Systematic modeling of phenotypic drug response profiles in patient-derived organoids

Area of Science:

• Oncology
• Biotechnology
• Pharmacology

Background:

• Patient-derived tumor organoids are advanced 3D models for preclinical drug discovery.
• Traditional 2D cell lines have limitations in mimicking in vivo tumor complexity.
• Dynamic drug responses in organoids require sophisticated evaluation methods.

Purpose of the Study:

• To develop a systematic method for evaluating dynamic organoid drug responses.
• To introduce novel metrics for quantifying drug effects on organoid growth and viability.
• To classify drug-induced phenotypic changes in organoids.

Main Methods:

• Developed Systematic Classification of Organoids for Phenotypic Evaluation (SCOPE).
• Utilized multi-timepoint 3D imaging and AI-based image analysis for organoid viability.
• Integrated mathematical modeling for tracking organoid growth dynamics.
• Defined combined growth and viability (GV) score and cytostatic-cytotoxic transition range (CCTR).

Main Results:

• Captured temporal and dose-dependent dynamics of organoid phenotypic changes.
• Introduced GV score and CCTR metrics to differentiate drug effects.
• Classified drug responses into four distinct phenotypic groups: cytotoxic, cytostatic plus cytotoxic, late cytotoxic, and cytostatic.
• Demonstrated potential for identifying novel drug effects and therapeutic applications.

Conclusions:

• The SCOPE system provides a robust framework for evaluating organoid drug responses.
• Novel metrics enhance the understanding of drug mechanisms and patient-specific responses.
• This approach can accelerate the development of new therapies and overcome drug resistance challenges.
• Improved clinical applicability of organoid-based drug discovery findings.