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Impact of Study Design on the Evaluation of Inhaled and Intranasal Corticosteroids’ Effect on Hypothalamic–Pituitary–Adrenal Axis Function, Part I: General Overview of HPA Axis Study Design
Inhaled and intranasal corticosteroids (ICS and INS) are among the mainstays of the treatment for asthma and allergic rhinitis, respectively, and also carry the potential to suppress the hypothalamic–pituitary–adrenal (HPA) axis. Several important factors affect the interpretability of trials investigating the impact of ICS and INS on the HPA axis. This paper reviews 106 published clinical trials, peer-reviewed articles, and New Drug Application reviews of approved ICS and INS, using MEDLINE and Drugs@FDA database. The trials included in this review evaluated the potential impact on HPA axis function of eight approved single-ingredient ICS and INS (beclomethasone dipropionate, budesonide, ciclesonide, flunisolide, fluticasone furoate, flucticasone propionate, mometasone furoate, and triamcinolone acetonide) and combination products containing these ingredients. The most commonly utilized design was blinded, placebo controlled, and short term (<6 weeks) for adult trials and blinded, placebo controlled, and long term (≥6 weeks) for pediatric trials. Factors potentially affecting trial results include the choice of dose, dosing duration, assay sensitivity, statistical methodology, and the study population evaluated (patients or healthy volunteers). All of these factors have the potential to affect the level of adrenal suppression detected. In conclusion, to be informative, a HPA axis study should be well designed and carefully implemented to minimize variability in results and improve the overall interpretability of data obtained.Keywords: regulatory science, pulmonary, study design, hypothalamic–pituitary–adrenal axis, intranasal corticosteroids, pharmacodynamics, inhaled corticosteroid
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