Hao Zhu, Ruihao Huang, Menglun Wang, Lixia Zhang, Hanrui Zhang, Yutao Gong, Rajnikanth Madabushi, Qi Liu
The convergence of MIDD and AI represents a natural evolution from established quantitative frameworks toward a broader, more powerful computational toolbox that can address persistent MIDD challenges such as high-dimensional data integration, complex biology, and operational constraints in evidence generation. AI can both enhance traditional MIDD through hybrid approaches and extend MIDD's horizon to include various AI models. Recent publications of guidance demonstrate the agency's preparation on the acceptance of AI in MIDD.