Model-integrated evidence: A vision to expand the role of modeling in drug development and regulatory decision-making

PBPK & PBBM

MIDD

QSP

Regulatory interactions

Pharmacometrics

Program strategies and efficiencies

Quant Med. 2026;1(1). Online ahead of print.

Zhao L, Mondick J, Barrett J, Bhattacharya S, Chenel M, Corrigan B, Dutta S, Gao W, Gao X, Girish S, Hooker AC, Jones H, Langevin B, Peck C, Rostami-Hodjegan A, Sun YN, Lovern M.

The pharma industry is facing a productivity crisis: despite advances in computing, biology, and regulation, Eroom's Law still holds (the observation that drug discovery and development have gotten slower and more expensive over time, even though technology and science have improved significantly); the cost of developing a new medicine roughly doubles every 9 years.

This publication is a collaboration between pharma, consultancies and academia, outlines a pivotal shift from Model-Informed Drug Development (MIDD) to Model-Integrated Evidence (MIE). In this emerging paradigm, rigorously validated computational models generate "digital evidence" that carries evidentiary weight comparable to empirical clinical data for regulatory purposes, including approvals, labeling, and lifecycle management. The vision is for MIE to be recognized as primary evidence of safety and effectiveness, accelerating R&D and improving treatment options for patients.

In this paper you’ll find:

A review of the evolving MIE landscape in light of recent regulatory initiatives
An overview of quantitative methodologies enabling MIE
Presentation of high-impact case studies illustrating practical applications
Recommendations for advancing the adoption and impact of MIE.