AIIA Clinical Trials Dashboard - a real-time, cloud-based, GCP-compliant Clinical Trial Management System (CTMS) for Ayurveda research, with CDISC/FHIR-interoperable data, role-based KPIs, and integrated ethics, regulatory (CTRI / NDCT Rules 2019) and pharmacovigilance tracking.
Ministry of Ayush · Space Technology · Software
The sponsor has removed the data barrier and told you exactly what to build and in what order, but this is enterprise regulatory software with almost no visible surface, so take the staging advice and make the adverse event reporting clock your demo rather than the portfolio view.
Data: Clinical-trial data is sensitive personal data, so development should use synthetic or de-identified datasets. Representative standards and public sources: Clinical Trials Registry – India public trial records (ctri.nic.in) and CDISC standards and controlled terminology covering CDASH, SDTM, ADaM and Define-XML (cdisc.org).
What it actually is
The All India Institute of Ayurveda runs a growing number of clinical trials and also coordinates national safety reporting for Ayurvedic medicines, but tracks all of it in spreadsheets. Nobody can see in one place which study is behind on recruitment, which ethics approval is expiring, or whether a serious side effect was reported to the regulator in time. The ask is a single monitoring system that covers the whole portfolio and the safety reporting together.
What to build
A trial management platform tracking each study across the lifecycle stages the statement names — protocol and ethics approval, CTRI registration, site activation, screening, enrolment against target, protocol deviations, data query status, milestones and close-out — surfaced as configurable KPIs with alerts for the specific triggers listed such as enrolment lag and overdue monitoring visits, plus an integrated pharmacovigilance module capturing adverse and serious adverse events, coding them to MedDRA and WHODrug and routing them against regulatory reporting clocks with aggregate signals to the safety monitoring board, all on CDISC-aligned data models with FHIR R4 interoperability, an immutable time-stamped audit trail, seven distinct role-based views and submission-ready SDTM and ADaM export.
Smallest thing that wins the room
Log a serious adverse event as a site coordinator and show the regulatory reporting clock start, the event auto-code to MedDRA, the safety board dashboard update, and the audit trail record who did what and when.
How crowded this one gets
A guess, projected from the 2025 statements — the last year where both the submission counts and the winners were published.
Quieter than 67% of the 226 · #75 of 226 by expected field
A normal-sized field. Your idea has to be good, not miraculous.
Why: central ministry statements sat below the average.
This is a guess, not a fact
Nobody has published 2026’s numbers yet. This is an analysed estimate from last year’s pattern, so please do not take it as the truth — check the live counter on the SIH portal before you decide anything. The range covers the middle half of likely outcomes, so one statement in two lands outside it. Entry closes at 500 ideas per statement, so no range goes past that — a statement that reaches the cap fills and shuts rather than drawing an unlimited crowd. The model reads only three things a team can see before choosing — software or hardware, the theme, and what kind of body posted it — and those explain about a quarter of the variation in last year’s field sizes (R² 0.25 on held-out statements). Trust the band more than the number, and the ordering more than either. It cannot see how good your idea is, which is the part that actually decides it.
The scores
The number is the shorthand. The line under it is the reason.
Acceptance potential
3/5Zero data risk, an unambiguous specification and a very thin field are all real advantages, but the scope is enterprise-scale and the parts that actually distinguish a serious submission — correct SDTM mapping and MedDRA coding — require specialist regulatory knowledge that most student teams do not have and will therefore fake.
Feasibility
4/5The statement removes the one thing that would otherwise block this by explicitly directing you to synthetic and de-identified data, and everything you must conform to is public — CTRI records are open, the CDISC standards and controlled terminology are published, and the FHIR R4 specification is freely available.
Innovation scope
2/5The lifecycle stages, the KPIs, the alert triggers, the data standards, the coding dictionaries, the seven roles and the export formats are all specified, so this is a conformance exercise where the correct answer is defined externally by regulation and standard.
Clarity
5/5Exceptionally precise — it names every governing framework from GCP-ASU and the NDCT Rules to the DPDP Act and its 2025 Rules, every data standard including Define-XML, both coding dictionaries, all seven access roles, and even the four criteria the solution will be evaluated on.
Effort
MassiveA study lifecycle tracker, a KPI and alerting engine, a full pharmacovigilance module with dictionary coding and regulatory timers, CDISC-conformant data models with submission export, FHIR and ABDM interoperability, consent management and an immutable audit trail is enterprise clinical software that vendors build over years.
Demo-ability
MediumThe adverse event routing against a regulatory clock is a genuinely good moment and the audit trail is tangible, but the bulk of the product is a portfolio dashboard, and enterprise compliance software rarely produces anything a judge feels rather than merely follows.
In its favour
- Green flag: The statement tells you to use synthetic and de-identified data, which removes the ethics and access barrier that normally makes clinical software statements impossible for students
- Green flag: It also tells you the build can be staged and names the order, so a core study-tracking and KPI MVP done properly is explicitly a valid submission rather than a partial one
- Green flag: Correctness is defined by published standards and regulations rather than by your judgement, so requirement ambiguity is essentially zero
- Green flag: The Space Technology theme label buries a clinical research platform where no MedTech team will look for it
Against it
- Red flag: CDISC SDTM mapping is a specialist skill with a genuine learning curve, and a submission claiming submission-ready datasets that would not actually pass a validator is the exact claim a regulatory-literate judge will test
- Red flag: The scope taken whole is an enterprise CTMS plus a pharmacovigilance system plus a standards conformance layer — take the statement's own staging advice or you will ship nine shallow modules
- Red flag: There is no visible product moment here beyond the adverse event clock, so the demo needs deliberate staging or it becomes a tour of dashboards
- Red flag: MedDRA is a licensed dictionary with access restrictions, so plan how you will demonstrate coding without it rather than discovering the licensing question during your presentation
What you will be writing
- CDISC SDTM and ADaM data models with Define-XML export
- HL7 FHIR R4 resources for ABDM interoperability
- MedDRA and WHODrug coding integration
- event-sourced immutable ALCOA+ audit trail
- role-scoped dashboards with configurable KPI alerting
- DPDP-aligned consent and encryption layer
- Clinical research operations
- Pharmacovigilance
- Health data standards
Prior art to read before you start
clinical trial lifecycle and KPI monitoring · adverse event capture and regulatory timeline tracking · standards-conformant health data interoperability
Analysed by Claude Opus. Every score above is a judgment call with its reasoning attached — kindly cross-check this against the official statement on the SIH portal before your team commits to it.