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November 19, 2025

A living map of the resources I regularly return to while building prevention-focused health tech, human digital twins, wearables, and longevity R&D.


research search engines & paper workflows

How I read papers

  • Start with 2–3 reviews → collect the landmark citations → follow citation graph forward.
  • Capture: problem, dataset, method, endpoints, limitations, "what would change my mind?"

digital twins (health + device + simulation)

Twin infrastructure / patterns

Physiology & simulation

  • BioGears (human physiology engine)
  • OpenSim (musculoskeletal simulation)
  • SimVascular (blood flow + patient-specific modeling)
  • OpenCOR / CellML ecosystem (reusable physiology models)

wearables + biosignals (real-time physiology)

Signal processing

Datasets

  • PhysioNet (waveforms + challenges)
  • UK Biobank (when accessible; massive population-scale)
  • NIH/NLM & NCBI resources (genomics + clinical references)

healthcare data standards & interoperability

  • HL7 FHIR (data model + APIs for clinical exchange)
  • HAPI FHIR (practical server/client implementation)
  • OHDSI / OMOP CDM (observational data standardization)
  • SNOMED CT / LOINC / ICD (clinical vocabularies; mapping matters)

biomedical knowledge graphs & targets


drug discovery & computational biology

  • RDKit (cheminformatics foundation)
  • DeepChem (drug discovery ML toolkit)
  • OpenMM (molecular simulation)
  • DiffDock (DL docking methods; good for exploring structure-based workflows)
  • AlphaFold/OpenFold ecosystem (protein structure workflows)

longevity & prevention

  • Hallmarks of Aging literature (mechanism framing)
  • Biomarker discovery: proteomics/metabolomics/epigenetics resources
  • Geroscience reviews (interventions + translational pathways)

product, growth, and commercialization (health-tech reality)

  • YC Library (startup fundamentals + GTM)
  • "Crossing the Chasm" frameworks (adoption + distribution)
  • Practical sales: discovery calls, ICP definition, messaging tests
  • Marketing experiments: content → distribution → measurement loops

communities / conferences I track

  • Digital health + wearables conferences
  • Computational biology & ML conferences
  • Longevity/geroscience meetings
  • Clinical informatics communities (FHIR/OMOP builders)

my filter for "good links"

  • Is it actionable?
  • Does it explain endpoints & failure modes?
  • Does it survive deployment / real-world messiness?
  • Does it help a clinician (or patient) make a better decision?