Erik Reinertsen, M.D., Ph.D.

Profile

Physician-scientist and health AI executive with 8+ years building partnerships across biopharma, academic medicine, and AI product programs; experience spans MIT/Harvard research, venture, startup, and a $10.8B biotech exit.
Lead strategy and execution for multimodal AI collaborations spanning EHR, imaging, genomics, proteomics, and clinical trial data; translate partner needs into technical milestones, product requirements, and executive decisions.
Built collaboration models across pharma and top academic centers (Stanford, MD Anderson, UCSD, MSK, MGH, MIT, Broad); coordinate scientific, clinical, commercial, legal, and engineering stakeholders.
Comfortable operating in ambiguity; convert open-ended clinical and scientific questions into structured workstreams, evaluation plans, and decision points.
15+ publications, ~1,100 citations, and patents in biosignal ML, clinical prediction, and multi-omic patient stratification.

VP, Product & Strategy, Standard Model Bio 2025–Present

Own product, partnership, and commercial strategy for oncology-focused multimodal AI platform across EHR, imaging, genomics, and proteomics.
Provided project management and stakeholder alignment for a top-10 pharma partnership, including problem framing, milestone design, validation, reporting, and renewal planning.
Defined evaluation frameworks for clinical trial inclusion/exclusion automation, including accuracy benchmarks, latency targets, deployment runbooks, and partner success metrics.
Translate clinical and partner requirements into coordinated execution across ML research, data engineering, and clinical teams.
Built strategic ecosystem across leading AMCs and biopharma; identified where data, research, or workflow partnerships create durable advantage.

Advisor & Consultant, Doximity, Clairyon, Character Bioscience, UCLA, Cedars-Sinai 2023–Present

Head of Data Science, Prometheus Biosciences 2021–2024

Led data science and engineering strategy for multimodal data platform supporting drug discovery and translational research in immunology; company acquired by Merck for $10.8B.
Structured and scaled external data and research partnerships, including major autoimmune biobanks; coordinated clinical, genomic, imaging, regulatory, and engineering stakeholders.
Managed technical team and cross-functional programs translating scientific hypotheses into scalable data assets and partner-ready analyses.
Helped connect platform and data strategy to broader company value creation through IPO and acquisition.

Postdoctoral Fellow, MIT & Harvard Medical School 2019–2021

Led multi-institutional collaboration across MGH, MIT, and Broad to build a large-scale ECG dataset (11.6M records, 2.2M patients) linked to longitudinal clinical data.
Built TensorFlow pipelines and evaluation frameworks across ECG, ICU waveform, and imaging data at scale.
Coordinated data governance, cohort definition, and evaluation standards across institutions without direct authority.

Investment Associate, Takeda Ventures 2018–2019

Sourced and evaluated AI/ML companies across digital health, biomarkers, and therapeutics-adjacent platforms.

Reinertsen E et al. The Harvard-Emory ECG Database. Scientific Data, 2026.
Palanques-Tost E, Reinertsen E et al. Cardiac output estimation in the ICU. JACC Advances, 2025.
Diamant N, Reinertsen E et al. Patient contrastive learning for ECG modeling. PLOS Computational Biology, 2022.
Reinertsen E et al. Prediction of operative mortality for cardiac surgery. J Thorac Cardiovasc Surg, 2023.
Schlesinger DE, Reinertsen E et al. Deep learning model for pulmonary capillary wedge pressure. JACC Advances, 2022.
Clifford GD, Cakmak A, Shah AJ, Reinertsen E. Passive data collection for event prediction. Patent 12,057,232 B2.
Reinertsen E, Towfic F et al. Patient selection for IL-23 modulators. Patent application.
Clifford GD, Reinertsen E et al. Heart rate-based PTSD classification. Patent 11,246,520 B2.