Restricted mean survival time for the analysis of cardiovascular outcome trials assessing non-inferiority: Case studies from antihyperglycemic drug development.

Cardiovascular outcome trials (CVOTs) have been employed in multiple therapeutic areas to explore whether a noncardiovascular drug increases the risk for cardiovascular events. These studies are now a central part of drug development programs for antihyperglycemic drugs. These programs are expected to demonstrate that new antihyperglycemic drugs for patients with Type 2 diabetes do not have unacceptable cardiovascular risk. The hazard ratio, which is usually provided as evidence that patients receiving the investigational treatment are not at statistically significantly greater cardiovascular risk than patients on the control treatment, can be difficult to interpret for various reasons. Therefore, an alternative approach known as the Restricted Mean Survival Time (RMST) or τ-year mean survival time is presented, and its ability to overcome interpretation challenges with the hazard ratio discussed. The RMST approach is applied to five completed CVOTs and is compared with the corresponding hazard ratios. Additionally, detailed considerations are given on how to design a non-inferiority CVOT using the RMST approach. The RMST methodology is shown to be a practical alternative to the hazard ratio methodology for designing a non-inferiority CVOT.

Extrapolation of adult data and other data in pediatric drug-development programs.

OBJECTIVES: In 1994, the US Food and Drug Administration (FDA) proposed an approach, based on extrapolation of efficacy findings from adults to the pediatric population, to maximize the use of adult data and other data when designing pediatric drug-development programs. We examined the experience of the FDA in using extrapolation to evaluate how and when it was used and any changes in scientific assumptions over time. METHODS: We reviewed 370 pediatric studies submitted to the FDA between 1998 and 2008 in response to 159 written requests (166 products) issued under the Pediatric Exclusivity Provision. We identified cases in which efficacy was extrapolated from adult data or other data, we categorized the type of pediatric data required to support extrapolation, and we determined whether the data resulted in new pediatric labeling. RESULTS: Extrapolation of efficacy from adult data occurred for 82.5% of the drug products (137 of 166). Extrapolation was defined as complete for 14.5% of the products (24 of 166) and partial for 68% of them (113 of 166). Approaches to extrapolation changed over time for 19% of the therapeutic indications studied (13 of 67). When extrapolation was used, 61% of the drug products (84 of 137) obtained a new pediatric indication or extension into a new age group; this number decreased to 34% (10 of 29) when there was no extrapolation. CONCLUSIONS: Extrapolating efficacy from adult data or other data to the pediatric population can streamline pediatric drug development and help to increase the number of approvals for pediatric use.

Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications.

The value of quantitative thinking in drug development and regulatory review is increasingly being appreciated. Modeling and simulation of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression is often referred to as the pharmacometrics analyses. The objective of the current report is to assess the role of pharmacometrics at the US Food and Drug Administration (FDA) in making drug approval and labeling decisions. The New Drug Applications (NDAs) submitted between 2000 and 2004 to the Cardio-renal, Oncology, and Neuropharmacology drug products divisions were surveyed. For those NDA reviews that included a pharmacometrics consultation, the clinical pharmacology scientists ranked the impact on the regulatory decision(s). Of about a total of 244 NDAs, 42 included a pharmacometrics component. Review of NDAs involved independent, quantitative evaluation by FDA pharmacometricians, even when such analysis was not conducted by the sponsor. Pharmacometric analyses were pivotal in regulatory decision making in more than half of the 42 NDAs. Of the 14 reviews that were pivotal to approval related decisions, 5 identified the need for additional trials, whereas 6 reduced the burden of conducting additional trials. Collaboration among the FDA clinical pharmacology, medical, and statistical reviewers and effective communication with the sponsors was critical for the impact to occur. The survey and the case studies emphasize the need for early interaction between the FDA and sponsors to plan the development more efficiently by appreciating the regulatory expectations better.

A pharmacodynamic model of the effects of controlled-onset extended-release verapamil on 24-hour ambulatory blood pressure.

OBJECTIVE: To formulate and evaluate a pharmacodynamic model that characterizes the effects of S-verapamil on the circadian 24-hour ambulatory blood pressure (ABP). METHODS: ABP was recorded in 19 hypertensive patients off drug, and following administration of the targeted dose of COER-V given once daily for at least 30 days. Blood samples were collected after the last dose for determination of the pharmacokinetic of S-verapamil. ABP vs. time was analyzed using a cosinor function, and the effects of S-verapamil on ABP were fitted using the pharmacodynamic model. RESULTS: COER-V decreased average systolic and diastolic blood pressures (mesors): baseline, 142 +/- 10 and 90 +/- 7; treated, 132 +/- 8.8 and 83 +/- 6.6 mmHg, respectively (p < 0.001). COER-V had no effect on the amplitude, cycle or the time shift (acrophase). The mean +/- SD time to peak and maximal S-verapamil concentrations were 9.5 +/- 1.2 hours and 46.4 +/- 35.8 ng/ml, respectively. Model estimates of the maximal inhibited systolic (Emax S), diastolic. (Emax D) pressures and C50 were 101 +/- 14 mmHg, 61 +/- 9.9 mmHg and 32.9 +/- 22.8 ng/ml, respectively. The model fit of the data was satisfactory and parameter estimates were precise. CONCLUSIONS: The model may be useful to characterize the relationship between plasma concentrations of verapamil and the antihypertensive effects of the drug and may be suitable for characterizing the effect of drugs on biological functions displaying oscillatory behavior.