Majid Sohail Khan
All work
Healthtech·Clinical Trials & Real-World Evidence

OnTracka

High-compliance infrastructure for clinical trials and real-world patient monitoring — with an AI/RAG layer for researchers.

role · Backend Architect & Full-Stack Leadtimeline · 2019 — Present
Clinician PortaliOS AppAndroid AppStudy Onboarding(Confidential)
OnTracka screenshot

Overview

OnTracka is a purpose-built platform for investigator-led and sponsor-led clinical trials, supporting structured endpoint capture, longitudinal monitoring, and audit-ready workflows in regulated care environments. As backend architect and full-stack lead, I built the platform's core from the ground up.

// the brief
The problem

Trials still lean on paper diaries, spreadsheets, and email. Patient-reported data arrives late, incomplete, or recalled from memory; sites only discover who has fallen behind at the next visit; and side effects surface too slowly to act on. What does get collected is rarely structured enough to stand up to an audit.

The solution

OnTracka puts the whole study on one connected system. Participants report from their phone on the protocol's schedule, with wearable and health-app data syncing automatically. Clinicians watch adherence and safety signals across the cohort in real time and run telehealth visits without leaving the record. Every reading lands as structured, timestamped, audit-ready evidence — and a RAG layer lets researchers query the dataset in plain language.

What I did

  • Engineered the core backend architecture for secure collection and scheduling of complex patient health data across clinical research trials.
  • Built the web portal for doctors, research analysts, and administrators — real-time data visualization and patient-progress monitoring.
  • Implemented time-sensitive data pipelines that automate patient self-monitoring and real-world studies against strict clinical schedules.
  • Designed and shipped a retrieval-augmented generation (RAG) system on the OpenAI Agents SDK so researchers can securely query and analyze patient datasets through an AI interface.
// stack
Node.jsNestJSReactAI AgentsAgentic WorkflowsRAG / Vector StoresLangChain / LangGraphOpenAIRedux ToolkitAnt DesignPostgreSQLRedisCloudflareAWSREST APIsSaaS

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