Two decades inside clinical research sites taught Ryan one truth: enrollment failures are planning failures. Today he leads strategy at CT Scan, building the forecast layer the industry has been missing.
The pattern behind every missed timeline.
For most of my career I've worked alongside research sites, coordinators, investigators, and leadership — helping studies open faster, run smoother, and stay financially sustainable.
Over time I noticed a pattern. Some studies are difficult no matter how strong the site is. Amazing teams still struggle. Timelines slip. The issue usually isn't effort. It's expectations.
Enrollment challenges begin long before activation. Projections are built on optimistic feasibility, incomplete referral assumptions, and historical comparisons that don't match the real patient pathway.
My work now focuses on helping the industry think about enrollment earlier — treating it as something that can be analyzed, forecasted, and engineered, instead of reacted to.
better expectations → healthier sites → faster trials → more patients receiving therapies
CT Scan
Predictive Enrollment Engineering™ · powered by DYNO Ai™
CT Scan models the precise cost per enrollment for digital advertising — so sponsors know exactly how much must be spent to enroll a patient. Our proprietary engine, DYNO Ai™, transforms each protocol into a fully modeled enrollment blueprint with mathematical precision.
Cost-per-Enrollment Modeling
CT Scan mathematically models the digital advertising cost required to enroll a single patient — so sponsors know exactly what must be spent before a dollar is committed.
DYNO Ai™ Blueprint
DYNO Ai™ converts each protocol into a fully modeled enrollment blueprint — projecting cost-per-lead, cost-per-enrollment, and enrollment velocity with mathematical precision.
Optimized Execution
CT Scan executes against DYNO's forecasts — optimizing ad strategy, budget allocation, site selection, and funnel management in real time against the model.
Translate Predictive Enrollment Engineering™ into practical implementation across sponsors, CROs, and site networks — projecting cost-per-lead, cost-per-enrollment, and enrollment velocity ahead of activation, then operationalizing recruitment against the model.
Launch DYNO Ai™ — dyno.clinicaltrialscan.ai
Eighteen years inside the problem.
Chief Strategy Officer
Advancing Predictive Enrollment Engineering™ powered by DYNO Ai™. Translating the framework into practical implementation across sponsors, CROs, and site networks.
Founder & Principal Consultant
Advising independent sites, specialty practices, and hospital programs on startup strategy, budgeting, workflow design, and enrollment execution.
Director of Clinical Research — Finance & Regulatory
Oversaw financial and regulatory infrastructure for clinical research across the hospital system — budget strategy, coverage analysis, billing compliance, and investigator payments.
Administrator
Built operational infrastructure for fellowship programs (Sports Medicine, Total Joint, Spine) and led the orthopedic clinical research program end-to-end.
Clinical Research Manager
Led clinical research coordinators across multiple therapeutic areas; integrated research into routine clinical care and reduced startup delays.
Clinical Project Manager II
Coordinated study startup, regulatory, and execution across a large hospital system — first deep look at how clinic capacity, not protocol, gates enrollment.
Project Manager
First role outside the site environment — bridging sponsor timelines with site operational reality.
Clinical Research Coordinator → Team Manager
Began career in oncology trials (GI, Head & Neck, Thyroid). Patient-level work that shaped a lifelong focus on access, feasibility, and enrollment predictability.
If you work in clinical research,
let's exchange ideas.
Sponsor, CRO, site, or partner — Ryan is always happy to talk enrollment, feasibility, and the upstream work that makes trials succeed.
Start a conversation→