Consideration for Assessing Data/Models/Tools Expiration Supporting Drug Development and Clinical Decision Making.

Abstract

Decision making of any kind is informed by data and often by models, tools or other solutions built from data. Data are evaluated for such purposes within a specific context of use (COU) but implicitly we often believe the data to be relevant, accurate and of high quality. In reality, this is not always the case. The status of data for various COUs must constantly be revisited for relevance and information value over time. Using drug development as an example, we postulate that there are indeed occasions where data value diminishes over time and consideration for data expiration with respect to its relevance for decision making should be entertained and at least identified with respect to a time-dependent change in status. Other situations exist which will also necessitate periodic review and condition reassessment. For example, considerations for patient privacy and consent along with compliance to regulatory standards must factor into future recommendations as well. Actions regarding data expiration are proposed as initial thoughts to be expanded upon but this assessment is primarily an attempt to explore factors which impact opinions about data information value for both drug development and clinical decision making.