Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response.

ABSTRACT: Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, a

SUBMITTER: Spiller ER 

PROVIDER: S-EPMC8724556 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature