effect of pharmacogenetics on its elimination. This prospective observational cohort study enrolled 30 participants with a singleton pregnancy who chose to continue citalopram/escitalopram during pregnancy for a prior diagnosis of major depression. Monthly blood samples were obtained 24 hours post-dose across pregnancy and twice postpartum for measurement of plasma citalopram, desmethylcitalopram, and didesmethylcitalopram enantiomer concentrations. Compared with the 36-week reference, (S)-citalopram C/D ratios were not significantly different throughout pregnancy. However, the mean (S)-citalopram C/D ratio was elevated by 63% (P < 0.001) 6 to 8 weeks after delivery before it decreased to a mean C/D ratio in the later post-birth period that was marginally different than at 36 weeks (1.20 ± 0.64 vs. 0.92 ± 0.46, respectively; P = 0.06). Analyzing the results by cytochrome P 450 (CYP) 2C19 phenotype, the mean late postpartum (S)-citalopram concentration to dose ratio in intermediate metabolizers was approximately twice that in extensive, rapid, or ultrarapid metabolizers. However, at the 36-week reference point, the mean concentration to dose ratio in pregnant CYP2C19 intermediate metabolizers was 35.7% lower than the distant postpartum ratio, while the ratios in extensive and rapid/ultrarapid metabolizers were 15.4% and 18.5% lower, respectively. Without dose adjustment, people with intermediate or poor CYP2C19 activity may be at risk for subtherapeutic S-citalopram concentrations during pregnancy.

Adverse drug reactions (ADRs) are a common cause of morbidity and mortality in hospitalized patients. Identification of ADRs in clinical practice, surveillance and research is essential to prevent further harm. The aim of this study was to assess the likelihood of drugs contributing to clinically important inpatient adverse events, in order to provide a list of drug-event pairs indicating ADRs in electronic health record (EHR) data, referred to as "indicators of ADRs". We conducted a consensus process based on the RAND/UCLA Appropriateness Method for 14 ADRs. Experts were asked to rate the strength of the causal link between adverse events and potentially causative drugs on a 4-point Likert scale. Based on the median rating, drug-event pairs were categorized according to the likelihood of an ADR being present. Drug-event pairs with a median rating of ≥ 3 without disagreement were defined as indicators of certain and probable ADRs. Of the 255 drug-event pairs evaluated, 2 (1%) and 42 (16%) achieved consensus validation that they certainly and probably indicate an ADR. In addition, 137 drug-event pairs were considered as indicators of possible (54%) and 74 drug-event pairs were considered as indicators of unlikely (29%) ADRs. The provided set of content-validated indicators of clinically important inpatient ADRs can be used in clinical practice (e.g., decision support), surveillance (e.g., quality indicators) and research (e.g., outcome measures). They will be implemented in EHR data from German university hospitals to determine the prevalence of ADRs, support efficient use of pharmacist resources, and develop models predicting ADRs.

The widely prescribed oral anti-diabetic drug metformin is eliminated unchanged in the urine primarily through active tubular secretion. This process is mediated by organic cation transporter 2 (OCT2), an uptake transporter expressed on the basolateral membrane of renal proximal tubule cells. Metformin uptake into the liver, the site of action, is mediated by organic cation transporter 1 (OCT1), which is expressed on the sinusoidal membrane of hepatocytes. Sixteen healthy adults participated in a clinical pharmacokinetic drug-drug interaction study in which they were orally administered metformin (50 mg) as a dual OCT1/2 substrate alone (baseline) and with cimetidine (400 mg) as an OCT inhibitor. Relative to baseline, metformin systemic plasma exposure increased by 24% (p < 0.05) in the presence of cimetidine, which was accompanied by a disproportional decrease (8%) in metformin renal clearance (p = 0.005). Genetic variants of OCT1 and OCT2 moderately impacted the significance and magnitude of the interaction. Collectively, we hypothesized that the cimetidine-metformin interaction involves inhibition of hepatic OCT1 as well as renal OCT2. We tested this hypothesis by developing a physiologically based pharmacokinetic (PBPK) model and assessing potential OCT biomarkers in plasma and urine to gain mechanistic insight into the transporters involved in this interaction. The PBPK model predicted that cimetidine primarily inhibits hepatic OCT1 and, to a lesser extent, renal OCT2. The unchanged renal clearance of potential OCT2 biomarkers following cimetidine exposure supports a minimal role for renal OCT2 in this interaction.

Genetic factors, inflammatory cytokines such as interleukin (IL)-6 and tumor necrosis factor-α (TNF-α), and uremic substances such as 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF) have been reported to affect organic anion transporting polypeptide (OATP)1B1 transport activity. However, the relationship between OATP1B1 transport activity and these factors in patients with cancer cachexia has not been reported. This study aimed to identify the factors contributing to individual differences in OATP1B1 transport activity in patients with cancer cachexia, using coproporphyrin-I (CP-I) as an endogenous biomarker of OATP1B1 transport activity. The study recruited 114 patients with cancer cachexia who satisfied the selection criteria. The subjects were classified into pre-cachexia, cachexia, and refractory cachexia. Median [interquartile range] plasma CP-I level was higher in patients with pre-cachexia (0.91 [0.67-1.12] ng/mL) compared with the data in the general population reported previously and tended to be higher in patients with refractory cachexia (1.06 [0.78-1.64] ng/mL) than in those with cachexia (0.87 [0.62-1.07] ng/mL), suggesting that OATP1B1 transport activity may decrease with the progression of cancer cachexia. Plasma CP-I correlated positively with IL-6 and TNF-α concentrations but did not correlate with OATP1B1 polymorphisms or CMPF concentration, which have been reported to reduce transport activity. Multiple regression analysis using the forced entry method identified refractory cachexia as a significant factor independently affecting plasma CP-I concentration. These findings suggest that the reduction in OATP1B1 transport activity in patients with cancer cachexia may be attributed to inflammatory cytokines or some other factors that are elevated by cancer cachexia progression, rather than OATP1B1 polymorphisms and CMPF.

Pediatric patients with advanced-stage newly diagnosed Hodgkin lymphoma (HL) were treated with brentuximab vedotin (BV) combined with adriamycin, vinblastine, and dacarbazine (A + AVD). Weight-based BV dosing is employed in adult patients, while both body weight- and body surface area (BSA)-based dosing are used in pediatric patients. Data from two pediatric studies were used for a population pharmacokinetics (PK) analysis. Study 1 was a phase I/II dose-escalation study in which patients with relapsed or refractory systemic anaplastic large-cell lymphoma or HL received single-agent weight-based BV 1.4-1.8 mg/kg every 3 weeks. Study 2 tested BSA-based BV 48 mg/m² every 2 weeks with AVD in patients with advanced-stage, newly diagnosed HL. Sources of PK variability were quantified using nonlinear mixed-effects modeling. The relationships between antibody-drug conjugate (ADC) or payload monomethyl auristatin E (MMAE) exposures and progression-free survival (PFS) or incidence of adverse events were analyzed by Cox proportional hazards and logistic regression, respectively. Population PK models of ADC and MMAE were developed using data from 95 patients. BSA was identified as a significant covariate for the clearance of ADC and MMAE. BSA-based BV dosing resulted in similar systemic exposures of ADC and MMAE in pediatric patients across age groups (< 12, 12-16, and > 16 years). A significant increase (P < 0.05) in the incidence of febrile neutropenia was related to increasing exposure of MMAE. No apparent relationship was identified between ADC or MMAE exposures and PFS. The analyses support BSA-based BV dosing in combination with AVD in pediatric patients.

While endogenous cortisol secretion rises in the early morning, the number of lymphocytes in the blood is higher at night, thus exhibiting an antiphase pattern to cortisol secretion. Therefore, compared with the daytime, the infiltration of lymphocytes into immune-reactive tissues is enhanced at night. This study aimed to determine whether the administration of methylprednisolone (mPSL) in the evening is more effective against T cell-mediated rejection (TCMR) after liver transplantation compared with morning administration. This study used a randomized, open-label, parallel-group comparison design. Pediatric patients scheduled to undergo living-donor liver transplantation were randomly divided into morning (8:00 a.m.) and evening (8:00 p.m.) mPSL administration groups. The primary endpoint was the occurrence of TCMR within 14 days of surgery. Sixty-two patients were enrolled between 2014 and 2023, and six patients were excluded from the analysis as their dose of mPSL deviated from the protocol within 14 days after surgery. Of the 56 subjects analyzed, TCMR was detected in 10 of the morning group (n = 29) and three of the evening group (n = 27) within 14 days after surgery. Stratified analysis of patients who did not receive preoperative rituximab treatment showed that none of the evening group and 36.4% of the morning group developed TCMR within 14 days after surgery (P < 0.01, 95% confidence interval; 2.00-infinity). Safety evaluation results were comparable between the two groups. This study shows that the evening administration of mPSL is an effective approach for suppressing TCMR. This study is hypothesis generating, and replication in further studies is needed.