期刊
SLAS TECHNOLOGY
卷 22, 期 3, 页码 276-288出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/2211068216681979
关键词
personalized medicine; precision medicine; combination therapy; drug development; drug cocktails; digital health; oncology
资金
- UCLA Children's Discovery and Innovation Institute (CDI) Today's and Tomorrow's Children Fund (TTCF) Award
- National Science Foundation CAREER Award [CMMI-1350197]
- Center for Scalable and Integrated NanoManufacturing [DMI-0327077, CMMI-0856492, DMR-1343991, OISE-1444100]
- V Foundation for Cancer Research Scholars Award
- Wallace H. Coulter Foundation Translational Research Award
- National Cancer Institute [U54CA151880]
- Society for Laboratory Automation and Screening Endowed Fellowship
- Beckman Coulter Life Sciences
- American Academy of Implant Dentistry Research Foundation [20150460]
- Office Of Internatl Science &Engineering
- Office Of The Director [1444100] Funding Source: National Science Foundation
Acute lymphoblastic leukemia (ALL) is a blood cancer that is characterized by the overproduction of lymphoblasts in the bone marrow. Treatment for pediatric ALL typically uses combination chemotherapy in phases, including a prolonged maintenance phase with oral methotrexate and 6-mercaptopurine, which often requires dose adjustment to balance side effects and efficacy. However, a major challenge confronting combination therapy for virtually every disease indication is the inability to pinpoint drug doses that are optimized for each patient, and the ability to adaptively and continuously optimize these doses to address comorbidities and other patient-specific physiological changes. To address this challenge, we developed a powerful digital health technology platform based on phenotypic personalized medicine (PPM). PPM identifies patient-specific maps that parabolically correlate drug inputs with phenotypic outputs. In a disease mechanism-independent fashion, we individualized drug ratios/dosages for two pediatric patients with standard-risk ALL in this study via PPM-mediated retrospective optimization. PPM optimization demonstrated that dynamically adjusted dosing of combination chemotherapy could enhance treatment outcomes while also substantially reducing the amount of chemotherapy administered. This may lead to more effective maintenance therapy, with the potential for shortening duration and reducing the risk of serious side effects.
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