Search

It has become increasingly common for patients to rely on the use of multiple prescription medications. The management of polypharmacy requires careful consideration for how drugs are metabolized and their potential for interaction with other drugs. Drug-drug interaction (DDI) assessments are typically performed in a stepwise manner during drug development, though knowledge gaps can exist at the time of approval. The US Food and Drug Administration can establish postmarketing requirements (PMRs) or postmarketing commitments (PMCs) to address these knowledge gaps. In this study, we systematically evaluated PMRs and PMCs established to new molecular entities (NMEs) at the time of initial approval between 2009 and 2023, for the assessment of pharmacokinetics-based DDIs (i.e., drug metabolizing enzyme- and transporter-related DDIs). We found that 22% of NMEs had at least one DDI-related PMR or PMC, with a total of 263 that were pharmacokinetic based. Of these, 67% were for the assessment of drug metabolizing enzymes, which were established most frequently for their evaluation as a substrate, and 28% for transporters, which were established most frequently for their evaluation as an inhibitor. The 89% of PMRs and PMCs that were considered fulfilled had a revision to the United States prescribing information, the majority of which resulted in updated new instructions for use. This study highlights the value in conducting PMRs and PMCs early in the drug development process allowing broad patient inclusion at the time of initial drug approval., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA.)

Introduced by the Hatch-Waxman Amendments of 1984, 505(b)(2) applications permit the US Food and Drug Administration to rely, for approval of a new drug application, on information from studies not conducted by or for the applicant and for which the applicant has not obtained a right of reference. This pathway is designed to circumvent the unnecessary duplication of studies already conducted on a previously approved drug. It can lead to a considerably more efficient and expedited route to approval compared to a traditional development path. Model-informed drug development refers to the utilization of a diverse array of quantitative models in drug development to streamline the decision-making process. In this approach, diverse quantitative models that integrate knowledge of physiology, disease processes, and drug pharmacology are employed to address drug development challenges and guide regulatory decisions. Integration of these model-informed approaches into 505(b)(2) regulatory submissions and decision-making can further expedite the approval of new drugs. This article discusses some applications of model-informed approaches that were used to support 505(b)(2) drug development and regulatory actions. Specifically, various quantitative models such as population pharmacokinetic and exposure-response models have been employed to provide evidence of effectiveness, guide dosing in subgroups such as subjects with hepatic or renal impairment, and inform policies. These case study examples collectively underscore the significance of model-informed approaches in drug development and regulatory decisions associated with 505(b)(2) submissions., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA.)

Statins are widely prescribed and highly susceptible to pharmacokinetic (PK)-based drug-drug interactions (DDIs). To date, there has not been a comprehensive analysis of the basis upon which statin DDI recommendations in US Food and Drug Administration (FDA) prescribing information (PI) are derived. We have conducted such an analysis. We also assessed the degree of concordance of statin DDI recommendations in FDA PI and those provided in common tertiary clinical resources. We catalogued statin DDI information, including PK data and management recommendations, for statin precipitant drugs approved from 2010 to 2021, available from FDA PI and tertiary clinical resource databases. Recommendations were categorized and mapped with associated PK data to assess consistency in the PK basis for labeling recommendations. From the 80 precipitant drugs evaluated, 180 statin DDIs were identified in FDA PI. Dedicated clinical DDI studies were conducted for 54% (n = 97) of these DDIs and 34% (n = 61) of DDI recommendations were extrapolated from clinical data with other statins. Overall, we found that PK-based statin recommendations were consistent across PI. These findings highlight regulatory precedence for translating information across statins without conducting dedicated clinical DDI studies, which may support future efforts toward streamlining the approach to investigation and labeling of statin DDIs. In addition, with the exception of some notable discrepancies, general concordance was observed between FDA and tertiary resources regarding "Dose Adjustment" and "Avoid Coadministration" recommendations. However, further analyses are warranted across other DDI pairs to determine whether discordance can routinely lead to different clinical recommendations depending on the drug information resource., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA.)

The prevalence of obesity has grown tremendously in recent years and this population has an increased risk of disease comorbidities. The presence of disease comorbidities requires treatment interventions and proper dosing guidelines. However, drug development programs often do not have adequate representation of individuals who are obese in clinical trials, leaving gaps in the understanding of treatment response leading to a lack of adequate individualization options. Based on a recent survey of approved drug product package inserts, very few approved products included specific dosing based on obesity, in both adults and pediatrics. Reasons for the limited information on patients who are obese may include the under-reporting of information regarding such patients and a lack of clinical trial diversity in enrolling patient groups in whom obesity or obesity-related comorbidities are more prevalent. An inadvertent impact of the practice of exclusion of subsets of patients with some comorbidities in clinical trials may play a role in the reduced enrollment of individuals who are obese. Recently, regulatory authorities have taken specific initiatives to promote clinical trial diversity, including engaging with stakeholders and publishing regulatory guidance. These guidance documents highlight the need to enroll diverse clinical trial populations and provide recommendations on concepts related to drug development for obese populations. Such efforts will help to address the gap in information regarding drug response and dosing in patients who are obese., (Published 2023. This article is a U.S. Government work and is in the public domain in the USA.)

Characterization of infant drug exposure through human milk is important and underexplored. Because infant plasma concentrations are not frequently collected in clinical lactation studies, modeling and simulation approaches can integrate physiology, available milk concentrations, and pediatric data to inform exposure in breastfeeding infants. A physiologically based pharmacokinetic model was built for sotalol, a renally eliminated drug, to simulate infant drug exposure from human milk. Intravenous and oral adult models were built, optimized, and scaled to an oral pediatric model for a breastfeeding-relevant age group (<2 years). Model simulations captured the data that were put aside for verification. The resulting pediatric model was applied to predict the impacts of sex, infant body size, breastfeeding frequency, age, and maternal dose (240 and 433 mg) on drug exposure during breastfeeding. Simulations suggest a minimal effect of sex or frequency on total sotalol exposure. Infants in the 90th percentile in height and weight have predicted exposures ≈20% higher than infants of the same age in the 10th percentile due to increased milk intake. The simulated infant exposures increase throughout the first 2 weeks of life and are maintained at the highest concentrations in weeks 2-4, with a consistent decrease observed as infants age. Simulations suggest that breastfeeding infants will have plasma concentrations in the lower range observed in infants administered sotalol. With further validation on additional drugs, physiologically based pharmacokinetic modeling approaches could use lactation data to a greater extent and provide comprehensive information to support decisions regarding medication use during breastfeeding., (© 2023, The American College of Clinical Pharmacology.)

Many of the conditions for the safe and effective use of new molecular entities (NMEs) are understood at the time of initial drug approval. However, some remaining knowledge gaps can be addressed after drug approval through postmarketing requirements (PMRs) or commitments (PMCs) established by the US Food and Drug Administration (FDA). Our objective was to conduct an assessment of clinical pharmacology-related PMRs and PMCs established at the time of approval and evaluate the impact of fulfilled PMRs and PMCs on prescription information (PI). This analysis included clinical pharmacology-related PMRs and PMCs established for NMEs approved between 2009 and 2020. Of the 1171 PMRs and PMCs, over one-third were clinical pharmacology-related. Of these, 46% were to evaluate drug interactions, 16% were to evaluate drug dosing in patients with hepatic impairment, and 10% were related to dose. The majority (57%) of PMRs and PMCs were fulfilled at the time of analysis, with a median time to fulfillment of approximately 2.3 years. The majority (94%) of the fulfilled PMRs and PMCs, either with or without a PI revision, resulted in new or modified instructions for use or supported existing instructions for use. This is the first time that clinical pharmacology-related PMRs and PMCs have been catalogued and analyzed to understand their impact on PI. An understanding of the knowledge gaps that exist at the time of drug approval could inform the most effective and efficient methods for evidence generation prior to and after new drug approval., (Published 2023. This article is a U.S. Government work and is in the public domain in the USA.)

Carriers of two copies of the loss-of-function CYP2C19*2 variant convert less clopidogrel into its active metabolite, resulting in diminished antiplatelet responses and higher cardiovascular event rates. To evaluate whether increasing the daily clopidogrel dose in poor metabolizers (PM) overcomes the effect of the CYP2C19 * 2 variant, we enrolled 18 healthy participants in a genotype-stratified, multi-dose, three-period, fixed-sequence crossover study. Six participants with the *1/*1 extensive (EM), *1/*2 intermediate (IM), and *2/*2 poor metabolizer genotypes each received 75 mg, 150 mg, and 300 mg each for 8 days. In each period, maximal platelet aggregation 4 hours post-dose (MPA4) and active metabolite area under the curve (AUC) differed among genotype groups (P < .05 for all). At day 8, PMs needed 300 mg daily and IMs needed 150 mg daily to attain a similar MPA4 as EMs on the 75 mg dose (32.6%, 33.2%, 31.3%, respectively). Similarly, PMs needed 300 mg daily to achieve active metabolite concentrations that were similar to EMs on 75 mg (AUC 37.7 and 33.5 ng h/mL, respectively). These results suggest that quadrupling the usual clopidogrel dose might be necessary to overcome the effect of poor CYP2C19 metabolism., (© 2014, The American College of Clinical Pharmacology.)

The glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide was approved in 2010 by the US Food and Drug Administration (FDA) as an adjunct treatment to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus. This article provides insights into the use of pharmacometric analyses for regulatory review with a focus on the dosing recommendations. The assessment was based on the totality of exploratory and confirmatory analysis of dose-finding and pivotal clinical data and was structured around a set of key questions in accordance with current FDA review practice. For the pharmacometric review of liraglutide, the key questions focused on exposure-response relationships for effects on fasting plasma glucose, hemoglobin A(1c), and calcitonin and on variability in exposure across demographic subgroups of patients. The importance of conducting exploratory exposure-response analysis and population pharmacokinetic studies in clinical drug development to support dosing recommendations is highlighted.

The objective of this work was to derive a dosing regimen for dabigatran in patients with severe renal impairment by modeling and simulation. Data from a dedicated renal impairment study were used to model the pharmacokinetics of dabigatran in normal and renal-impaired subjects. Model parameters were used to simulate the average concentration time-course of dabigatran following various dosing regimens. Pharmacokinetics of dabigatran in normal and renal-impaired subjects were best described by a 2-compartment open model with first-order absorption and elimination. Simulations were performed to select an appropriate regimen that reasonably matched the exposures on an average with those observed in subjects with moderate renal impairment who did not require a dose adjustment because of a favorable benefit-risk. Dabigatran 150 mg given once daily resulted in 35% higher average C(max, ss), whereas a 75 mg once daily regimen resulted in 42% lower average Cτ, relative to that observed with 150 mg administered twice daily in subjects with moderate renal impairment. A twice daily regimen of dabigatran 75 mg resulted in a reasonable matching of exposures and was selected as an appropriate dosing regimen in patients with severe renal impairment. This recommendation was incorporated in the dosing and recommendation section of dabigatran product insert.

The objective was to characterize the pharmacokinetics (PK) and pharmacodynamics (PD) of argatroban in pediatric patients and derive dosing recommendations. An open-label multicenter trial was conducted in pediatric patients (n = 18 from birth to 16 years). A population modeling approach was used to characterize pharmacokinetics and pharmacodynamics of argatroban in pediatric patients. Simulations were performed to derive a dosing regimen for pediatric patients. The estimated clearance of argatroban in pediatric patients was 2-fold lower than that in healthy adults. Body weight was significant predictor of argatroban clearance. The clearance in a typical 20-kg pediatric patient was 3.1 L/h. In 4 patients with elevated serum bilirubin levels, the estimated clearance was 0.6 L/h. Effect on activated plasma thromboplastin time (aPTT) was found to be concentration dependent. Simulations suggested that a starting dose of 0.75 µg/kg/min in pediatric patients was comparable in performance to 2.0 µg/kg/min approved in adults for attaining target aPTT and risk for bleeding. A dose increment step size of 0.25 µg/kg/min was suitable for titration. The PK/PD of argatroban was reasonably characterized in pediatrics. Plasma concentration-aPTT relationship was used to derive a safe starting dose and titration scheme for the first time in pediatric patients and was incorporated into the US prescribing information for argatroban.

The End-of-Phase 2A meetings are proposed to identify opportunities to make innovative medical products available sooner and to increase the quality of drug applications through early meetings between sponsors and the FDA. This article summarizes the overall experience across 11 pilot End-of-Phase 2A meetings since 2004. Four case studies are presented in more detail to demonstrate the various issues and methods encountered at these meetings. Overall, industry and FDA scientists ranked these meetings to be "very helpful" (average score of 4 on a scale of 1 to 5). In almost all the instances the sponsors changed their drug development plans subsequent to these extensive quantitative analyses-based meetings. A draft Guidance is being developed to be issued in 2008, and we hope this initiative will be resourced by then.

The criterion for assessing whether a drug prolongs QT as described in the International Conference on Harmonization topic E14 guideline does not explicitly account for individual drug concentrations. The authors' experience with reviewing QT studies indicates that understanding the relationship, if any, between individual drug concentration and QT change provides important additional information to support regulatory decision making. Therefore, regulatory reviews of "thorough QT" studies routinely include a characterization of the concentration-QT relationship. The authors provide examples to illustrate how the concentration-QT relationship has been used to plan and interpret the thorough QT study, to evaluate QT risk for drugs that have no thorough QT studies, to assess QT risk in subpopulations, to make dose adjustments, and to write informative drug labels.