title: A framework establishing clear decision criteria for the assessment of drug efficacy.
abstract: Much has been published on various aspects of data analysis and reporting from clinical trials within the biopharmaceutical environment. This ranges from regulatory guidelines on the format and content of registration dossiers to recommendations on data presentation and the statistical methodologies that are appropriate for the diverse types of data one observes in clinical trials. Little has been written about designing a clinical trial analysis and reporting package that focuses on the decisions that must be made throughout the drug development process. Pharmaceutical companies today are under enormous pressure to develop drugs quickly and (cost-) efficiently. Because of this, drugs often move into the later phases of drug development before evidence from prior phases is completely understood. This provides a challenge to clinical trialists to design and execute a clinical trial programme which can expedite drug development. The statistician, as a clinical trialist, must strive to determine the optimum analytical methodology that facilitates decision making for this clinical trial programme. This paper proposes a new framework for the assessment of efficacy in drug development called the 'one programme, one p-value' framework. This framework will accelerate drug development by providing clear criteria for the decisions which must be made along the way. The 'one programme, one p-value' framework is based on the notion that the clinical trial programme comprises exploratory and confirmatory phases. The use of the likelihood function in the exploratory phase facilitates the decision whether (or when) to move into the confirmatory phase. The confirmatory phase consists of one confirmatory trial with a single hypothesis test of the drug's efficacy; hence 'one p-value'. Sponsor interaction with regulatory agencies is necessary at each decision point. Finally, the paper considers how analysis and reporting of efficacy data can be accomplished from a clinical trial programme as described.
authors.affiliation: Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana 46285, USA.
authors.forename: W J
authors.initials: WJ
authors.lastname: Huster
authors.forename: G G
authors.initials: GG
authors.lastname: Enas
mesh_terms: D002986:Clinical Trials as Topic / Q000592:standards*; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D004341:Drug Evaluation / Q000592:standards*; D004992:Ethics, Medical; D005060:Europe; D017408:Guidelines as Topic; D006801:Humans; D007564:Japan; D016013:Likelihood Functions; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards*; D013997:Time Factors; D014481:United States