Kurt Roloff says large pharma often treats compliance as a cost center, but secure collaboration can turn existing data into a profit enabler. It lets divisions and companies reuse data across geographies, cutting IRB and administrative overhead so rare pediatric cancer research becomes more cost efficient.
Kurt Roloff describes U.S. tribal communities with well-founded trust issues about sharing data with pharma and federal agencies. His company protects rich tribal datasets locally with strong guarantees to tribal health-center data stewards, while letting researchers use them to develop treatments tailored to those communities' genetic and environmental conditions.
Roloff notes data officers hesitate because 'no one ever gets fired for saying no,' making them fear exposure. Strong encryption guarantees and GDPR court acceptance, he says, reduce the perceived liability of sharing rather than just the technical risk. That reframes data repositories as potential value sources instead of cost centers.
Roloff says getting the privacy technology in place is usually the easy part. The harder work is communicating with regulators, standards bodies and policy authorities about changing workflows and liability. He personally meets with Capitol Hill, White House and NIST/OSTP officials to move that conversation forward.
Roloff says every country sets its own data rules, but Germany's GDPR decisions, plus forward-leaning Singapore, South Korea and California, influence others. Showing a European customer that German courts accept this technology makes regulatory and customer conversations easier, he says, because other jurisdictions often follow the perceived leaders.
Roloff agrees that AI in medicine is constrained less by models or compute than by access to sensitive data. He says privacy technology is ahead of community acceptance; secure inference through commercial trusted execution environments is emerging, but training large foundational models on patient data remains the 'golden apple' still being pursued.
Roloff wants to turbocharge reuse of clinical trial data so it can be reanalyzed for other diseases. He expects secure collaboration within three to five years to make virtual trials using reused data less expensive for pharma and the FDA to accept, which could reshape drug research and development.