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Mitigate Japan's Drug Loss With Model-Informed Drug Development.

Yasuhiko Imai1, Emi Akatsu1, Suzanne K Minton2

  • 1Certara GK, Tokyo, Japan.

CPT: Pharmacometrics & Systems Pharmacology
|October 12, 2025
PubMed
Summary

Drug loss in Japan, where approved medicines aren't available locally, can be reduced. A strategic approach using Model-Informed Drug Development (MIDD) with AI/ML can improve patient access to vital treatments.

Keywords:
model based drug developmentpediatricregulatory

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Area of Science:

  • Pharmaceutical Sciences
  • Drug Development
  • Regulatory Science

Background:

  • 'Drug loss' in Japan describes approved drugs lacking local development or approval.
  • This phenomenon limits patient access to potentially beneficial therapies.

Purpose of the Study:

  • To explore strategies for minimizing 'drug loss' in Japan.
  • To highlight the role of Model-Informed Drug Development (MIDD) and AI/ML in addressing this issue.

Main Methods:

  • Reviewing current drug development and approval processes in Japan.
  • Analyzing the potential of MIDD strategies, augmented by artificial intelligence/machine learning (AI/ML).

Main Results:

  • A comprehensive MIDD strategy, enhanced with AI/ML, can significantly reduce instances of 'drug loss'.
  • This approach streamlines development and approval pathways.

Conclusions:

  • Implementing advanced MIDD with AI/ML is crucial for minimizing 'drug loss' in Japan.
  • Sustained collaboration between the pharmaceutical industry and regulatory bodies is essential for patient access and global advancement.