In vitro clinical trials: the future of cell-based profiling

Area of Science:

• Pharmacology and Drug Discovery
• Genetics and Personalized Medicine

Background:

• Traditional drug discovery relies on biochemical assays and limited genetic testing.
• Key drug properties like bioavailability, toxicity, and solubility are critical but often assessed late.
• Most clinical trial drugs are tested in a narrow range of human genetic backgrounds.

Purpose of the Study:

• To review and advocate for large-scale in vitro and in vivo models that incorporate human genetic diversity.
• To explore the necessity of high-throughput automation and pooling strategies for modeling genetic variations.
• To emphasize the importance of extensive model characterization for unbiased computational analysis.

Main Methods:

• Review of current efforts in large-scale cellular and animal models for disease simulation.
• Discussion of high-throughput automation and pooling/deconvolution strategies for assaying genetic diversity.
• Emphasis on comprehensive characterization of models for informatics-based analysis.

Main Results:

• Current drug discovery models inadequately represent human genetic diversity.
• Advanced automation and modeling approaches are required to address this gap.
• Extensive model characterization is essential for unbiased, data-driven insights.

Conclusions:

• Large-scale, genetically diverse models are vital for understanding drug response.
• These approaches promise improved patient stratification in clinical settings.
• Oncology is leading the way, with potential expansion into immunology and neuroscience.