Machine learning-assisted exploration of multidrug-drug administration regimens for organoid arrays.

ABSTRACT: Combination therapies enhance the therapeutic effect of cancer treatment; however, identifying effective interdependent doses, durations, and sequences of multidrug administration regimens is a time- and labor-intensive task. Here, we integrated machine learning, automation, and large microfluidic arrays of cancer spheroids or patient-derived organoids formed in a tissue-mimetic hydrogel to achieve notable acceleration of the discovery of effective multidrug administration regimens. For the clinically approved drug combination, we found a sequential administration regimen leading to a substantial reduction in the total drug dose, in comparison with concurrent drug supply, both at comparable drug efficacy. For the drugs that are currently under clinical development, we found a synergistic e

SUBMITTER: Yakavets I 

PROVIDER: S-EPMC12309667 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature