Increasing the consistency, quality and transparency of conduct and documentation of Model-Informed Drug Discovery and Development (MID3) activities will be an important step in achieving a greater harmonization of these approaches across the pharmaceutical industry and in its interactions with regulatory agencies. MID3 is a general term describing a "quantitative framework for prediction and extrapolation, centered on knowledge and inference generated from integrated models of compound, mechanism and disease level data and aimed at improving the quality, efficiency and cost effectiveness of decision making". The MID3 Workgroup from European Federation of Pharmaceutical Industries and Associations (EFPIA) recently published a white paper [1] focusing on three major objectives: i) inform company decision makers how the strategic integration of MID3 can benefit R&D efficiency; ii) provide MID3 analysts with sufficient material to enhance the planning, rigor, and consistency of the application of MID3; and iii) provide regulatory authorities with substrate to develop MID3 related and/or MID3 enabled guidelines. In this document, a collection of "good practice" recommendations were assembled in order to minimize the heterogeneity in both the quality and content of MID3 implementation and documentation. An important recommendation was to explicitly state the underlying statistical and mathematical, physiological, pharmacological and disease-related assumptions and their evaluation, both in the planning and reporting of analyses. Moreover, an EFPIA categorization of MID3 internal decision-making was proposed to clarify the use of modeling and simulation for decision making, which is in close alignment with the EMA proposal [2]. These classifications are envisioned to offer a more transparent way of communicating how modeling and simulation work enables informed decision making as well as to guide the level of documentation. Finally, a collection of 100+ case studies was presented aiming to illustrate the MID3 framework with regards the key R&D questions, the integration of various modeling approaches, the application types spanning from Target Selection to Therapeutic Use, and the potential for internal industry and regulatory impact on decision making.

[1]CPT PSP 2016 5(3):93-122. http://dx.doi.org/10.1002/psp4.12049 [2]CPT PSP 2013 2:e31. http://dx.doi.org/10.1038/psp.2013.7