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Optimization of Acute Lymphoblastic Leukemia Patient Regimens Using a Phenotypic Personalized Medicine Digital Health Platform

Abstract

Acute lymphoblastic leukemia (ALL) is a blood cancer that is characterized by overproduction of lymphoblasts in the bone marrow. Treatment for ALL typically uses combination chemotherapy. However, a major challenge for combination therapy is the inability to pinpoint drug doses that are optimized for each patient. To address this challenge, we have developed a powerful digital health technology platform based on the field of Phenotypic Personalized Medicine (PPM). PPM identifies patient-specific maps that correlate drug inputs with phenotypic outputs parabolically. In a disease mechanism-independent fashion, PPM was able to determine individualized drug ratios/dosages for 2 ALL patients in this study using a retrospective optimization approach. This optimization process demonstrated that dynamically adjusted dosing of combination chemotherapy can enhance treatment outcomes while also substantially reducing the amount of chemotherapy that is required. This may lead to shortened maintenance therapy regimens that will in turn, reduce the onset of complications following remission.

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