Clinical and regulatory data, ready when the submission is due.
We build the data pipelines behind clinical trials and regulatory submissions, validated applications that pass quality review, and practical AI for research teams. We also supply engineers who know GxP work.
Four problems we hear from life sciences teams
Each one slows the path from data to decision.
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Clinical trial data is slow to collect and clean
Site, lab and patient-reported data arrive in different formats and at different times. We build pipelines that bring them into one place with automated checks. Data managers spend less time chasing queries.
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Regulatory submissions and safety reporting are manual
Teams copy figures between systems to build submissions and safety cases. We automate data assembly with traceable steps. Reports come together faster, and every figure traces back to its source.
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Research and real-world data sit in separate systems
Discovery, clinical and real-world data are hard to use together. We connect them in one governed data layer, with access controls that protect patient privacy.
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Validation and quality paperwork slow every release
Validation evidence is often assembled at the end, which delays releases. We produce requirements, test evidence and traceability as the work happens, and quality review starts with a complete package.
What we build for life sciences teams
Six capabilities, each connected to the clinical, quality and research systems you run today.
- Clinical data pipelines
- Site, lab and patient-reported data in one place, with automated checks and clear audit trails.
- Regulatory and safety data
- Traceable data assembly for submissions and safety reporting.
- Validated, GxP-ready applications
- Applications delivered with validation evidence built in, ready for quality review.
- A governed research data layer
- Discovery, clinical and real-world data joined, with access controls for patient privacy.
- AI for research and operations
- Practical starting points for AI, with clear rules for data use and human review of every output.
- Engineering talent
- Engineers and analysts who understand validated environments, placed on your teams quickly.
Who we work with
The tools are similar. The scope changes with your pipeline and your regulatory load.
- Pharma companiesClinical, regulatory and safety data at portfolio scale.
- Biotech companiesRight-sized data platforms that grow from first trial to submission.
- Clinical research organizationsData pipelines and reporting that work across sponsors and studies.
How a life sciences engagement runs
Four phases, with validation planned from the first week.
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Assess
We review your data flows, systems, validation approach and the reports that take longest to produce.
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Design
We plan one connected architecture with timeline, team and cost, and agree the validation plan with your quality team.
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Build and integrate
We build the pipelines, applications and models, producing test evidence and traceability as we go.
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Improve
After go-live we monitor, tune and hand over runbooks and validation records your teams can own.
Why life sciences teams work with us
In regulated science, every step needs a record.
- Quality built in
- We produce requirements, test evidence and traceability during delivery.
- Patient data handled with care
- We design access controls, privacy and data governance before we build.
- A certified diverse supplier
- Infinity Tech Group is certified women- and minority-owned, which counts toward supplier diversity goals.
From our founder
Kamlesh Ranka founded Infinity Tech Group in 1999 to connect new technology with measurable business outcomes. He has led its client work for 27 years.
Talk to us about your clinical and regulatory data
A 30-minute call with a data engineering specialist. We will look at your trial, submission and quality workflows, and you leave with clear next steps.