Translational value of mouse models in oncology drug development

Area of Science:

• Oncology
• Translational Research
• Drug Discovery

Background:

• Preclinical oncology models are crucial for drug development but often lack predictive power for clinical outcomes.
• Claims of superiority among different model systems are common, yet no single model adequately informs target validation or molecule selection.
• Existing models have limitations that hinder the translation of preclinical efficacy to clinical activity.

Purpose of the Study:

• To critically evaluate claims of superiority for various oncology model systems.
• To propose a framework for the appropriate utilization of preclinical models in drug testing and discovery.
• To identify and discuss gaps and model-independent shortcomings in preclinical oncology research.

Main Methods:

• Perspective-based analysis of existing literature and common practices in oncology model systems.
• Critical review of assertions regarding the predictive power of preclinical models.
• Identification of limitations in current oncology mouse models and general preclinical research.

Main Results:

• No single preclinical oncology model system is adequate for comprehensive drug discovery and target validation.
• Existing models possess inherent limitations that impede the translation of preclinical findings to clinical efficacy.
• Significant gaps and model-independent shortcomings exist in current preclinical oncology research.

Conclusions:

• A balanced and critical approach to preclinical model selection and utilization is necessary.
• A framework for the proper use of existing models can improve preclinical drug testing and discovery.
• Addressing model-independent shortcomings and gaps is essential for advancing oncology drug development.