How to Choose a Clinical Biometrics CRO for a Phase 2 Trial.

“Biometrics” bundles three related disciplines. A provider may offer all three as an integrated team, or only one or two. Know which you are buying, and who owns each hand-off.

ICH E9, written mainly for later-phase trials but widely applied earlier, expects responsibility for a trial’s statistical aspects to rest with an appropriately qualified and experienced trial statistician who is involved from the protocol onward ^[1]. In practice, the most consequential biometrics decisions in a Phase 2 study are made before the first patient is dosed.

Most emerging sponsors choose between three models. The right one depends less on price than on how much statistical leadership you have in-house and how many vendors you can realistically oversee.

Whatever the model, ICH E6(R3) is explicit that the sponsor keeps ultimate responsibility for activities transferred to a service provider, should assess the provider’s suitability before selection, and should oversee important transferred activities, including any the provider subcontracts ^[3]. Under a US IND, any transfer of sponsor obligations to a CRO must be described in writing, and obligations not described are deemed not transferred ^[12]. Choose a model you can actually oversee.

In the directory you can filter clinical biometrics providers by documented engagement model, then confirm how each model works in practice.

• The clinical question is still being refined. The E9(R1) addendum expects the estimand, including how intercurrent events such as treatment discontinuation or rescue medication are handled, to be defined at the design stage ^[2]. Involve the provider’s statistician in protocol development, not only in the SAP.
• Interim analyses and adaptations are common. Dose-ranging and proof-of-concept studies often include interim looks, futility rules or adaptive elements. These need unblinded statistical support, firewalled from the study team ^[1], and they change the budget.
• The data will outlive the study. Phase 2 datasets are typically pooled or re-analyzed for Phase 3 planning and integrated summaries. Building to CDISC standards from the start avoids a later legacy conversion, which the FDA conformance guide treats as a distinct and documented activity ^[5].
• Data comes from many sources. Central and specialty labs, bioanalytical PK data, ECG, imaging and electronic patient-reported outcomes all need transfer specifications and reconciliation. See the bioanalytical laboratory guide for the PK data hand-off.

Standardized study data are a regulatory requirement for many FDA submissions, set out in FDA’s guidance on providing standardized study data in electronic format and the technical specifications it incorporates by reference ^[4]. The requirement covers NDAs, ANDAs and certain BLAs and commercial INDs, including later amendments, and applies according to the study’s start date (the first participant’s informed consent), so the standards decision belongs at study planning; submissions under noncommercial INDs, such as investigator-sponsored INDs, are exempt ^[4]. CDISC states that SDTM, ADaM and Define-XML are required for submissions to FDA and Japan’s PMDA ^{[7] [8] [10]}.

Version requirements change, so do not rely on a provider’s general claim of “CDISC compliance”. Ask which standard and implementation-guide versions they will deliver, and how those align with the versions FDA’s Data Standards Catalog lists as supported or required for studies with your study’s start date ^{[6] [4]}.

Data management quality is decided by design: what the eCRF collects, which edit checks run, and how external data are reconciled. ICH E6(R3) sets data governance expectations across the data life cycle, including audit trails, data corrections, transfers and finalization of datasets before analysis, and expects computerized systems to be validated on a risk basis before use ^[3].

Electronic records kept to meet FDA record-keeping requirements (predicate rules) fall under 21 CFR Part 11, which requires controls including system validation, secure computer-generated audit trails and limited access ^[11]; FDA recommends a documented, risk-based approach to validation and audit trails ^[13]. FDA’s 2024 question-and-answer guidance on electronic systems in clinical investigations lists what to assess before relying on an IT service provider, such as an EDC or cloud host: oversight access, validation, the ability to produce complete copies for the retention period, backup and recovery, access controls, audit trails and data confidentiality ^[13].

The MHRA’s GxP data integrity guidance recommends that any contract or technical agreement with a third party define data ownership, governance and accessibility, and that vendor assurance include a review of data governance ^[14]. Put those terms in the contract, not only the quality agreement.

• Named people, not a bench. Ask for the lead statistician, lead programmer and data manager by name, with their recent studies in your indication or design type, and a contractual process for replacing them.
• Relevant designs. Experience with your endpoint type (time-to-event, repeated measures, composite or patient-reported endpoints) matters more than a generic therapeutic-area list. Ask for anonymized SAP shells or mock TLFs from comparable studies.
• Regulatory interaction. If an end-of-Phase 2 meeting will follow, ask who has prepared statistical briefing material or responded to agency statistical questions.
• Continuity. Ask about staff turnover and how knowledge transfers if people change mid-study.

Biometrics work is front- and back-loaded. Capacity problems usually appear at database build before first patient in, and in the weeks around database lock. Ask each provider to commit to dates for these milestones and to say what they are currently delivering in the same window.

Biometrics proposals are rarely comparable as received. Before comparing totals, give every provider the same assumptions, or extract theirs into a common table.

Ask for unit rates alongside the total, so that later changes are priced transparently. Compare named team seniority, not only blended rates.

The items below are commonly excluded or capped in biometrics proposals. None is wrong to exclude, but each should be an explicit decision rather than a surprise.

• Protocol amendments and the resulting eCRF, SAP and TLF changes
• Additional or post hoc analyses requested after topline results
• Extra data transfers, cuts or interim snapshots
• Unblinded statistician and programmer for DMC or interim analyses
• Integrated analyses across studies and integrated summaries of safety and efficacy
• Clinical study report writing, as distinct from statistical outputs
• Responses to regulatory statistical questions
• Conversion of legacy or non-CDISC data
• EDC licences, hosting fees and archiving after study close

Score each provider from 1 (weak) to 5 (strong) on each criterion, using evidence from proposals, team interviews, sample outputs and references. The weights below are a starting point for a typical Phase 2 study; adjust them to your situation before you see the proposals, not after.

• The proposal names no statistician, or the person in the bid defense will not work on the study
• “CDISC compliant” with no named standards, versions or reviewer’s guides
• A total price with no unit assumptions
• Unclear answers about subcontracting or offshore delivery
• Reluctance to share SOPs, metrics or a summary of audit and inspection history during selection
• No plan for external data reconciliation
• A timeline that puts EDC go-live after first patient in

Use the clinical biometrics directory to find providers whose public sources document the services you need, filter by stage and engagement model, and compare up to four side by side. Then send every shortlisted provider the same scope worksheet and questions. If you want help running that process, ArgusBio can support it.