LAUSR

Overview The International Neonatal Consortium (INC) integrates global stakeholders to promote clinical drug development for neonates.1 The INC focuses on generalizable methods for using data to support claims that a drug is safe and efficacious when used to treat a specific indication (regulatory science). The framework provided by regulatory science is similar to evidence-based medicine, including a “gold standard” approach of drawing on more than 1 adequately powered randomized clinical trial (RCT) when possible. Regulatory science includes several steps that are not usually emphasized in evidence-based medicine, including preclinical studies of toxicology and effects, optimized drug formulations, a transparent justification of dosage levels and trial designs, and a series of studies (including phase 1 and 2 studies, known as therapeutic exploratory studies) that are used to design the pivotal RCTs (known as therapeutic confirmatory studies).2 These steps promote the success of large RCTs while decreasing risks within the large RCTs for patients, funders, and investigators. Regulatory science includes a framework for circumstances in which conducting large RCTs is not feasible.3 The information generated by applying regulatory science supports judgments about drugs and biologics, typically allows a product to be placed on the market, and supports the rational use of the marketed drug. An adapted regulatory science framework can also support the use of drugs if they need to be used off-label. Contemporary regulatory science emphasizes (1) a program based on the systematic synthesis of data from preclinical and clinical sources rather than a series of uncoordinated trials; (2) study designs that are based on data about natural history and patient flow rather than expert opinions; (3) an explicit understanding of the performance of biomarkers and surrogate outcomes; (4) the voices of patients and their families; and (5) using real-world data when appropriate, considering the need for shared definitions, interoperable data systems and trade-offs with data reliability, a control of errors, study size, and safety.4 To advance the pediatric community’s understanding of regulatory science, we highlight collecting highquality data and rationally using data. High-quality data involve reliable measurements with acceptable interand intraobserver variation and are not necessarily the measurements used in clinical practice or collected in existing databases. Additionally, assessing the quality of the data involves paying close attention to how the data are collected, including checks on data entry (monitoring). Rationally using information during clinical drug development involves several components: (1) using quantitative models for the effects of the drug based on prior knowledge about natural history of the condition; (2) analyzing pharmacokinetics that can come from other age groups or animals through extrapolation; (3) demonstrating safety including drawing on preclinical toxicology studies and phase 1 studies among a small number of patients; (4) predicting the expected effect size; (5) identifying gaps in the models that need more information; (6) gathering data that will improve the model and the predictions (eg, conduct a large RCT, or use alternatives such as adaptive designs); (7) using the data to test the model and the predictions (eg, did the effect size in the RCT match what was expected); (8) validating predictions in independent cohorts (eg, conduct more than 1 large RCT when possible); and (9) applying understanding to the clinical situation.3 Ideally, steps 2 to 8 are performed more than once. The Figure shows a qualitative scheme for classifying limitations in neonatal drug development by whether there are sufficient data or a sufficient understanding of Figure. Scheme for Regulatory Science