A FORECASTING APPROACH TO ACCELERATE DRUG DEVELOPMENT

The clinical phase of drug development should be concluded sooner and at a lower cost if primarily only the pivotal and supportive studies w ere to be conducted. Such improved efficiency requires development of a decision support system that delivers five new capabilities: (i) it enables one to predict a result of a clinical study and to identify th ose studies that are expected to have an acceptable probability of suc cess; (ii) it will allow one to optimally utilize available pharmacoki netic and pharmacodynamic (PK/PD) data and improve its predictive capa bility as more data become available; (iii) it will enable one to proj ect useful population results, not just mean results; (iv) predictions will be accompanied by a measure of reliability; and (v) expected ini tial clinical results will be predictable from animal and related drug class data. With such a tool population targets could be specified ve ry early in the drug development programme, challenged, and then ratio nally revised at each step during the development process. This report describes progress in developing and testing a clinical trials Foreca ster, a prototype for such a system. The Forecaster generates estimate s of the joint density for a population of combined PK/PD parameters. That population then serves as a surrogate for the population of indiv iduals. When the resulting joint density is sampled, the obtained sets of parameters may be used to generate data that is statistically indi stinguishable from the original experimental data. Such simulated data can be used to validate assumptions, and make inferences on specified population targets that are accompanied by a measure of prediction re liability. We demonstrate use of the forecaster by employing N = 22 PK /PD parameter sets for an orally administered analgesic. (C) 1998 John Wiley & Sons, Ltd.