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.

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Pharmacometric analyses have become an increasingly important component of New Drug Application (NDA) and Biological License Application (BLA) submissions to the US FDA to support drug approval, labelling and trial design decisions. Pharmacometrics is defined as a science that quantifies drug, disease and trial information to aid drug development, therapeutic decisions and/or regulatory decisions. In this report, we present the results of a survey evaluating the impact of pharmacometric analyses on regulatory decisions for 198 submissions during the period from 2000 to 2008. Pharmacometric review of NDAs included independent, quantitative analyses by FDA pharmacometricians, even when such analysis was not conducted by the sponsor, as well as evaluation of the sponsor's report. During 2000-2008, the number of reviews with pharmacometric analyses increased dramatically and the number of reviews with an impact on approval and labelling also increased in a similar fashion. We also present the impact of pharmacometric analyses on selection of paediatric dosing regimens, approval of regimens that had not been directly studied in clinical trials and provision of evidence of effectiveness to support a single pivotal trial. Case studies are presented to better illustrate the role of pharmacometric analyses in regulatory decision making.

P ediatric drug development is challenging and fairly unique in several aspects. 1 Most of the development programs have just one chance to perform an informative set of trials. After that, industry does not have any financial incentive. Pharmacokinetic (PK) information is useful in (1) selecting dose range for future studies; (2) assessing drug exposure for efficacy and safety purposes, especially by matching exposures to adults, and ultimately (3) supporting dosing approval. Different guidances were published to explain the role of pediatric studies under various conditions and the growth and developmental changes in factors influencing absorption, distribution, metabolism, and elimination of drugs in the pediatric population. 2,3 Even though sample size justification is provided for pediatric efficacy studies, the sample size selection for pediatric PK and safety studies has been vastly different without clear justification. As a consequence, either the pediatric exclusivity determination or the approval decision was affected. Hence, there is a need for a uniform definition of study quality for PK studies.One of the important goals of the pediatric PK study is to ensure the precise estimate of important PK parameters, such as clearance and volume of distribution, to justify the choice of a safe and effective dose from a PK perspective. To achieve this goal, a standard regulatory requirement has been drafted and communicated to the sponsors, where applicable, as follows:The study must be prospectively powered to target a 95% CI [confidence interval] within 60% and 140% of the geometric mean estimates of clearance and volume of distribution for DRUG NAME in each pediatric sub-group with at least 80% power. This report describes methodological details and expectations to fulfill this requirement based on either a noncompartment analysis (NCA) or a population PK (popPK) modeling approach. In the case of NCA analysis, we assume PK parameters have been robustly evaluated with an appropriate blood sampling strategy at the individual patient level. In some cases, the requirement for sample size is primarily driven by safety objectives where a minimum number of participants are required for safety evaluation, and this number may be more than that for PK objectives. Nevertheless, the same language will be communicated to the sponsors even if the planned sample size for safety objectives is more than that for PK objectives. A review of 3 pediatric clinical trials is presented to illustrate the feasibility of complying with the proposed quality standard. Finally, the potential impact of the quality standard on pediatric drug development is discussed. MethodIn this section, detailed steps to achieve the target, 95% CI within 60% and 140% of the geometric