The Search for Cures Leads to Silicon Valley

Panel Context & Audience

• Hosted by Lindy Fishburne (Breakout Labs/Thiel Foundation), the session features leaders from Intel, Stanford Medicine, 23andMe, and Science 37.
• Audience polling revealed high engagement: >30-40% had undergone genetic testing, >30% participated in clinical trials (or were willing to), and >30% currently use wearables.
• Key theme: The intersection of Silicon Valley technology and healthcare aims to shift from "sick care" (reactive) to "precision health" (proactive/preventative).

Intel's Data Strategy: The Collaborative Cancer Cloud (CCC)

• Intel has dedicated ~20 years to healthcare, now focusing on personalized cancer care through data rather than just device hardware.
• Problem: Genomic and clinical data is siloed; a single oncologist lacks the data volume to make optimal personalized treatment decisions.
• Solution: The Collaborative Cancer Cloud (CCC), a distributed analytics platform developed with Oregon Health & Science University.
• Mechanism: Analytics and queries move to the data (securely) rather than moving data to a central repository, preserving data sovereignty.
• Governance: Participating institutions define strict boundary conditions (e.g., data usable only by academics, not pharma).
• Partners: Dana-Farber Cancer Institute, Ontario Institute for Cancer Research (each >15,000 full genome cases).
• Outcome Goal: Enable rapid identification of treatment efficacy and side-effect profiles based on global genomic datasets.

Stanford Medicine: Shift to Precision Health

• Defining "Precision Health" as the next generation of "Precision Medicine," shifting focus from treating established disease to preventing it.
• My Heart Counts App: Launched March 2015 with Apple; >50,000 users participating in research studies.
• Key Metric: >6,000 participants completed the six-minute walk test, creating the largest cohort of this data globally.
• Partnership: Integrated 23andMe genetic data (1.2M+ users) with My Heart Counts phenotypic data to interpret cardiac health in genetic context.
• Longitudinal Study: Collaboration with Verily (Alphabet/Google) on a cohort of 10,000 individuals for genomic and clinical longitudinal tracking.

23andMe & We Are Curious: Consumer Data & Social Layers

• Participation Rate: ~80% of 1.2M+ 23andMe users have consented to participate in research surveys.
• Research Model: "Instant studies" via online surveys linking genomic data to phenotypic data (case-control design), reducing research timelines from years to immediate data retrieval.
• Data Control: Analytics performed internally; data is not pushed to pharma partners without explicit consent.
• We Are Curious: Linda Avey's new venture focuses on aggregating siloed data (wearables, environment, symptoms) for individuals (N=1) to identify patterns for conditions like migraines, autism, and chronic fatigue.
• Social Component: Emphasizes the missing social layer in health apps—peer support, shared stories, and community encouragement for behavior change.

Science 37: Decentralized Clinical Trials

• Mission: Solving the participation gap where 90% of patients want to join trials, but <3% do due to logistical barriers.
• Model: "Metasite" approach shifting the research center from the investigator to the patient; trials are conducted at patients' homes.
• Operations: FDA-registered randomized controlled trials reaching patients via Google/Facebook; drugs, nurses, and blood draws delivered to home; samples shipped to labs.
• Diversity Impact: Minorities represent 30-40% of Science 37 trials vs. <5% in traditional site-based trials.
• Speed: Trials run 30-40% faster than traditional models, accelerating drug discovery costs (estimated $1M/day delay cost).
• Wearable Validation: Validated a wearable device for measuring nighttime scratching in sleep labs, establishing a new "real-world data" gold standard for patient-reported outcomes.
• Data Ownership: Advocates for patient ownership of biological data; utilizes NORA (Research EMR) to keep patient records centralized while clients (pharma/payers) purchase data access.

Lisa Sunan (Breakout Labs/Venture Capital): Delivery System & Economics

• Focus: Emphasizes that the value of precision medicine lies in the delivery system (adherence, behavior change) rather than just drug discovery.
• Problem: ~33% of medical care is wasted or error-prone; patients are non-compliant with treatments.
• Economic Reality: New cures require significant economic scrutiny and validation to be reimbursed; fee-for-service models hinder preventative/precision care adoption.
• Partnerships: Highlights "weird bedfellows" like the American Heart Association partnering with AstraZeneca and Google, or Merck investing $25M into Geisinger for a cardiovascular data program.
• HealthReveal: Cites as an example of a company using algorithms (fed by EMR, wearables, claims) to mimic credit card fraud detection, flagging clinical risks in real-time to doctors.
• Monetization: Success depends on proving actionable decisions lower healthcare costs; "Pick and shovel" companies (data movers) make early money, but value is realized by those who "melt the gold" (actionable outcomes).

Q&A Highlights & Future Outlook

• Data Interoperability: Consensus that a "universal ID" and government/regulatory standardization are required to stitch disparate data sources together; current EMR systems are often billing-focused, losing clinical nuance (e.g., SF General Hospital spending $300M on a billing-centric EMR).
• HIPAA & Security: Linda Avey notes HIPAA is often less restrictive than assumed for DTC companies not involved in reimbursement, but security breaches remain a critical barrier to patient trust.
• Quality of Life (QoL) Metrics: FDA and sponsors are increasingly prioritizing patient-reported outcomes (PROs) and QoL (e.g., activity levels via actigraphy) over traditional clinical endpoints.
• Reimbursement Reform: Teva Chairman (former Israeli Healthcare CEO) stresses that innovation fails without changing the reimbursement model from fee-for-service to value/outcome-based payments; ROI timelines need to expand beyond 2 years.
• Patient Access: Science 37 and disease foundations are using digital channels and social networks to connect patients to trials, bypassing the "geographic lock" of traditional academic centers.
• Timeline: Panelists predict immediate adoption of telemedicine for routine follow-ups, with a full cultural shift in healthcare delivery expected over the next decade as smartphone penetration (80% global in 2020) enables mass engagement.