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ClinPrecision, by Novatra AI

Built for the trial you actually designed.

Basket, umbrella, platform or a single-arm Phase II. ClinPrecision runs data capture, operations, documents and quality on one auditable record, with AI that proposes and people who approve.

Book a demoSee how it fits together
SCREENINGMASTERPROTOCOLbiomarker matchCohort AEGFR exon 20Cohort BKRAS G12CCohort CHER2 amplifiedCohort Dadded at week 24EVENT STREAM · every change appended, none overwritten
One protocol, four cohorts, one record illustrative
EDC · CTMS · eTMF · QMS on one platformDesigned for 21 CFR Part 11CDASH / SDTM mappingMedDRA & WHODrug coding
Platform
01 / 04

Today, a trial lives in fourteen systems.

Each one holds part of the record. People reconcile the gaps by export and email, and some data falls through.

02 / 04

ClinPrecision keeps one record.

Data capture, operations, documents and quality read and write the same trial. No interfaces to validate, nothing to reconcile.

03 / 04

Every study is a set of cohorts.

Screened patients route to the cohort their biomarkers match. A new cohort can open mid-study without a new build.

04 / 04

Every change is appended, never overwritten.

A deviation in data capture opens a quality event, a CAPA and retraining within milliseconds, each signed by the person who caused it.

Hover any dot to read it · data is illustrative

Master protocols

Every study is a set of cohorts. A standard trial is just a set of one.

In about a decade, master protocols went from a niche design to a large share of oncology trials. ClinPrecision models cohorts from the data model up, so a platform trial uses the same screens as a Phase III, with no special mode and no add-on.

Basket

One therapy across several indications, each cohort with its own enrolment and stopping rules.

Umbrella

One disease, a shared biomarker panel, and patients routed to the matching cohort.

Platform

Arms added and dropped mid-study at interim looks, under governed design changes.

SMART

Patients re-assigned at decision-point visits based on how they responded.

Works with your IRT. Randomisation and drug supply stay in the IRT you already trust. ClinPrecision consumes its assignments and keeps blinded data blinded.

How the AI works

The system proposes. A person approves.

During study build, the platform suggests eligibility criteria, CDISC mappings and cross-form checks. Every suggestion carries a score you can take apart, and the score decides who has to look at it.

AUTO_APPLIED

Score of 0.92 or higher. Applied, logged, and reversible.

PENDING_REVIEW

Below 0.92. Waits for a named reviewer to accept or reject it.

UNMAPPED

Nothing to bind to. A person maps it by hand.

"Date of onset"→AE.AESTDTC
0.951AUTO_APPLIED
0.920.00.51.0
context ×0.25
semantic ×0.20
assessability ×0.20
dependencies ×0.15
history ×0.10
catalogue ×0.10

score = Σ weight × part · example values

Traceability

Pull any regulation. See every part of the platform it touches.

Our own documentation is a graph: each rule links to the work it governs, the people who do it, and the part of the platform that records it. Inspectors ask for exactly this chain.

  1. Regulation21 CFR Part 11
  2. Stream & capabilityGovernance & AccessAdministration
  3. ProcessActivate a SiteGrant Emergency AccessOnboard a User & Assign Study RolesPrepare for an Inspection+1 more
  4. Who does itInspector / AuditorOrganization ManagerQA / ComplianceSecurity / Compliance Officer+3 more
  5. Where it livesCTMS Site ActivationCTMS Site ManagementeTMF Inspection ReadinessQMS Vendor Oversight+3 more
21 CFR Part 11 reaches 2 streams & capabilities · 5 processes · 7 roles · 7 platform areasTrace any rule →
By job

What changes for the people running the trial.

assemble the database

Study build

Review a proposed database, eCRFs and edit checks derived from the protocol, then approve.

eyeball every discrepancy

Data management

Validation runs continuously. People judge the residuals that need judgement.

travel and spreadsheets

Monitoring

Sites ranked by risk, so the CRA knows where to look first and why.

"where do I file this?"

Documents & quality

Filed on arrival, with the gap, the deviation and the suggested fix in one place.

TIMECAPABILITYTHE WINDOWDigitise the hand-off · c. 2005paper → browser → workflowAI-native
Leaders on the old curve keep improving the old answer
Why now

Three conditions arrived at the same time.

Models can be trusted to propose

Clinical reasoning and protocol reading are now good enough to draft, as long as a person reviews.

Regulators are converging

FDA, EMA and ICH guidance accommodates AI-supported work when the audit trail and explanation come first.

Sponsors are out of patience

Faster start-up, cheaper monitoring and fewer queries are the levers they need, and the old stack can't pull them.

Team
“I've seen how this stack is built from the inside, and why it can't carry the next decade of trial designs.”
Narendra Nath SarkarFounder & CEO, Novatra AI · 20+ years of enterprise architecture in pharma, financial services and healthcare

Leadership

  • Narendra Nath SarkarFounder & CEO
    ParexelOraclePerceptive
  • G. GogadaCo-Founder & CTO
    MGH
  • Meena KaushikCo-Founder, Head of Product & Strategy
    ParexelMedidata
  • Mahua SarkarCo-Founder & Chief Marketing Officer

Advisory Board

  • Dr. Ramesh AdhikaryAdvisory Board

Bring a protocol. We'll show it running.

A working session on your own design: cohorts, visits, forms and the checks the platform would propose for it. We reply within 1–2 business days.

Emailinfo@novatra-ai.compartners@novatra-ai.com
Phone · Mon–Fri, 9 AM–6 PM CT1-469-238-1258
Designed for 21 CFR Part 11ICH E6(R3)GxP-ready architecture

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