TrialFlow's agents draft the protocols, trial documents, eligibility checks, safety reports, and billing work every trial runs on. A clinician reviews and signs each one. Every patient, visit, and action tracked to a permanent audit trail — replacing Excel sheets and manual record-keeping.
None of this is for lack of effort. It's general-purpose software (Excel, email, shared drives) doing a job it was never built for. That gap is where trials delay, deviate, and stall.
Trial software today either stores the records or holds the files. Every system tracks something else: which trials exist, what data the sponsor needs, what regulators require, which patient might be eligible. None of them do the actual work. TrialFlow is built around the trial and the patient. Its agents draft the documents. Grade the side effects. Reconcile the billing. Prepare the filings. A human reviews and signs each one before it goes anywhere.
AI does the work that wastes time. Humans make the decisions that affect safety.
A protocol goes in. Agents generate the visit-by-visit nursing sheets, eligibility checks, and safety write-ups — each citing the exact protocol section it came from.
A quality-control agent checks every draft against the source protocol and flags anything uncertain. Flagged work goes to a named human reviewer, then the coordinator and investigator. Agents never sign, dose, consent, or file on their own.
The investigator signs with a password and a one-time passcode. Every action is written to an append-only, tamper-evident 21 CFR Part 11 audit trail — the FDA's standard for electronic records. Nothing is deleted.
Drop in a redlined amendment. TrialFlow rebuilds only the documents the change actually touches — and nothing reaches a patient until the ethics board approves it.
The amendment is read and compared against the current protocol.
2 of 47 documents regenerate. The other 45 stay at their approved version.
A missing "max 800 mg" dose cap in §7.4.1 is caught against the source.
The analyst resolves the flag; the investigator e-signs (Part 11).
The amended protocol and consent form go to the IRB — the required gate.
Once approved, affected patients re-consent at their next visit.
Most software picks a side. A site system for the cancer center, or a separate sponsor system for the pharma company. TrialFlow runs both on one shared spine: the same trial, the same data, two views. Each person sees only what they're allowed to. Every crossover is logged.
Visit tip sheets, nursing flow sheets, and in-service notes, written from the protocol and checked against it — line by line, with a citation for every claim.
40–80 hrs → under 2 hrs per trial (projected)Site billing checked against what each payer covers; sponsor budgets, milestones, and invoices reconciled before payment.
coverage analysis · invoice-to-contractEach criterion with a plain pass / fail / needs-review and a citation.
HL7 FHIR R4 · Epic-compatibleSeverity grading and expedited safety reports on the 7- and 15-day clocks.
CTCAE v5.0 · MedWatch 3500AEthics-board cascade, IND lifecycle, ClinicalTrials.gov, agency correspondence.
IRB · IND · FDAAA 801National enrollment, grant sections, and catchment & enrollment-equity.
CTRP · CCSG (P30)The reassurance a cancer center and a sponsor both need before AI touches a trial.
Password, one-time passcode, and a meaning-of-signature statement — the FDA's 21 CFR Part 11 standard.
Every action writes a linked, hash-chained record. Nothing is edited or deleted; each entry traces back to its source.
A named reviewer signs off on every AI-drafted document. Agents never sign, dose, consent, or file on their own.
Every AI answer shows its reasoning three ways — plain, clinical, and audit-ready — from one verified record.
A well-funded competitor could write similar software. What they can't shortcut is everything around it.
Site and sponsor on the same system — not two products bridged after the fact.
The NCI-specific reporting, coverage, and review work generic trial software doesn't touch.
A 9–18 month buying cycle and a 12-month security-audit clock a fast follower still has to serve.
Built by someone who runs these trials — operational ground truth a competitor can't hire.
TrialFlow is built by Dr. Mahendra Chaudhari, a physician (MD) with a Master's in Clinical Research from Boston University. He's worked every seat in the clinical research room. Practicing physician in India for five years. Founder and operator of a clinic and a hospital. Sub-investigator on early-phase oncology trials. Today: leading and managing oncology trials at a major cancer center across NCI, SWOG, COG, Alliance, IIT, and industry-sponsored studies (sarcoma, lymphoma, cell therapy).
Every workflow in TrialFlow started as a real problem on a real trial. One he's caused, caught, or watched cause harm.
He's been building with AI in clinical research for over two years, starting with a precision-medicine program in pediatric autism. Since then: a protocol quality-control agent presented at his institution's AI Prompt-a-Thon, an oncology research-agent collaboration, 9 peer-reviewed publications, and a Cedars-Sinai Applied AI for Health Systems certificate in progress.
He's not writing about clinical research from the outside. He runs trials on Monday morning.
Bring a real protocol. Watch the agents draft it, a human approve it, and the whole thing get signed.