Clinical Pharmacology & Therapeutics最新文献

Drug dose appropriateness is one of the most discussed issues in regulatory reviews. We analyzed dose determinations during Food and Drug Administration (FDA) drug reviews to determine whether there were changes between the proposed and approved doses of new molecular entities (NMEs), including cases where postmarketing dose-finding studies were requested, and explored the factors associated with these decisions. Of the 218 eligible NMEs approved between 2018 and 2022, 28 drugs (13%) had modifications to the proposed dose or requested additional postmarketing assessments, 20 of which were to a lower dose ("downward," 9.2%) and five were to a higher dose ("upward," 2.3%). Multinomial logistic regression analysis suggested that products that used the Accelerated Approval program were more likely to undergo downward modification (relative risk ratio (RRR) = 5.73). In addition, the fact that a dose/exposure-response relationship was observed for safety, but not efficacy, was associated with an increased probability of downward modifications (RRR: 4.27). In contrast, the use of pharmacodynamic biomarkers for dose setting and designation of Priority Review was associated with decreased probabilities of downward change (RRR: 0.405 and 0.195, respectively). Infectious disease drugs went through more upward modifications than those in the other therapeutic categories. This study revealed that dose "optimization" occurs during the FDA's review for drug approval and that not only product characteristics but also factors related to the drug review and approval process are associated with the decisions to modify or question the dose, suggesting considerations for the presence of compelling evidence and restrictions in data availabilities.

PBPK models are gaining special interest as a drug development tool to estimate the effect of intrinsic and extrinsic factors on drug pharmacokinetics. The IQ Consortium Clinical Pharmacology Organ Impairment Working Group conducted a survey across IQ Consortium member pharmaceutical companies to understand current practices on how PBPK is used in understanding the effect of hepatic impairment (HI) on drug disposition and its impact on clinical development. Responses from 21 participants indicated that most organizations (~86%) are already using PBPK models for HI assessment. The survey results indicate that PBPK models have been influential in optimizing the design of dedicated HI study with 57% of respondents using PBPK models to inform the design elements of dedicated HI studies, and the majority of these respondents using the PBPK model to support internal decision making regarding the HI study. Additionally, the PBPK model was used by 62% of the respondents to predict drug plasma protein binding. Despite common usage of the PBPK models by drug developers, 14.3% of the respondents discussed their PBPK modeling strategy with regulatory agencies with only two cases where the regulators accepted the PBPK model. In conclusion, although the use of PBPK models to support regulatory decisions regarding drug use in HI is currently limited, its future is promising, and the success of such models needs collaboration between regulators and drug developers to shrink the knowledge gap in the use of PBPK as an impactful tool for drug development in patients with HI.

Less frequent adverse drug reactions are usually discovered after a drug's release to the market, making effective and timely communication of regulatory post-market advisories essential for preventing emerging adverse effects. Time series analysis is a key study design for assessing the impact of post-market safety advisories. However, most previous studies have focused on narrow evaluations, limiting systematic assessment of how different safety advisories affect prescribing practices. This study aimed to investigate changes in prescribing practices following regulatory post-market safety advisories in Korea. Interrupted time series analyses were conducted using nationwide claims data from 2018 to 2021 and hospital datasets covering the period from 2 years before and 3 years after post-market safety advisories. We categorized the selected drugs into two groups: safety warning through letters and real-time safety alarms (contraindications or requiring attention). Twelve post-market safety advisories were analyzed, including four safety warnings and eight safety alarms, which showed an overall relative reduction (safety warning: relative change [95% confidence interval]: -8.06% [-10.23% to -5.84%], safety alarm on contraindication: -92.65% [-95.65% to -87.59%], and safety alarm on requiring attention: -8.04% [-9.98% to -6.05%]). All types of regulatory interventions reduced the prescribing of targeted drugs; however, the magnitude of these effects differed substantially depending on the type of intervention. By identifying and comparing the influence of regulatory post-market safety advisories, we can enhance these measures to better protect patient health. Continuous monitoring and systematic assessment of safety-related regulatory advisories, with ensured reproducibility, are warranted to optimize effectiveness and ensure safe medication practices.

Clinical cocktails for cytochrome P450 (CYP) phenotyping lack a marker for CYP2C8. We aimed to combine the CYP2C8 index drug repaglinide with the Geneva cocktail (caffeine/CYP1A2, bupropion/CYP2B6, flurbiprofen/CYP2C9, omeprazole/CYP2C19, dextromethorphan/CYP2D6, and midazolam/CYP3A4). We also included endogenous organic anion transporting polypeptide (OATP) 1B1 and 1B3 biomarkers glycochenodeoxycholate 3-O-glucuronide and glycochenodeoxycholate 3-sulfate, and investigated the CYP2C8 inhibition selectivity of clopidogrel and gemfibrozil with the full cocktail. In a five-phase randomized cross-over study, the following drugs were administered to 16 healthy volunteers: (i) repaglinide, (ii) the Geneva cocktail, (iii) repaglinide with the Geneva cocktail (full cocktail), (iv) clopidogrel followed by the full cocktail, and (v) gemfibrozil followed by the full cocktail. The Geneva cocktail increased repaglinide AUC_0-23h 1.22-fold (90% confidence interval 1.04-1.44, P = 0.033). The full cocktail accurately captured known inhibitory effects of clopidogrel on CYP2B6, CYP2C8, and CYP2C19 and that of gemfibrozil on CYP2C8. Gemfibrozil decreased the paraxanthine/caffeine AUC_0-12h ratio by 23% (14-31%, P < 0.01) and increased caffeine AUC_0-12h 1.20-fold (1.03-1.40, P = 0.036). Gemfibrozil increased the metabolite-to-index drug AUC_0-23h ratios of flurbiprofen, omeprazole, dextromethorphan, and midazolam 1.59-fold (1.32-1.92), 1.47-fold (1.34-1.61), 1.79-fold (1.23-2.59), and 2.1-fold (1.9-2.4), respectively, without affecting the index drug AUCs (P < 0.01). Gemfibrozil increased the AUC_0-4h of glycochenodeoxycholate 3-O-glucuronide 1.33-fold (1.07-1.65, P = 0.027). In conclusion, the combination of repaglinide, the Geneva cocktail and endogenous biomarkers for OATP1B1 and OATP1B3 yields a nine-in-one phenotyping tool. Apart from strong CYP2C8 inhibition, gemfibrozil weakly inhibits CYP1A2 and OATP1B1 and appears to impair the elimination of the metabolites of several CYP index drugs.

Conducting high-quality health technology assessments requires high-quality evidence. With evolving regulatory standards for faster approval of new pharmaceutical products, health technology practitioners often find that the evidence base available to inform their work is lacking. This review article provides case examples of how health technology assessors have grappled with this tension, from the United States and European perspective, including experiences with new therapies for large populations, such as Alzheimer's disease, and gene therapies for ultra-rare conditions. The article concludes by offering some potential policy solutions that can meet the goals of robust evidence generation, patient access, and system affordability, including reimbursement with evidence development, outcomes-based contracts, and other types of managed entry agreements.

The decision-making process in drug development involves “go/no-go” decisions, particularly at the transition from early to late-stage trials. While the decisions are solely made by drug developers, they must take into account the perspectives of multiple stakeholders—such as regulatory agencies, HTA bodies, payers, patients, and ethics committees—to ensure well-informed and robust decision-making. These perspectives influence key considerations, including resource allocation, risk mitigation, regulatory compliance, etc. To support this process, quantitative methodologies, including Bayesian and hybrid frequentist-Bayesian approaches, have been introduced to improve decision-making. However, these methodologies often do not fully account for the diverse priorities and needs of all stakeholders. This scoping review examines criteria and methods used in decision-making at the phase II to III transition, with a focus on broadening the probability of success (PoS) concept beyond efficacy alone. Our review explores PoS for different success definitions, such as regulatory approval, market access, financial viability, and competitive performance. Key themes include decision criteria selection, trial design optimization, utility-based approaches, financial metrics, and multi-stakeholder considerations in decision-making. Our findings highlight both the limitations of current methodologies and potential paths forward, including the integration of real-world data (RWD) and advanced analytics. This work complements a companion manuscript by Cetinyurek-Yavuz et al. (2025) providing a detailed review of PoS methodologies focused solely on efficacy, specifically PoS for achieving statistical significance in phase III studies, including definitions, terminologies, and analytical approaches. Together, these studies provide a foundation for advancing late-stage trial decisions toward a more balanced, data-driven, and stakeholder-aligned approach.