Nalan for Pharma · Life-sciences intelligence
Nalan for Pharma is being designed to connect governed longitudinal data, reproducible cohort logic and participant-centred trial workflows. The aim is to give life sciences teams clearer evidence without obscuring provenance or scientific responsibility.
Solution programme in developmentCapabilities will be introduced through governed, use-case-specific programmes.
Answer first
Nalan for Pharma is Doxyte's planned artificial intelligence (AI) layer for pharmaceutical teams, researchers, contract research organisations (CROs) and clinical-trial operations. It is designed to support real-world evidence, cohort discovery, disease registries, drug-utilisation analysis and reviewable trial workflows using appropriately authorised, governed data. It does not replace investigators, ethics oversight, biostatistical review or regulatory decision-making.
From data to scientific review
Nalan can help authorised teams organise source-aware evidence and operational signals for qualified scientific review without presenting an automated analysis as a conclusion.
Designed around the workflow
Each capability begins as a defined use case with its own data, validation, permissions and review requirements. Release status is confirmed during discovery.
Create analysis-ready views from approved personal health record (PHR), electronic medical record (EMR), hospital, clinic, laboratory and wearable sources while preserving dates, provenance, missingness and study definitions.
Translate approved inclusion and exclusion criteria into reproducible searches across permitted data. Potential matches remain candidates for authorised review.
Support governed disease registries with longitudinal context, configurable measures and clear data-quality indicators.
Explore appropriately governed patterns in initiation, switching, persistence, adherence proxies and outcomes. Findings require qualified scientific interpretation.
Connected trial operations
Nalan can be designed around approved study workflows while existing clinical trial management systems (CTMS), electronic data capture (EDC) systems and other validated platforms remain the record of truth. Every agentic action is scoped, reviewable and governed by the protocol.
Prepare structured draft protocol modules, schedules of activities, visit logic and data requirements for expert review.
Support version-controlled e-consent, digital-consent and video-consent journeys with approved scripts and withdrawal capture.
Collect configured symptoms, questionnaires and daily diaries; provide reminders in supported languages; never act as emergency monitoring.
Run approved text or call workflows for scheduling, diary reminders and missed check-ins, escalating configured events to the study team.
Review recruitment, retention, completion, visit deviation, query burden and participant-reported trends according to role.
Complement existing CTMS, EDC and related trial systems through documented integrations instead of replacing the validated system of record.
A governed path to production
Document the scientific question, protocol purpose, population and governance plan.
Confirm access, consent requirements, data agreements and approved users.
Map approved sources, terminology, timelines, missingness and quality rules.
Configure cohort definitions, registry measures, endpoints or participant workflows.
Require investigator, clinical, statistical and operational review appropriate to the use case.
Version definitions and track provenance, quality, changes, exceptions and model performance.
Governance is a product capability
These boundaries guide product design and discovery. The final controls must be validated for the organisation, population, workflow and applicable obligations before production use.
Read Doxyte's security approach ↗Use data only for a documented, authorised scientific or operational purpose.
Apply de-identification, pseudonymisation and data minimisation where appropriate.
Preserve cohort logic, transformations, source lineage and version history.
AI suggestions and analyses require qualified investigator, clinical and statistical review.
Consent, withdrawal, ethics and safety-escalation obligations take priority over automation.
A model must not independently determine eligibility, enrol a participant or make a treatment decision.
Primary reference points
These official sources inform the direction of the experience. They do not constitute a certification, regulatory approval or a substitute for implementation-specific legal, clinical or scientific review.
Reference set reviewed 31 July 2026.Questions, answered plainly
It helps authorised research teams organise approved longitudinal health data into analysis-ready cohorts, measures and timelines while preserving source and methodological context.
Real-world data are routinely collected health and care data, such as information from electronic health records, claims, registries and digital health technologies. Real-world evidence is the clinical evidence produced by analysing fit-for-purpose real-world data using an appropriate study design.
It is designed to surface potential matches against approved criteria for authorised review. Investigators and study teams remain responsible for eligibility confirmation, outreach, consent and enrolment.
No. The planned trial layer is intended to connect with validated trial systems and improve selected workflows, not silently replace the system of record.
Planned workflows can present approved materials, capture version and acknowledgement events, support comprehension steps and document withdrawal. The exact process must follow the approved protocol and applicable requirements.
No. Nalan may help prepare drafts or organise evidence, but protocol approval, interpretation and regulatory decisions remain with qualified people and appropriate oversight bodies.
Nalan for Pharma is a solution programme in development. Doxyte can explore focused design-partner workflows and confirm the status of each capability before engagement.
Evidence starts with a well-defined question
Bring a specific evidence, cohort, registry or participant-operations problem. We will start with purpose, data and oversight.
Talk to the life-sciences team ↗