Current mathematical models for cancer drug discovery

Area of Science:

• Pharmacometrics
• Oncology Drug Discovery
• Translational Research

Background:

• Pharmacometric models offer comprehensive data integration for early-phase oncology drug discovery.
• Empirical methods suffice for screening, but modeling is crucial for optimizing research and clinical development.

Purpose of the Study:

• To review and comment on modeling approaches used in anticancer drug discovery over the last decade.
• To highlight the increasing importance and application of these models.

Main Methods:

• Literature review focusing on papers from the last decade.
• Selection based on methodological interest or application in anticancer drug discovery.

Main Results:

• A growing number of modeling approaches are applied in anticancer drug discovery.
• New models are developed aligning with current research trends in oncology.

Conclusions:

• Pharmacometric models enhance understanding of oncological targets and utilize sparse preclinical data effectively.
• These models support translational research by guiding dosing regimens in early clinical development.