Klein Harry, Mazor Tali, Siegel Ethan, Trukhanov Pavel, Ovalle Andrea, Vecchio Fitz Catherine Del, Zwiesler Zachary, Kumari Priti, Van Der Veen Bernd, Marriott Eric, Hansel Jason, Yu Joyce, Albayrak Adem, Barry Susan, Keller Rachel B, MacConaill Laura E, Lindeman Neal, Johnson Bruce E, Rollins Barrett J, Do Khanh T, Beardslee Brian, Shapiro Geoffrey, Hector-Barry Suzanne, Methot John, Sholl Lynette, Lindsay James, Hassett Michael J, Cerami Ethan
Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
The Hyve, Utrecht, The Netherlands.
NPJ Precis Oncol. 2022 Oct 6;6(1):69. doi: 10.1038/s41698-022-00312-5.
Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials. Here, we describe MatchMiner's capabilities, outline its deployment at Dana-Farber Cancer Institute (DFCI), and characterize its impact on PM trial enrollment. MatchMiner's primary goals are to facilitate PM trial options for all patients and accelerate trial enrollment onto PM trials. MatchMiner can help clinicians find trial options for an individual patient or provide trial teams with candidate patients matching their trial's eligibility criteria. From March 2016 through March 2021, we curated 354 PM trials containing a broad range of genomic and clinical eligibility criteria and MatchMiner facilitated 166 trial consents (MatchMiner consents, MMC) for 159 patients. To quantify MatchMiner's impact on trial consent, we measured time from genomic sequencing report date to trial consent date for the 166 MMC compared to trial consents not facilitated by MatchMiner (non-MMC). We found MMC consented to trials 55 days (22%) earlier than non-MMC. MatchMiner has enabled our clinicians to match patients to PM trials and accelerated the trial enrollment process.
对患者肿瘤进行广泛、全面的测序有助于使用精准医学（PM）药物来靶向特定的基因组改变。治疗性临床试验对于测试新型PM药物以推进精准医学至关重要，然而，大量的患者测序数据加上复杂的临床试验资格标准，使得将患者与PM试验相匹配具有挑战性。为了便于患者参与PM试验，我们开发了MatchMiner，这是一个开源平台，用于通过计算将基因组特征明确的癌症患者与PM试验进行匹配。在此，我们描述了MatchMiner的功能，概述了其在丹娜法伯癌症研究所（DFCI）的部署情况，并阐述了其对PM试验入组的影响。MatchMiner的主要目标是为所有患者提供PM试验选择，并加速患者进入PM试验的入组过程。MatchMiner可以帮助临床医生为个体患者找到试验选择，或者为试验团队提供符合其试验资格标准的候选患者。从2016年3月到2021年3月，我们整理了354项PM试验，这些试验包含广泛的基因组和临床资格标准，MatchMiner促成了159名患者的166项试验同意（MatchMiner同意，MMC）。为了量化MatchMiner对试验同意的影响，我们测量了这166项MMC从基因组测序报告日期到试验同意日期的时间，并与未由MatchMiner促成的试验同意（非MMC）进行比较。我们发现，MMC比非MMC提前55天（22%）同意参加试验。MatchMiner使我们的临床医生能够将患者与PM试验相匹配，并加速了试验入组过程。
