Basket
One therapy across several indications, each cohort with its own enrolment and stopping rules.
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.
Each one holds part of the record. People reconcile the gaps by export and email, and some data falls through.
Data capture, operations, documents and quality read and write the same trial. No interfaces to validate, nothing to reconcile.
Screened patients route to the cohort their biomarkers match. A new cohort can open mid-study without a new build.
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
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.
One therapy across several indications, each cohort with its own enrolment and stopping rules.
One disease, a shared biomarker panel, and patients routed to the matching cohort.
Arms added and dropped mid-study at interim looks, under governed design changes.
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.
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.
Score of 0.92 or higher. Applied, logged, and reversible.
Below 0.92. Waits for a named reviewer to accept or reject it.
Nothing to bind to. A person maps it by hand.
score = Σ weight × part · example values
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.
Review a proposed database, eCRFs and edit checks derived from the protocol, then approve.
Validation runs continuously. People judge the residuals that need judgement.
Sites ranked by risk, so the CRA knows where to look first and why.
Filed on arrival, with the gap, the deviation and the suggested fix in one place.
Clinical reasoning and protocol reading are now good enough to draft, as long as a person reviews.
FDA, EMA and ICH guidance accommodates AI-supported work when the audit trail and explanation come first.
Faster start-up, cheaper monitoring and fewer queries are the levers they need, and the old stack can't pull them.
“I've seen how this stack is built from the inside, and why it can't carry the next decade of trial designs.”
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.