Clarification on Precision Criteria to Derive Sample Size When Designing Pediatric Pharmacokinetic Studies

Abstract

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

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models

“…RSE of CL TV predictions over weight were also calculated using the variance-covariance matrix obtained from NONMEM [13]. For this, we log-transformed the power function of Eq.…”

“…In this context, the power function in Eq. 1 can be considered a linear model in the log domain, with an intercept of log CL pop [13]. If the same concepts apply, we might expect the RSE of the estimate of CL pop to be minimal when normalizing weight to the geometric mean.…”

Use of Modeling and Simulation in the Design and Conduct of Pediatric Clinical Trials and the Optimization of Individualized Dosing Regimens

“…Several methods for defining an appropriate sample size for pediatric population PK studies have been proposed, each of which is associated with relative strengths and weaknesses 4, 5, 6, 7. The most well‐known approach was put forth by the FDA in 2012 3. This approach aims to precisely estimate PK parameters (e.g., clearance and volume of distribution).…”

“…This approach aims to precisely estimate PK parameters (e.g., clearance and volume of distribution). The regulatory requirement that evolved from this approach states that a pediatric trial “must be prospectively powered to target a 95% confidence interval within 60‐140% of the geometric mean estimates of clearance and volume of distribution […] in each pediatric sub‐group with ≥80% power.”3 Pediatric subgroups are most commonly derived from stratifications based on age; however, other physiologic (e.g., weight) or pathophysiologic (e.g., rate of disease progression) factors that influence the exposure–response profile should also be considered to ensure that the sample size is appropriate given the trial's objectives. In three examples put forth by the FDA, including two antibiotics and one sympatholytic drug, the following age groups have been used: 3 to <6 months, 6 to <12 months, 1 to <2 years, 2 to <6 years, 6 to <12 years, and 12 to 18 years 3…”

A Report from the Pediatric Formulations Task Force: Perspectives on the State of Child-Friendly Oral Dosage Forms

“…Likewise, there is an evolving set of physiologic-based absorption models (e.g., ADAM, GITA, Grass) which are able to accommodate pediatric-specific anatomical parameters potentially improving guidance for pediatric formulations even further. Integrating in vitro drug characteristics, study design, sampling scheme, dosing requirements, and sample size into a complete trial simulation model would seem to be an optimal way of assuring adherence with both study objectives (49) and recent FDA quality standards on pediatric trial design (50).…”