Model Selection for the Preclinical Development of New Drug-Radiotherapy Combinations

Area of Science:

• Oncology
• Radiation Oncology
• Pharmacology

Background:

• Radiotherapy is a cornerstone in cancer treatment for over 50% of patients.
• Advances in radiation delivery and planning software enable precise tumor targeting with reduced normal tissue toxicity.
• Combining radiotherapy with targeted drug therapies aims to improve cure rates by widening the therapeutic window.

Purpose of the Study:

• To review and discuss the strengths and weaknesses of preclinical models used in drug discovery.
• To provide guidance on optimally utilizing these models for identifying novel drug-radiotherapy combinations.
• To facilitate the development of clinically beneficial combination therapies for cancer treatment.

Main Methods:

• Literature review and critical analysis of existing preclinical models for drug-radiotherapy combination studies.
• Evaluation of model suitability based on factors like tumor microenvironment representation, genetic relevance, and scalability.
• Discussion of adaptation strategies for preclinical models to better suit combination therapy research.

Main Results:

• Identification of key strengths and limitations of various preclinical models (e.g., cell lines, xenografts, genetically engineered mouse models).
• Assessment of how different models can be leveraged to predict clinical efficacy and toxicity of combined treatments.
• Highlighting the need for model selection tailored to specific drug-radiotherapy combinations.

Conclusions:

• Preclinical models are essential for advancing drug-radiotherapy combination therapies.
• Judicious adaptation and selection of preclinical models are necessary for successful identification of beneficial combinations.
• Optimized preclinical research will accelerate the development of improved cancer treatment strategies.