Stanford Biomedical Data Science Program

What Stanford Biomedical Data Science Program does

Stanford's Department of Biomedical Data Science (DBDS) is an academic research unit within Stanford University School of Medicine, founded in 2015 and headquartered at the Stanford campus in Palo Alto, CA. The department merges biomedical informatics, biostatistics, computer science, and AI to advance precision health, leveraging multi-scale data including molecular, tissue, imaging, EHR, biosensory, and population datasets. Core research outputs include proprietary models such as CIBERSORTx, CytoTRACE 2, SEQUOIA, scGPT-based single-cell embeddings, spatial single-cell aging clocks, and AI-assisted tumor boards, plus the first experimentally validated AI-generated antibiotic molecule. The department operates on four concurrent tracks: graduate education (PhD, MS, co-terminal, postdoctoral, plus an online certificate through Stanford Online), federal research funding (ARPA-H, NIH/NLM, NSF, NIDA), training programs (NLM T15, Warren Alpert CBAI Scholars), and an External Engagement Program offering Tier One Affiliate memberships at $40,000/year and Tier Two Center of Excellence affiliations at $275,000/year with partners including IBM, AWS, Google, Microsoft, Genentech, GRAIL, 10X Genomics, and Accenture.

DBDS derives recurring revenue from a two-tier subscription-style affiliate program, project-based funding from a large base of federal grants, and donations/endowed funds (such as the $100,000 Darlene Vian Memorial Fund). The 2024 $8.9M ARPA-H award for AI tumor board research exemplifies its federal funding traction, while the annual Collaboration & Careers Forum (52 organizations in 2026, up 30%+ year-over-year) anchors community-led go-to-market. Select downstream collaborators include Stanford Health Care, Stanford Medicine Children's Health, GRAIL, Genentech, and 10X Genomics, where DBDS-trained scientists and AI methods are applied to clinical decision support, multi-cancer early detection, and single-cell genomics. Business model is therefore best categorized as a hybrid academic-commercial model: training and federally funded research on one side, monetization through industry affiliate memberships, sponsored research, and consulting on the other.

Name

Stanford Biomedical Data Science Program

Legal name

Stanford University School of Medicine - Department of Biomedical Data Science

Website

https://dbds.stanford.edu

Company type

Private

Founded year

2015

Operating status

Operating

Headcount range

11–50 employees

Short description

Stanford DBDS is an academic research department at Stanford School of Medicine that combines biomedical informatics, biostatistics, and AI to advance precision health. It trains graduate students and postdocs, develops proprietary AI models (CIBERSORTx, SEQUOIA, AI-assisted tumor boards), and engages industry partners through a tiered affiliate program.

Ownership category

akta.pro rank

Product category

Academic Biomedical Data Science Research and Education

NAICS

Scientific Research and Development Services (5417)

SIC

Services-Commercial Physical & Biological Research (8731)

akta.pro primary industry

Scientific Data Management & Data Platforms (SDMS/Data Lakehouse for R&D) (HLAGAJAC)

akta.pro secondary industries

Healthcare Data Lakes, Lakehouses & Cloud Warehouses (HLACAIAA), SaMD – Imaging & Signal Analysis (AI/ML) (HLACANAG), Digital & AI-Enabled Diagnostics (algorithmic interpretation, decision support tied to assays) (HLAAALAO)

Keywords

• Biomedical informatics
• Precision health research
• Clinical data science
• Computational biology programs
• Biostatistics education

Headquarters

HQ city

Palo Alto

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B and B2C

Offering type

Services

Cost components

Personnel, Technology or R&D, Operations, Marketing or Sales, Infrastructure

Revenue model

1. Research Grants and Federal Funding: DBDS receives significant funding from federal agencies including ARPA-H ($8.9M for AI tumor board research), NSF, NIH/NLM (NLM T15 training grant, NRSA fellowships), and NIDA for specific research projects
2. External Partnerships and Affiliate Program: Two-tier affiliate program: Tier One at $40,000 annual membership providing thought-leadership, recruiting access, and research connections; Tier Two at $275,000 for Center of Excellence partnerships in Precision Health, Multimodal Data, and Computational Biology
3. Donations and Endowed Funds: Gifts from alumni and donors supporting student activities, including Darlene Vian Memorial Fund ($100,000 endowed), Biomedical Data Science Gift Fund for pizza lunches, retreats, and student support
4. Strategic Collaborations: Sponsored research projects, seed grants, consulting arrangements, curriculum development, and in-kind donations from strategic partners like IBM, Bain, Google, Microsoft, Amazon, 10X Genomics

Pricing tiers

Go-to-market motion1 record

Distribution channels5 records

Marketing channels8 records

Core offering

Stanford DBDS is an academic research department offering graduate degree programs (PhD, MS, Co-Terminal, Honors Cooperative) and an online certificate in Biomedical Data Science, training future research leaders in biomedical informatics, biostatistics, AI/ML, and computational methods. The department conducts research and develops AI-driven tools for precision health—spanning AI-assisted tumor boards, pathology foundation models, CIBERSORTx, generative AI drug discovery, and multimodal foundation models—and connects industry, government, and academia through its External Engagement Program (Affiliate membership tiers), annual Collaboration and Careers Forum, and mentored industry partnerships.

Product overview

Stanford's Department of Biomedical Data Science (DBDS) is an academic research department at Stanford University School of Medicine, not a commercial product company. DBDS's offerings consist primarily of graduate education programs (PhD and MS degrees in Biomedical Data Science, plus an online graduate certificate), research resources (Data Studio), professional development programs (Industry Mentoring Program, External Engagement Program), and collaborative events (annual Collaboration and Careers Forum, Generative AI Workshops, AI Frontiers Summit). The department conducts research across biomedical informatics, biostatistics, and AI/ML for precision health, developing research tools and methodologies rather than commercial products.

Differentiator

Problem solved

Functional benefit

Brands

• Data Studio: A resource center providing data science support and collaboration space
• Workshop in Biomedical Data Science
• AI in Health Training
• Center I: Precision Health & Pharmacogenomics (PGx)
• Center II: Multimodal Data Integration
• Center III: Computational Biology and AI

Products and services

• Biomedical Data Science Graduate Program PhD and Master's degree programs in Biomedical Data Science training future research leaders to design and implement novel quantitative and computational methods for biology and medicine, including Academic Research MS, Co-Terminal Stanford undergraduate, and Honors Cooperative MS tracks.
• Online Biomedical Data Science Graduate Certificate Graduate certificate program in Biomedical Informatics Data Modeling and Analysis delivered through Stanford Online for remote learners seeking biomedical data science methodology training.
• Warren Alpert Computational Biology and AI (CBAI) Scholars Program Scholars program supporting trainees in computational biology and AI research at DBDS, including an annual research symposium and core faculty community.
• DBDS External Engagement Program (Affiliate Program) Two-tier industry partnership program offering annual memberships—Tier One at $40,000 and Tier Two Centers of Excellence at $275,000—providing industry partners with thought leadership, recruiting access, faculty liaison connections, research partnerships, advisory council participation, and Center affiliations in Precision Health and Pharmacogenomics, Multimodal Data Integration, or Computational Biology and AI.
• Collaboration and Careers Forum Annual forum connecting leaders from companies, government agencies, and organizations with DBDS faculty, students, and postdocs to discuss AI, data science, and precision healthcare advancements through lightning talks, career fairs, and industry panels.
• Generative AI Workshops Workshops bringing together interdisciplinary teams to ideate on generative AI applications in healthcare challenges, including Epic Cosmos Hackathon, d.School design-thinking frameworks, responsible AI panels, and VC engagement.

Quantifiable outcome

• First ARPA-H award ($8.9M) for AI tumor board research
• +8 more outcomes

Named customers5 records

Segments3 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability15 records

Feature8 records

Partnerships

16 partnerships are on record, tiered core and major.

• ARPA-H (Advanced Research Projects Agency for Health)coreStrategic or Co-development PartnerARPA-H awarded $8.9 million to Stanford DBDS to fund development of AI-augmented support tools for cancer tumor boards. Multi-disciplinary teams of clinicians collaborate to review data on cancer patients and determine optimal treatment courses using multimodal foundation models.
• Epic CosmoscoreTechnology or IntegrationEpic Cosmos dataset with over 250M patient records provides Stanford researchers opportunity to explore nationwide data. DBDS Professor Nigam Shah serves on Epic Cosmos Advisory Council. DBDS faculty including Roxana Daneshjou obtained Data Architect certification for SQL queries.
• IBMmajorStrategic or Co-development PartnerStrategic collaborator providing technology partnerships, research collaboration, and industry engagement with DBDS
• Bain & CompanymajorStrategic or Co-development PartnerStrategic collaborator in consulting and research partnerships, panel discussions on AI in healthcare
• Amazon Web Services (AWS)majorTechnology or IntegrationAWS provides cloud infrastructure and technology partnership for DBDS research and compute needs
• GooglemajorStrategic or Co-development PartnerGoogle participates in collaboration forums and provides technology partnerships for AI research. Scott Penberthy serves as Director of Applied AI at Google and engages with DBDS.
• MicrosoftmajorStrategic or Co-development PartnerMicrosoft provides technology partnerships including Azure cloud services. Matthew Lungren (formerly Stanford, now Microsoft) bridges academic-industry collaboration. Eric Horvitz (CSO Microsoft, DBDS alumnus class of 1990) participates in DBDS events.
• 10X GenomicsmajorStrategic or Co-development Partner10X Genomics CEO Serge Saxonov (DBDS alumnus) returns for collaboration forums. Company engages in recruiting and research discussions with DBDS community.
• Gladstone InstitutesmajorStrategic or Co-development PartnerCollaborative research partner in biomedical data science and AI applications in healthcare
• AccenturemajorStrategic or Co-development PartnerTier One Affiliate member engaging in thought leadership, recruiting, and research connections. Co-hosted Executive AI Summit on Healthcare and Medicine with DBDS in April 2025.
• Boehringer IngelheimmajorStrategic or Co-development PartnerTier One Affiliate member participating in industry collaboration and recruiting through DBDS external engagement program
• CareDxmajorStrategic or Co-development PartnerTier One Affiliate member engaging in transplant diagnostics research and industry partnerships with DBDS
• RegeneronmajorStrategic or Co-development PartnerTier One Affiliate member in pharmaceutical/biotechnology sector engaging with DBDS research community
• VeracytemajorStrategic or Co-development PartnerTier One Affiliate member in genomic diagnostics engaging with DBDS for research collaboration and recruiting
• Genentech/RochemajorStrategic or Co-development PartnerSarah McGough (Principal Data Scientist) establishes research projects with DBDS faculty including Rob Tibshirani, James Zou. Aïcha BenTaieb serves as Principal AI Scientist at Genentech. Multiple alumni work at Genentech.
• GRAILmajorStrategic or Co-development PartnerJeffrey Venstrom (CMO) participates in DBDS panels. GRAIL develops multi-cancer early detection tests using machine learning, aligning with DBDS research in AI diagnostics.

Scale indicators8 records

Recent moves7 records

Expansion highlights7 records

Emerging players

• Recursion Pharmaceuticals: AI-driven drug discovery company that combines high-throughput biology with foundation models — a commercial counterpart to DBDS's generative AI for drug discovery (e.g., the Zou-lab AI-generated antibiotic) and competes for the same talent pool.

Direct peers

• Icahn School of Medicine at Mount Sinai — Institute for Genomic Health: Mount Sinai's genomics-and-AI institute combines EHR-linked biobank research with machine learning for precision medicine — directly comparable to DBDS's multimodal data integration work.
• Harvard Medical School Department of Biomedical Informatics: Harvard's flagship biomedical informatics academic department, with overlapping scope in AI for healthcare, EHR-based research, genomics, and precision health. Most direct academic peer to Stanford DBDS.
• UCSF Bakar Computational Health Sciences Institute: UCSF's institute for computational health sciences, working at the intersection of clinical data, AI, and precision medicine — directly comparable to DBDS's research and training mission.
• Columbia University Department of Biomedical Informatics: Columbia's DBMI covers clinical informatics, translational bioinformatics, and AI for healthcare, with strength in EHR data and population health — a close functional peer to Stanford DBDS.
• MIT CSAIL / Abdul Latif Jameel Clinic for Machine Learning in Health: MIT's primary computational medicine research hub, focused on AI/ML for clinical decision support, biomedical imaging, and population health — directly comparable to DBDS's AI/precision-health agenda.
• University of Pennsylvania Institute for Biomedical Informatics: Penn's biomedical informatics institute with overlapping foci in translational bioinformatics, AI/ML methods, and graduate training — a same-tier academic peer competing for federal grants and trainees.
• University of Washington Department of Biomedical Informatics and Medical Education: UW's BMI department combines biomedical informatics with medical education, with active research in clinical AI and translational bioinformatics — a comparable academic peer in the same elite tier.
• Johns Hopkins Department of Biomedical Informatics: Top-tier academic biomedical informatics program with parallel research in clinical NLP, translational bioinformatics, and AI in healthcare; competes with DBDS for the same NIH/NSF funding and faculty talent.
• Vanderbilt University Department of Biomedical Informatics: Vanderbilt's BMI department is a leading academic biomedical informatics program with strengths in clinical informatics, NLP, and AI — directly comparable in scope and training mission.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/StanfordDBDS
• YouTubeyoutube.com/@DBDSatStanfordUniversity-e4q
• LinkedInlinkedin.com/company/stanford-dbds-program

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds

Investors

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M&A

Investments

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Frequently asked questions about Stanford Biomedical Data Science Program