Clinical Research SaaS

Hello Sophie
I am willing to work with you and partner up in creating an MVP, for the purpose of clinical trials.
We can build your Clinical Research SaaS MVP, focusing on a lean, compliant, and functional initial release. Given the highly regulated environment (SOC2, GDPR, HIPAA, GCP), our approach prioritizes security and compliance from day one, which inherently impacts the scope and cost.

For the MVP, we would concentrate on:
• Open-Source Data Parsing: Developing robust mechanisms to ingest and parse specified open-source clinical trial data.
• Dashboard Presentation: Creating intuitive dashboards to visualize this data and answer key questions, as defined by your initial requirements.
• Foundational Security & Compliance: Implementing a secure architecture with necessary access controls, audit trails, and data encryption to lay the groundwork for SOC2, GDPR, HIPAA, and GCP compliance. This includes careful selection of cloud infrastructure and development practices.
• Scalable Architecture: Designing the MVP with future multi-module enterprise expansion in mind, ensuring the core is robust and extensible.
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Bootstrapping an enterprise SaaS in a regulated space like clinical research means every dollar counts. While a basic HIPAA-compliant MVP can range from $35,000 to $65,000, multi-compliance requirements (SOC2, GDPR, GCP) and enterprise features typically push this into the $150,000 - $400,000 range for a production-ready MVP. This is not a small prototype; it's a foundational, secure platform.

Regarding your offer for a technical co-founder title with equity, I am open to discussing this further for the right long-term partnership, as it aligns with a shared commitment to quality and success.

Two critical questions before a more precise estimate:
1.
What are the specific open-source data sources (e.g., ClinicalTrials.gov, PubMed) and the exact key questions the dashboards need to answer for the MVP?
2.
Which compliance certifications (e.g., HIPAA, SOC2 Type 1, GDPR) are absolute must-haves for the initial MVP launch, and which can be phased in during subsequent development stages?
I'll make sure that I also reach you at the website provided.

Hello! Having studied your project with great interest, I am ready to start working on it. Let's discuss the details to achieve the best result.

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WE can approach this as a paid discovery and MVP architecture phase first - 2 to 3 weeks for data map, security model, system design, backlog, and a working dashboard prototype.
for the full MVP, I would expect a phased build rather than one large blind estimate, especially with SOC2, GDPR, HIPAA, and GCP in scope.

we have relevant experience in regulated and data-heavy systems.
> https://business.ingello.com/lita - healthtech platform work with medical process logic.
> https://business.ingello.com/rapport - healthcare adjacent product with structured workflows and user roles.
> https://business.ingello.com/fractal - AI and automation architecture, useful for the question-answering layer over open-source data.

main Ingello page for FLH - https://systems-fl.ingello.com
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Ну тут скорее так - I would make the MVP boring in the best possible way.
secure tenant structure, audit logs, role permissions, source-data ingestion, normalized storage, dashboards, and only then the AI question layer on top.
that keeps cost control realistic and avoids building a pretty demo that cannot survive compliance review =)

from your side, we would need sample open-source datasets, expected user roles, 5 to 10 key dashboard quesions, and your preferred cloud if already chosen.

2 quick questions.
> should the MVP include only public/open-source data, or also client-uploaded trial documents later?
> do you need formal compliance readiness artifacts in phase one, or only architecture built in a SOC2/HIPAA-ready way?

we can keep all communication here under platform rules, so nobody gets banished by the moderation gods.
В целом норм, the project is serious but absolutely buildable in stages.

MVP scope is clear: ingest open-source clinical datasets, normalize into a compliant data model, surface via dashboards with a query/Q&A layer. I'd architect on a HIPAA/SOC2-ready stack (encrypted at rest + in transit, audit logs, RBAC, BAA-ready infra) — same controls I apply on regulated web platforms.

For MVP: data pipeline, role-based dashboard, basic AI Q&A on top of the parsed data. Roughly 6–8 weeks.

Co-founder/equity structure works for me if the scope and vesting terms are reasonable.

What open-source datasets are you targeting first — ClinicalTrials.gov, OpenFDA, something else?