Compare the Best Biometrics Vendors for Clinical Trials

Who this guide is for

This guide is for clinical operations leads, heads of clinical development and biotech founders who need statistical design, statistical programming or analysis support for a clinical trial and do not have a full in-house biometrics function. It is also for teams who already have a statistician but need extra programming capacity, an independent statistician for a data monitoring committee, or help preparing standardised datasets for a regulatory submission.

If you are searching for the best biometrics vendors for clinical trials, treat the vendor cards and the table on this page as a starting point, not a verdict. They show which biometrics and data science vendors are listed and how each profile describes its focus; they cannot tell you whether a team has designed a study like yours, or how it handles a database lock under time pressure. Use the criteria below to decide what to ask before you commit.

What a biometrics vendor does — and when you need one

Biometrics is the umbrella term for the quantitative functions in a clinical trial. It usually covers three disciplines. Biostatistics designs the study and the analysis: sample size, randomisation, endpoints, the estimand, the statistical analysis plan and the interpretation of results. Statistical programming builds the analysis datasets and produces the tables, listings and figures that feed the clinical study report. Clinical data management designs the data collection, cleans the data and delivers a locked database; some sponsors buy it with biometrics, others buy it separately.

The category also now includes data science and real-world evidence providers, who analyse data generated outside the trial, for example to support external comparators, feasibility work or health technology assessment. These are related but different services, and the vendor records on this page include both kinds.

Typical trigger points are a protocol that needs a sample size justification, an adaptive or complex design, an interim analysis or data monitoring committee, a study approaching database lock without enough programming capacity, a submission that needs standardised datasets, or the departure of an in-house statistician part way through a programme.

How to evaluate a biometrics vendor

Statistical design depth

Ask who will design your study and what designs they have worked on. A group sequential design, a Bayesian adaptive design and a simple fixed-sample comparison need different skills and different simulation work. The ICH E9 guideline on statistical principles and the ICH E20 guideline on adaptive designs set expectations regulators will apply, so ask the vendor to explain how its proposed design would be defended in a scientific advice meeting.

Estimands and analysis planning

The ICH E9(R1) addendum requires a clear description of the treatment effect being estimated, including how intercurrent events are handled. A capable statistician will raise estimand questions during protocol drafting, not after the data arrive. Ask for an example statistical analysis plan, redacted if necessary, and look at how clearly it states the primary estimand, sensitivity analyses and missing data handling.

Programming standards and validation

Ask how programs are validated. Double programming, where a second programmer independently reproduces key outputs, is common for primary and key secondary results; lighter review may be used elsewhere. Ask which outputs get which level of validation, which software is used and how version control and audit trails are kept.

CDISC and submission readiness

If your study could support a marketing application, ask for evidence of SDTM and ADaM packages, Define-XML and reviewer guides the vendor has delivered, and how it handles conformance checks. Retrofitting standards at the end of a programme is slow and expensive, so agree the standards strategy at the start.

Interim analyses and blinding

Interim analyses for data monitoring committees need an unblinded team separated from the study team. Ask how the vendor firewalls unblinded statisticians and programmers, how access to randomisation codes is controlled, and whether it has supported independent data monitoring committees before.

Integration with data management and other vendors

If data management sits with another vendor, the hand-off is where timelines slip. Ask how the vendor receives data, how often it runs test transfers, how it raises data issues back to data management, and who owns reconciliation of external data such as laboratory results.

Team continuity and capacity

Ask for the named lead statistician and lead programmer, how much of their time is allocated, and how cover works during absence. A strong proposal team that is replaced after signature is a common source of disappointment.

Biometrics vendors at a glance

The table below sets out the biometrics and data science vendors tracked for this page side by side, so you can see how each profile describes its service model, footprint and study coverage before you open individual pages.

The fields come from each vendor's Clinical Vendor Compare profile. Several records describe their service model only in general terms or have not yet been fully completed, and some list no study phases at all. A blank or general field means the record is silent, not that the vendor lacks the capability. Use the profiles to narrow the field, then confirm design, programming and standards experience directly.

Vendor profiles

CTI (Biometrics)

CTI's biometrics record lists a vendor headquartered in the United States with a global footprint, covering Phase I to Phase III studies of small and medium scale in oncology, rare diseases, CNS and cardiovascular medicine. Its stated best fit is sponsors who want biostatistics consulting alongside data management, and its profile describes a consulting approach. Where to probe: the record itself notes a mid-size organisation with limited global reach, so check resourcing and time-zone coverage if your study spans several regions.

Lambda (Biometrics)

Lambda's record describes a CRO headquartered in India providing biostatistics, data management and clinical trial services, with Phase I to Phase IV coverage in oncology, infectious disease, diabetes and cardiovascular medicine. Its profile lists CDISC standards among its strengths and positions it for cost-conscious sponsors buying delivery from India. Where to probe: ask how the team overlaps with your working hours, who reviews outputs before release and how communication is managed across sites.

Aetion

Aetion is listed as a technology vendor offering a software platform for real-world evidence, with a stated focus on causal inference, regulatory real-world evidence submissions, health technology assessment evidence and emulation of randomised trials. Its own record notes that it is an analytics platform that does not collect data and depends on external data partnerships. Where to probe: Aetion fits evidence questions around a trial, such as external comparators, rather than the statistical design and analysis of the trial itself.

Algorics Biostatistics

Algorics' record lists a biometrics and data science provider with a global footprint and a generalist therapeutic remit, covering Phase I to Phase IV. Its stated best fit is sponsors who need outsourced data science, statistics or programming capacity, and its profile highlights statistical rigour, programming depth and data quality. Where to probe: its record flags integration with sponsor standards, data flows and governance as an area to manage, so ask how it adopts your standards and conventions.

Berry Consultants

Berry Consultants' record describes a biometrics and data science provider with a global footprint whose public positioning centres on adaptive trial design, Bayesian analysis and simulation. That makes it relevant when the design itself is the hard problem, for example a platform trial or a study with response-adaptive randomisation. Where to probe: ask how the team works with your data management and programming vendors, since its record notes integration with sponsor and CRO systems as a consideration.

BioStat Solutions

BioStat Solutions' record describes biostatistics consulting for clinical trials with a global footprint and a generalist therapeutic remit. Its stated best fit is sponsors who need statistical analysis plan development. The profile does not yet list service model detail, study phases or trial scale. Where to probe: ask for redacted analysis plans and confirm whether the team can also program and run the analysis or would hand that work to another provider.

BioStata

BioStata is listed as a biometrics and data science provider with a global footprint and a generalist remit, covering Phase I to Phase IV studies. Its stated best fit is programmes needing statistics, programming, data management or analytics, which is a broad description rather than a specialism. Where to probe: ask which of those services it delivers most often, the size of the team that would work on your study, and examples of recent deliverables.

Biotech (Data Science)

This record describes a clinical data science and machine learning provider for drug development, with a global footprint and a generalist remit. Its stated best fit is sponsors wanting machine-learning-driven clinical insights. The profile does not yet list service model, study phases or trial scale. Where to probe: ask how its models are validated, how outputs would be used in decision-making, and how it documents methods so they can withstand regulatory or internal scrutiny.

Certara Biometrics

Certara Biometrics is listed as a biometrics and data science provider with a global footprint, covering Phase I to Phase IV studies with a focus on statistics, programming, data management and analytics. Its record notes that it is not aimed at sponsors who want only operational monitoring. Where to probe: ask how its biometrics work connects with any modelling and simulation support you need, and who would lead your study day to day.

Clindata Insight

Clindata Insight's record describes clinical data management and biostatistics for drug development, with a global footprint and a generalist remit. Its stated best fit is sponsors wanting integrated data management and statistics. The profile does not yet list service model detail, phases or trial scale. Where to probe: ask how the integrated team separates cleaning decisions from analysis decisions, and which EDC systems it works in.

Engagement and pricing models

Biometrics is usually bought in one of three ways. Unit-based quotes price defined deliverables, such as an analysis plan, a set of analysis datasets or a package of tables, listings and figures; they suit studies with a stable design. FTE or functional service models place named statisticians and programmers in your team for a period, which suits programmes with several studies or frequent change. Full-service bundles include biometrics inside a wider CRO contract alongside monitoring and data management.

The main cost drivers are the number and complexity of outputs, interim analyses and data monitoring committee support, simulation work for complex designs, data standards and submission packages, and rework after protocol amendments. Unit pricing is predictable but can generate change orders when outputs multiply; FTE models are flexible but need active oversight. Whichever you choose, define what triggers a change order and how output counts are agreed.

Questions to put in your RFP

• Who is the named lead statistician and lead programmer, and what share of their time will our study receive?
• Which comparable designs have you worked on, and can you share a redacted statistical analysis plan?
• How do you define estimands and handle intercurrent events under ICH E9(R1)?
• Which outputs are double programmed, and how is the rest validated?
• Can you deliver SDTM, ADaM and Define-XML packages, and how do you check conformance?
• How do you separate unblinded statisticians and programmers for interim analyses?
• How will you receive data from our data management vendor, and how often will you run test transfers?
• What simulation work do you propose for the design, and how is it documented?
• Which software and version control do you use, and how are audit trails kept?
• What is included in the quote, and what triggers a change order?
• How do you protect personal data under GDPR when data move between vendors and regions?

Due-diligence red flags

• No named statistician at proposal stage, or senior names that appear only in the bid defence.
• Validation described only as review, with no independent programming for key results.
• Vague answers on estimands, multiplicity or missing data handling.
• No examples of submission-ready standardised datasets when your study may support a marketing application.
• No clear firewall for unblinded work on studies with interim analyses.
• Quotes that are silent on interim analyses, output counts or amendment rework.
• Reliance on a single individual for a whole programme with no backup.
• Machine-learning or real-world evidence claims that cannot be explained in methodological terms.

Shortlist on Clinical Vendor Compare

Start in the vendor directory and filter for biometrics and data science to see every listed provider. Open profiles to check stated focus, then place a few side by side on the compare page to separate design specialists from programming capacity providers and real-world evidence platforms. If your study is a pivotal trial, read the guide to biometrics vendors for Phase III; if you also need data cleaning and database lock, see the guide to data management vendors. When your scope is clear, use the sponsor RFP tool to brief vendors on design, outputs and timelines. If you have worked with any of these vendors, please write a review: published reviews are what give the next buyer an evidence base.