Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.
Few scientific contributions have made significant impact unless there was a champion who had the vision to see the potential for its use in seemingly disparate areas-and who then drove active implementation. In this paper, we present a historical summary of the development of non-linear mixed effects (NLME) modeling up to the more recent extensions of this statistical methodology. The paper places strong emphasis on the pivotal role played by Lewis B. Sheiner (1940-2004), who used this statistical methodology to elucidate solutions to real problems identified in clinical practice and in medical research and on how he drove implementation of the proposed solutions. A succinct overview of the evolution of the NLME modeling methodology is presented as well as ideas on how its expansion helped to provide guidance for a more scientific view of (model-based) drug development that reduces empiricism in favor of critical quantitative thinking and decision making.
Pillai
Goonaseelan Colin
GC
Modeling and Simulation, Novartis Pharma AG, Basel, Switzerland.
Mentré
France
F
Steimer
Jean-Louis
JL
D000465:Algorithms; D000925:Anticoagulants / Q000493:pharmacokinetics; D002316:Cardiotonic Agents / Q000493:pharmacokinetics; D004077:Digoxin / Q000493:pharmacokinetics; D004345:Drug Industry; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D010599:Pharmacokinetics; D010600:Pharmacology / Q000706:statistics & numerical data* / Q000639:trends*; D012984:Software; D014859:Warfarin / Q000493:pharmacokinetics
D000925:Anticoagulants; D002316:Cardiotonic Agents; D014859:Warfarin; D004077:Digoxin