Real-World Evidence and Clinical Trial Platforms in India: A Practical Guide for Pharma and CRO Teams

Start with the research question, not the product demo

Define what the team is trying to answer before comparing features. A disease registry, drug-utilisation study, retrospective chart review and interventional clinical trial can all involve longitudinal health data, but they do not automatically follow the same governance or regulatory route. The protocol, data sources, participant interaction, intended use of the results and applicable approvals determine the route.

Ask for a written workflow map: the scientific question, target population, inclusion and exclusion logic, endpoints or operational measures, source systems, responsible roles and planned outputs. This gives scientific, clinical, data-management and quality teams a common basis for judging whether the platform fits the work.

Separate real-world data from real-world evidence

Real-world data can include appropriately authorised records from care delivery, registries, claims, laboratory systems, patient-reported information or connected devices. Real-world evidence is the conclusion produced when fit-for-purpose data are analysed using an appropriate study design and method. A platform can help organise data and document methods; it cannot make an incomplete dataset scientifically fit or turn an automated output into an evidence conclusion.

For each source, document where it came from, what period it covers, how identity matching was handled, what is missing, which transformations were applied and who can inspect the original context. This matters as much in a Chennai hospital collaboration as in a multi-site national programme: local record formats and care pathways can materially affect how a cohort is interpreted.

• Keep the original source and relevant dates available to authorised reviewers
• Version cohort logic, code lists, transformations and analysis definitions
• Record exclusions, missingness and data-quality checks rather than silently filling gaps
• Make clinical, statistical and methodological review explicit before a result is shared

Map trial governance before adding participant workflows

Where a proposed use case is an applicable clinical trial, the New Drugs and Clinical Trials Rules, 2019 set conditions that include ethics approval at each site and registration with the Clinical Trials Registry–India before the first subject is enrolled. The CTRI also requires ethics approval for registration and states that registration is prospective. These are governance responsibilities of the study team, sponsor and investigators—not software features supplied by Doxyte or another platform.

A practical platform review should therefore ask how approved protocol versions, site roles, participant-facing materials, consent or withdrawal events, safety escalation pathways and deviations will be recorded and reviewed. Do not assume that an electronic diary, e-consent flow or registry automatically makes every study a regulated clinical trial, or that a tool itself provides approval.

Test candidate cohorts without automating eligibility or enrolment

Cohort tools can translate approved criteria into repeatable searches across permitted data, helping teams identify records that may merit review. That is different from determining eligibility. Ambiguous criteria, incomplete records, contraindications and evolving protocol context require authorised investigator and study-team review.

Run a controlled test with representative, authorised data. Compare the candidate set with manual review, record false inclusions and exclusions, and check whether reviewers can see the exact source and criterion behind each match. Do not use a model output to independently contact, consent, enrol, treat or exclude a participant.

Keep the validated system of record in view

A useful layer should connect to the clinical trial management system, electronic data capture system and approved source systems without silently replacing them. Agree which system is the record of truth for protocol, participant status, visit data, queries, audit records and safety information. Define the interface, permitted fields, timing, reconciliation process, failed-message handling and access controls before launch.

Doxyte’s Nalan for Pharma is a solution programme in development, intended for governed, source-aware research context and reviewable workflows. It should be evaluated use case by use case. It does not replace investigators, ethics oversight, biostatistical review, validated trial systems or regulatory decision-making.

A procurement checklist for Indian pharma and CRO teams

Before selecting a platform, ask the supplier to demonstrate the exact workflow with your roles, sources and study boundaries—not a generic dashboard. Request clear answers on data purpose, access, provenance, configuration, validation evidence, model limitations, review controls, incident handling, exports, portability and exit arrangements.

• Can the team reproduce a cohort, timeline or analysis view from its saved definitions?
• Can reviewers trace a field or recommendation back to an approved source and version?
• Are user roles, approvals, exceptions and changes recorded in an auditable way?
• Does the workflow preserve investigator, ethics, clinical and statistical accountability?
• Can data and documented logic be exported or reconciled with the existing CTMS, EDC and source systems?
• Are planned capabilities clearly separated from capabilities available for the specific programme?