Evaluation of agile designs in first-in-human (FIH) trials--a simulation study.
The aim of the investigation was to evaluate alternatives to standard first-in-human (FIH) designs in order to optimize the information gained from such studies by employing novel agile trial designs. Agile designs combine adaptive and flexible elements to enable optimized use of prior information either before and/or during conduct of the study to seamlessly update the study design. A comparison of the traditional 6 + 2 (active + placebo) subjects per cohort design with alternative, reduced sample size, agile designs was performed by using discrete event simulation. Agile designs were evaluated for specific adverse event models and rates as well as dose-proportional, saturated, and steep-accumulation pharmacokinetic profiles. Alternative, reduced sample size (hereafter referred to as agile) designs are proposed for cases where prior knowledge about pharmacokinetics and/or adverse event relationships are available or appropriately assumed. Additionally, preferred alternatives are proposed for a general case when prior knowledge is limited or unavailable. Within the tested conditions and stated assumptions, some agile designs were found to be as efficient as traditional designs. Thus, simulations demonstrated that the agile design is a robust and feasible approach to FIH clinical trials, with no meaningful loss of relevant information, as it relates to PK and AE assumptions. In some circumstances, applying agile designs may decrease the duration and resources required for Phase I studies, increasing the efficiency of early clinical development. We highlight the value and importance of useful prior information when specifying key assumptions related to safety, tolerability, and PK.
Perlstein
Itay
I
Department of Clinical Pharmacology, Merck Research Laboratories, Merck & Co., Inc., 126 East Lincoln Avenue, Rahway, New Jersey 07065, USA.
Bolognese
James A
JA
Krishna
Rajesh
R
Wagner
John A
JA
D000704:Analysis of Variance; D019540:Area Under Curve; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D004364:Pharmaceutical Preparations / Q000008:administration & dosage; D010599:Pharmacokinetics; D012107:Research Design; D012449:Safety; D012984:Software
D004364:Pharmaceutical Preparations