Phenotypic approaches for CNS drugs.

Area of Science:

• Neuroscience
• Pharmacology
• Biotechnology

Background:

• Central nervous system (CNS) drug development exhibits a high clinical failure rate.
• Phenotypic assays are crucial for translating drug discoveries into clinical treatments for complex brain diseases.
• Patient-derived brain cells offer the most accurate recapitulation of CNS disease phenotypes.

Purpose of the Study:

• To critique platforms integrating patient-derived cells with higher-throughput models for CNS drug discovery.
• To explore strategies for improving compound library screening and drug target deconvolution.
• To review agnostic target deconvolution approaches for phenotypic screening hit optimization.

Main Methods:

• Integration of patient-derived brain cells with immortalized cell models for balanced validity and scalability.
• Screening of conventional chemogenomic compound libraries and novel fragment libraries.
• Review of emerging library curation strategies and agnostic target deconvolution methods like chemical proteomics and AI.

Main Results:

• Critique of current platforms highlights the need for improved hit rate and quality in drug screening.
• Novel fragment libraries and advanced curation strategies show promise for more tractable target deconvolution.
• Evolving agnostic target deconvolution approaches aid in elucidating drug mechanisms from phenotypic screening.

Conclusions:

• Platforms combining patient-derived cells with scalable models are advancing CNS drug discovery.
• Improved library screening and target deconvolution strategies are essential for rational hit-to-drug optimization.
• Agnostic target deconvolution, including AI, is key to identifying and optimizing novel CNS drug targets.