M2GEN’s portfolio consists of data solutions and services that have established track record of accelerating oncology research with biopharma partners. Using the Total Cancer Care® Protocol as a master trial-screening protocol, M2GEN was able to dramatically accelerate enrollment for an otherwise challenging biomarker-driven clinical trial in gastric and pancreatic cancers. M2GEN is collaborating with leading biopharmaceutical companies in the development of “synthetic control arms.” One such example is a Phase 2 CAR-T clinical trial. M2GEN Services include Bioinformatics Tools & Analysis, Clinical Trial Services, and Special Projects.
The M2GEN Portfolio allows biopharmaceutical companies to discover new targets and biomarkers, supplement clinical trial design and enrollment, and secure post-market analysis over time. M2GEN has three primary datasets: ORIEN Avatar, Lyncis, and Zenith, each of which feature rich, integrated clinical and molecular data. We also create Real World Data comparator cohorts to support data collection for FDA submission based on the Sponsor’s criteria and obtain follow-up data over time and work with research groups to provide targeted datasets. If you would like to find out if M2GEN has your dataset of interest, please complete our query form.
Biopharmaceutical companies play a vital role in the fight against cancer, from researching new targets to developing innovative clinical trials and ultimately bringing new medicines to the market. By leveraging our Oncology Research Information Exchange Network® (ORIEN) database to support their efforts, we help our pharma partners reduce research and discovery costs, perform more effective clinical trials, and accelerate drug development timelines.
We provide biopharmaceutical companies unparalleled insights into patients' clinical and molecular data that extends beyond the treatment window, giving broader context to health and outcomes and a unique view into how cancer impacts people differently. This accelerates cancer research and helps companies make more informed decisions around clinical trial structuring and development, maximizing the value of the data in our network.
Contact us for more information on cohorts of interest, special projects, and how to license our data and solutions.
M2Gen's core solution, ORIEN Avatar®, is an ever-expanding data solution focused on patients at high risk for disease progression and is unique in the depth of molecular and longitudinal clinical data it provides. In consultation with our pharma partners and ORIEN Members, M2Gen has identified cohorts of “high risk” patients, i.e., those with advanced primary or metastatic disease, who have limited treatment options, and those patients who are likely to develop progressive disease. Through development of a comprehensive genotypic and phenotypic profile of patients who have consented to being studied, we can identify their in silico “avatar,” i.e., patients like them. We can use this information to accelerate research, e.g., to match patients to clinical trials and develop real-world comparator cohorts. The depth and breadth of the ORIEN Avatar clinical and molecular data enables study of a wide array of clinically relevant markers, including emerging biomarkers associated with response to immuno-oncology agents.
Our ecosystem is scientifically rooted and believes meaningful advancements for patients come from data-driven decisions. See how we are already contributing to the fight against cancer. The following publications were developed by ORIEN Members based on Total Cancer Care data.
de la Iglesia JV, Slebos RJC, Martin-Gomez L, Wang X, Teer JK, Tan AC, Gerke TA, Aden-Buie G, van Veen T, Masannat J, Chaudhary R, Song F, Fournier M, Siegel EM, Schabath MB, Wadsworth JT, Caudell J, Harrison L, Wenig BM, Conejo-Garcia J, Hernandez-Prera JC, Chung CH. Clin Cancer Res. 2020 Mar 15;26(6):1474-1485. doi: 10.1158/1078-0432.CCR-19-1769. Epub 2019 Dec 17. PubMed PMID: 31848186; PubMed Central PMCID: PMC7073297.
Yun S, Sharma R, Chan O, Vincelette ND, Sallman DA, Sweet K, Padron E, Komrokji R, Lancet JE, Abraham I, Moscinski LC, Cleveland JL, List AF, Zhang L. Leuk Res. 2019 Sep;84:106194. doi: 10.1016/j.leukres.2019.106194. Epub 2019 Jul 18. PubMed PMID: 31357093. https://www.ncbi.nlm.nih.gov/pubmed/31357093
Stewart PA, Welsh EA, Slebos RJC, Fang B, Izumi V, Chambers M, Zhang G, Cen L, Pettersson F, Zhang Y, Chen Z, Cheng CH, Thapa R, Thompson Z, Fellows KM, Francis JM, Saller JJ, Mesa T, Zhang C, Yoder S, DeNicola GM, Beg AA, Boyle TA, Teer JK, Ann Chen Y, Koomen JM, Eschrich SA, Haura EB. Nat Commun. 2019 Aug 8;10(1):3578. doi:10.1038/s41467-019-11452-x. PubMed PMID: 31395880; PubMed Central PMCID: PMC6687710. https://www.ncbi.nlm.nih.gov/pubmed/31395880
Mirza AS, Yun S, Ali NA, Shin H, O'Neil JL, Elharake M, Schwartz D, Robinson K, Nowell E, Engle G, Badat I, Brimer T, Kuc A, Sequeira A, Mirza S, Sikaria D, Vera JD, Hackney N, Abusrur S, Jesurajan J, Kuang J, Patel S, Khalil S, Bhaskar S, Beard A, Abuelenen T, Ratnasamy K, Visweshwar N, Komrokji R, Jaglal M. Thromb J. 2019 Jul 2;17:13. doi: 1186/s12959-019-0202-z. eCollection 2019. PubMed PMID: 31303864; PubMed Central PMCID: PMC6604148. https://www.ncbi.nlm.nih.gov/pubmed/31303864
Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk. Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, Im HK, Chen YA, Permuth JB, Reid BM, Teer JK, Moysich KB, Andrulis IL, Anton-Culver H, Arun BK, Bandera EV, Barkardottir RB, Barnes DR, Benitez J, Bjorge L, Brenton J, Butzow R, Caldes T, Caligo MA, Campbell I, Chang-Claude J, Claes KBM, Couch FJ, Cramer DW, Daly MB, deFazio A, Dennis J, Diez O, Domchek SM, Dörk T, Easton DF, Eccles DM, Fasching PA, Fortner RT, Fountzilas G, Friedman E, Ganz PA, Garber J, Giles GG, Godwin AK, Goldgar DE, Goodman MT, Greene MH, Gronwald J, Hamann U, Heitz F, Hildebrandt MAT, Høgdall CK, Hollestelle A, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James P, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Kwong A, Le ND, Leslie G, Lesueur F, Levine DA, Mattiello A, May T, McGuffog L, McNeish IA, Merritt MA, Modugno F, Montagna M, Neuhausen SL, Nevanlinna H, Nielsen FC, Nikitina-Zake L, Nussbaum RL, Offit K, Olah E, Olopade OI, Olson SH, Olsson H, Osorio A, Park SK, Parsons MT, Peeters PHM, Pejovic T, Peterlongo P, Phelan CM, Pujana MA, Ramus SJ, Rennert G, Risch H, Rodriguez GC, Rodríguez-Antona C, Romieu I, Rookus MA, Rossing MA, Rzepecka IK, Sandler DP, Schmutzler RK, Setiawan VW, Sharma P, Sieh W, Simard J, Singer CF, Song H, Southey MC, Spurdle AB, Sutphen R, Swerdlow AJ, Teixeira MR, Teo SH, Thomassen M, Tischkowitz M, Toland AE, Trichopoulou A, Tung N, Tworoger SS, van Rensburg EJ, Vanderstichele A, Vega A, Edwards DV, Webb PM, Weitzel JN, Wentzensen N, White E, Wolk A, Wu AH, Yannoukakos D, Zorn KK, Gayther SA, Antoniou AC, Berchuck A, Goode EL, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J. A Cancer Res. 2018 Sep 15;78(18):5419-5430. doi: 10.1158/0008-5472.CAN-18-0951. Epub 2018 Jul 27. PubMed PMID: 30054336; PubMed Central PMCID: PMC6139053. https://www.ncbi.nlm.nih.gov/pubmed/30054336
Quantification of Breast Cancer Protein Biomarkers at Different Expression Levels in Human Tumors. Chen Y, Britton D, Wood ER, Brantley S, Fournier M, Wloch M, Williams VL, Johnson J, Magliocco A, Pike I, Koomen JM. Methods Mol Biol. 2018;1788:251-268. doi: 10.1007/7651_2017_113. PubMed PMID: 29243084.
Circulating T Cell Subpopulations Correlate With Immune Responses at the Tumor Site and Clinical Response to PD1 Inhibition in Non-Small Cell Lung Cancer. Manjarrez-Orduño N, Menard LC, Kansal S, Fischer P, Kakrecha B, Jiang C, Cunningham M, Greenawalt D, Patel V, Yang M, Golhar R, Carman JA, Lezhnin S, Dai H, Kayne PS, Suchard SJ, Bernstein SH, Nadler SG. Front Immunol. 2018 Aug 3;9:1613. doi: 10.3389/fimmu.2018.01613. eCollection 2018. PubMed PMID: 30123214; PubMed Central PMCID: PMC6085412.