Swapnil Potdar

TL;DR: DECREASE, an efficient machine learning model that requires only a limited set of pairwise dose–response measurements for the accurate prediction of synergistic and antagonistic drug combinations, is implemented.

TL;DR: The Breeze application provides a complete solution for data quality assessment, dose–response curve fitting and quantification of the drug responses along with interactive visualization of the results.

TL;DR: This study demonstrates that patient-derived and treatment-naïve glioblastoma stem cells cultures maintain patient-specific traits and display intertumoral heterogeneity in drug sensitivity to anticancer drugs.

TL;DR: Stemness markers in HGSC are associated with a decreased response to conventional chemotherapy and reduced survival if expressed by treatment‐naive tumours, and EGFR, mTOR‐PI3K and aurora kinase inhibitors are candidates for targeting this cell population.

TL;DR: The results show that patient-derived Sarcoma cells cultured in vitro are relevant and practical models for genotypic and phenotypic screens aiming to identify efficient drugs to treat sarcoma patients with poor treatment options.