The challenge of selecting the 'right' in vivo oncology pharmacology model

Area of Science:

• Oncology
• Pharmacology
• Translational Research

Background:

• Non-clinical cancer pharmacology models have historically shown poor predictive value for clinical outcomes.
• Numerous drugs demonstrating anti-tumor responses in preclinical animal models have subsequently failed in clinical trials.

Purpose of the Study:

• To address the challenge of improving the translation of preclinical cancer models to clinical settings.
• To emphasize the importance of selecting appropriate models for hypothesis-driven research in targeted drug discovery.

Main Methods:

• Discussion of various model systems employed in preclinical cancer drug discovery.
• Focus on criteria for selecting models that align with specific scientific questions.

Main Results:

• Analysis of current preclinical cancer model systems.
• Identification of strategies for enhancing the predictive accuracy of these models.

Conclusions:

• The selection of cancer models tailored to specific, hypothesis-driven scientific questions is critical.
• Improving model selection can enhance the translation of preclinical findings to clinical success in targeted cancer therapy.