OpenBioCure Research Studio

From Evidence to Action.
Verified at Every Step.

Query 200M+ papers in natural language. Synthesize findings with specialized Bio-LLMs. Verify every claim against the original source. One continuous flow — from question to manuscript.

200M+ papers indexed30+ specialist agentsInline verification

From question to verified manuscript.

Watch how OpenBioCure connects evidence to action in one continuous flow.

Product Demo Video

Four tools. Zero continuity. Every switch costs you.

Today's research workflow is stitched together from disconnected tools. You search in one, synthesize in another, verify in a third, and write in a fourth. Every context switch introduces friction — and the risk of missed evidence.

10–15 min
Per claim to verify manually
4+ tools
Stitched together per workflow
0%
Inline traceability in existing tools

One continuous flow. Full traceability.

From your first query to your final manuscript — everything happens in one place, with every claim linked to its source.

1

Aggregate

Search 200M+ papers across PubMed, arXiv, ClinicalTrials.gov, Europe PMC, and NIH with natural language queries.

2

Synthesize

Bio-LLMs identify patterns, contradictions, and evidence gaps — with transparent reasoning chains.

3

Verify

Every claim is inline-cited. Click any citation to see the original source text in seconds.

4

Publish

Export publication-ready manuscripts with formatted citations and a full evidence audit trail.

Click to verify. Seconds, not minutes.

This is the moment that changes everything. Every claim OpenBioCure generates is linked directly to its source. Click any citation to see the original passage, the study metadata, and the full context.

No more copying DOIs into new tabs. No more guessing whether the AI invented a reference. The evidence is right there — inline, instant, verifiable.

Seconds
To verify any claim
100%
Inline citation coverage
Evidence Synthesis — Tumor Resistance

Recent studies indicate that acquired resistance to PD-1 inhibitors in non-small cell lung cancer may involve upregulation of alternative immune checkpoints, particularly TIM-3 and LAG-3 [Chen et al., 2024]. This suggests combination checkpoint strategies may overcome single-agent resistance in approximately 30–40% of previously progressing cases.

Source Verified

Chen, L. et al. (2024)
“Adaptive immune checkpoint resistance in NSCLC: mechanisms and therapeutic implications”
Journal of Clinical Oncology, 42(8), 1124–1138

From evidence to optimized practice.

Transform dense guidelines and scattered evidence into actionable protocols, optimized workflows, and audit-ready documentation.

Protocol Development

Convert vague guidelines into specific, actionable protocols with decision trees and structured workflows.

62%reduction in process errors

Technique Optimization

Synthesize comparative evidence across technique variables to identify evidence-backed optimizations.

67%reduction in adverse outcomes

Interaction Screening

Screen for evidence-based interactions and contraindications across complex scenarios.

45–70 minsaved per complex case

Multi-Standard Synthesis

Synthesize recommendations from multiple guidelines and standards bodies simultaneously.

15–23 minsaved per complex scenario

Compliance & Quality

Instant gap analysis against current standards with AI-drafted revisions and audit trails.

12h → 15mmonthly review time

Team Enablement

Create decision trees, quick-reference cards, and onboarding guides from synthesized evidence.

35:1ROI on protocol development

Early momentum. Real results.

Pilot results from real research and practice environments.

200M+
Research papers indexed across 5 major databases
30+
Specialist AI agents and connectors
62%
Process error reduction in pilot environments
35:1
ROI demonstrated in protocol optimization

Built for how researchers actually work.

From senior academics managing complex literature reviews to junior researchers learning to build defensible hypotheses.

“I need to trust the output — not spend an hour checking it.”

A university researcher in translational oncology juggles patient consultations, grant applications, and manuscript deadlines. She's tried multiple AI tools — each falls short on verifiability.

With OpenBioCure

Every claim is inline-cited and click-verifiable. Her workflow collapses from four separate tools into one continuous flow — from query to verified manuscript draft.

Verification time: 10–15 min per claim → seconds

“I can find papers. I can't connect evidence into a hypothesis.”

A medical student starting his first independent research project. There's a gap between reading papers and reasoning through them. Chat AI gives confident answers with no foundation.

With OpenBioCure

OpenBioCure shows what's supported, what's contradicted, and where the gaps are — with transparent reasoning that traces back to studies.

Hypothesis development: days of searching → one focused session

Grounded in the world's biomedical knowledge.

Every query searches across the most trusted and comprehensive biomedical databases available.

PubMed
36M+ biomedical citations
ClinicalTrials.gov
500K+ registered studies
Europe PMC
43M+ life science articles
arXiv
2.4M+ preprints
NIH Reporter
Funded research projects

The people and mission behind the platform.

OpenBioCure was built to close the gap between what we know and what we do — in research labs, in professional practice, and in the systems that turn evidence into better outcomes.

Vision

We envision a healthcare ecosystem where knowledge flows seamlessly, discoveries happen faster, and care is safer — powered by AI that is transparent, traceable, and collaborative.

Mission

Accelerate biomedical research and improve professional practice by combining advanced AI with evidence-based infrastructure. Empower researchers, professionals, and organizations to transform raw data into actionable knowledge that saves lives.

Meet the team.

A multidisciplinary team spanning AI, biomedical research, product design, and platform engineering.

Mahmoud Fattouh

Mahmoud Fattouh

Co-Founder & CEO

Leading OpenBioCure's vision and strategy. Focused on building the bridge between biomedical evidence and actionable outcomes at scale.

Mohammad Shehab

Mohammad Shehab

Co-Founder & CTO

Architecting the platform's AI infrastructure, evidence verification systems, and multi-source data pipelines that power OpenBioCure.

Nicolai Tufar

Nicolai Tufar

Co-Founder & VP Engineering

Leading engineering execution across the platform. Building scalable, reliable systems for biomedical research infrastructure.

Transparency First

Every output is traceable. Every reasoning chain is visible. We build trust through openness, not obscurity.

Collaboration by Default

We believe the biggest problems in biomedicine require cross-disciplinary collaboration and shared infrastructure.

Evidence Over Opinion

We don't generate answers — we surface evidence. The professional stays in control. The AI stays honest.

Stop stitching tools together.
Start doing research.

Join the pilot and experience one continuous flow — from your first query to a verified, publication-ready manuscript.