The future of phenotypic drug discovery

Area of Science:

• Pharmacology and Drug Discovery
• Biotechnology
• Translational Medicine

Background:

• Phenotypic drug discovery (PDD) screens compounds using biological systems, identifying drugs with novel mechanisms.
• Widespread adoption of PDD is hindered by challenges in lead qualification, hit prioritization, and early identification of undesirable drug mechanisms.
• Existing PDD pipelines often face overloaded stages due to a lack of effective tools for data processing and decision-making.

Purpose of the Study:

• To discuss the application of human-based phenotypic platforms throughout the drug discovery process.
• To highlight how these platforms can improve hit triage, prioritization, and the elimination of unsuitable leads.
• To explore the potential of phenotypic platforms in supporting clinical strategies and understanding drug efficacy and toxicity.

Main Methods:

• Utilizing human-based phenotypic platforms for direct biological screening.
• Implementing data-driven approaches for hit triage and prioritization within discovery pipelines.
• Employing pathway-based decision frameworks to guide clinical strategies and assess lead viability.

Main Results:

• Human-based phenotypic platforms are being integrated to refine hit selection and accelerate lead progression.
• These platforms facilitate the early identification and removal of drug candidates with unfavorable mechanisms, reducing late-stage failures.
• Data generated from phenotypic platforms enhance the understanding of drug efficacy and toxicity, informing better decision-making.

Conclusions:

• Human-based phenotypic platforms offer powerful tools for optimizing drug discovery workflows.
• By improving hit quality and decision-making, these platforms promote faster generation of viable drug leads.
• Increased utilization of advanced phenotypic platforms is crucial for driving broader adoption and success in PDD.