We use MID3 as a holistic term to characterize a variety of quantitative approaches used to improve the quality, efficiency, and cost-effectiveness of decision-making through ‘‘fit-for-purpose’’ data analysis and prediction.
MID3: a quantitative framework for prediction and extrapolation centered on knowledge and inference generated from integrated models of compound, mechanism, and disease level data aimed at improving the quality, efficiency, and cost-effectiveness of decision-making.
The colored boxes represent essential components of the ‘‘Learn and Confirm Cycle’’.
The arrows represent processes that link these components.
The discipline of pharmacometrics has grown for more than two decades as a quantitative framework where knowledge is integrated to support decision-making in drug discovery and development.
Implementation of pharmacometric modeling and simulation tools in this field have emerged and established as a key component to optimize the drug development process, gaining increased support from the pharmaceutical industry, academia, and regulatory agencies.