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MatchMiner: an open-source platform for cancer precision medicine.
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.
Affiliation
  • Klein H; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA. hrklein@ds.dfci.harvard.edu.
  • Mazor T; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA. tmazor@ds.dfci.harvard.edu.
  • Siegel E; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Trukhanov P; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Ovalle A; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Vecchio Fitz CD; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Zwiesler Z; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Kumari P; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Van Der Veen B; The Hyve, Utrecht, The Netherlands.
  • Marriott E; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Hansel J; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Yu J; Department of Data Science, Dana-Farber Cancer Institute (DFCI), Boston, MA, USA.
  • Albayrak A; Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Barry S; Dana-Farber Cancer Institute, Boston, MA, USA.
  • Keller RB; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • MacConaill LE; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
  • Lindeman N; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
  • Johnson BE; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Rollins BJ; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Do KT; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Beardslee B; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Shapiro G; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Hector-Barry S; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Methot J; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Sholl L; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Lindsay J; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Hassett MJ; Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA, USA.
  • Cerami E; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA.
NPJ Precis Oncol ; 6(1): 69, 2022 Oct 06.
Article in En | MEDLINE | ID: mdl-36202909
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.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: NPJ Precis Oncol Year: 2022 Document type: Article Affiliation country: Estados Unidos Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: NPJ Precis Oncol Year: 2022 Document type: Article Affiliation country: Estados Unidos Country of publication: Reino Unido