Treatment of relapsed/refractory non-Hodgkin’s lymphoma (R/R-NHL) remains one of the most difficult challenges in haematologic malignancies, with many patients exhausting standard therapies and facing limited treatment options. In a final report extending on interim results from a prospective study led by Dr Anand D Jeyasekharan and A/Prof Edward Chow at NCIS and NUS, a novel AI-guided ex vivo drug screening tool, Quadratic Phenotypic Optimisation Platform (QPOP), accurately predicted response to drug combinations in 74.5% of 117 lymphoma cases.

Those who received QPOP-guided patient-specific treatment had a 59% overall response rate and nearly 60% experienced longer response duration compared to their preceding treatment. Two-year survival analysis revealed significant extension of progression free survival in QPOP-guided group compared to those on standard salvage regimens (P=0.019), with 44% lower risk of progression. These findings demonstrated clinical utility and potential of QPOP as a functional precision medicine platform, supporting its development as a clinical decision support tool in the management of R/R-NHL patients.

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