Model-based drug development: the road to quantitative pharmacology.

Area of Science:

• Pharmacology
• Biostatistics
• Drug Development

Background:

• High drug development costs and low success rates necessitate improved methodologies.
• The U.S. Food and Drug Administration (FDA) recognizes model-based drug development (MBDD) as a valuable prognostic tool.
• Quantitative pharmacology offers a systematic approach to characterizing new molecular entities.

Purpose of the Study:

• To review the concept, elements, and role of MBDD within quantitative pharmacology.
• To illustrate MBDD's utility in knowledge management and decision-making through case studies.
• To discuss the future prospects and collaborative needs of quantitative pharmacology.

Main Methods:

• Review of MBDD principles and its integration with quantitative pharmacology.
• Presentation of two case studies demonstrating MBDD application.
• Discussion of organizational learning derived from implementing quantitative pharmacology.

Main Results:

• MBDD facilitates efficient drug development by utilizing disease, exposure-response, and pharmacometric models.
• Case studies demonstrate MBDD's effectiveness in knowledge management and decision support.
• Implementation of quantitative pharmacology fosters organizational learning.

Conclusions:

• MBDD is an integral component of quantitative pharmacology, enhancing drug development efficiency and decision-making.
• Quantitative pharmacology requires interdisciplinary collaboration among academia, industry, and regulatory agencies for advancement.
• Continued development in quantitative pharmacology promises more predictable and optimized drug development pathways.