Marcia Fournier

AAAS Science & Technology Policy Fellow at National Cancer Institute (NCI)

Marcia Fournier is an accomplished entrepreneur with over 20 years of experience specializing in leading teams and developing cutting-edge health care products integrating genomics and machine learning technologies. Her expertise spans across drug discovery, biomarker development, and clinical diagnostics within the field of oncology.

In addition to her entrepreneurial pursuits, Marcia actively participates as a judge and mentor for start-ups in programs like MassChallenge Business Accelerator, StarOut, and InovAtiva, fostering innovation in the business sphere. She is a dedicated member of prestigious organizations like the American Society of Clinical Oncology, American Association for Cancer Research, and Coalition for the 21st Century Medicine.

Recognized for her outstanding contributions, Marcia Fournier has been honored with the Women of Innovation - Entrepreneurial Innovation and Leadership award by the Connecticut Technology Council in both 2016 and 2017. Her entrepreneurial acumen was also acknowledged with Connecticut's Entrepreneur of the Year award in 2018 for her exemplary work in scalable ventures.

Marcia Fournier pursued her Ph.D. in Molecular Biology at Universidade Federal do Rio de Janeiro, laying a strong academic foundation for her subsequent professional journey. She has held notable positions at renowned institutions and corporations, including serving as an AAAS Science & Technology Policy Fellow at the National Cancer Institute (NCI), Founder and President of Dimensions Sciences Inc., Founder and CEO of Bioarray Genetics Inc., Adjunct Associate Professor at College Staten Island CUNY, Principal Scientist at GlaxoSmithKline, and Instructor of Medicine at Dana-Farber Cancer Institute among others.

With a diverse background encompassing academia, industry, and entrepreneurship, Marcia Fournier brings a wealth of knowledge and experience to the realm of health care innovation, making her a pivotal figure in driving advancements at the intersection of genomics and machine learning in oncology.