Introduction
Non-Hodgkin’s lymphoma (NHL) is a heterogenous malignancy with many different subtypes. Although patients initially respond to treatments, approximately 40% of this cohort will subsequently relapse. After standard salvage regimen, determining the next option is largely empirical. We have developed a combinatorial functional precision medicine platform, Optim.AI, which utilizes efficiently designed experiments and small data AI to predictively rank all actionable treatments within the list of interrogated drug panel. Utilizing this approach, subsequent lines of treatment can be rationally determined for patients who have exhausted the standard repertoire of therapies. The clinical feasibility of using Optim.AI to guide treatment has been previously demonstrated in NHL1,2.
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