The data exists.
The evidence doesn't. Yet.
The RWE automation platform for Life Sciences. Convert raw clinical data into regulatory-grade evidence in minutes.
What our users say.
“I ran a target trial emulation to compare ACE inhibitors vs ARBs for patients with heart failure. The tool generated the exact statistical code I needed to handle confounding, and gave a transparent, auditable trace from the raw data to the final survival analysis.”
“We used the pipeline to validate a new prognostic score for sepsis. The reproducibility is impressive. It generated a complete set of TFLs along with the underlying scripts used to query and structure the hospital records, giving me exactly what I needed for a publication-ready paper.”
“I needed to extract a complex patient cohort and run a sensitivity analysis on treatment sequences. The platform handled the temporal data mapping automatically and gave me the transparent statistical code required to independently verify the clinical science.”
From raw chaos to
regulatory rigor.
Bring Your Own Data
Connect EHR, claims, or registry data. Frekil automatically maps schemas and standardizes terminologies to OMOP CDM.
Protocol Generation
AI drafts FDA-aligned study protocols. Define cohorts, covariates, and endpoints in natural language.
Code Execution
Transparent R/Python code generation. Executed in a secure sandbox. Zero patient data exposure.
Regulatory Output
Auto-generated TFLs (Tables, Figures, Listings) ready for submission or publication.
No clinical data
ever touches AI.
AI generates the code. The code runs in a sandbox. The data never leaves.
We built a hard architectural wall between the models and your patient records. This isn't a policy. It's how the system is built.
Stitch the data once.
Generate evidence infinitely.
Frekil runs the same evidence infrastructure across every use case - label expansion, post-market safety, payer value dossiers, competitive intelligence, and trial feasibility - tailored to your specific research question and output requirements.
HEOR & Market Access
Generate comparative effectiveness evidence, cost-effectiveness analyses, and payer-ready value dossiers. Evidence your market access team needs before the formulary decision - not after.
Safety & Pharmacovigilance
Run safety analyses across millions of patient records in days. Detect adverse event signals before they surface through spontaneous reporting - where the vast majority of reactions currently go undetected.
Label Expansion
Test hypotheses for new indications using real-world patient data. Drug repurposing has a 25-30% success rate compared to 10% for novel compounds - but only if you can generate the evidence fast enough.
Competitive Intelligence
Understand how your drug performs against alternatives in real-world clinical practice, across specific patient subpopulations. Get the data your commercial strategy team needs before formulary decisions are made.
Trial Feasibility
Analyze real-world patient data to assess whether your trial design is realistic before you recruit a single patient. Identify sites, estimate timelines, and test inclusion/exclusion criteria against actual populations.
External Control Arms
Replace placebo arms with synthetic controls built from historical real-world patient data. Accelerate trials for rare diseases and oncology where traditional randomization is ethically or practically difficult.
Start with a
single hypothesis.
Someone is waiting for each of these studies.
The bottleneck shouldn't be the evidence infrastructure.