Protecting Drug Discovery IP in AI

Research copilots and AI tools now help scientists analyze compounds, trial results, and manufacturing formulas. Generic DLP recognizes credit cards and Social Security numbers, not proprietary molecular structures or unpublished trial data. PointGuard AI lets life sciences organizations define their own sensitive data types and enforce policies across AI interactions, so research teams can use AI without exposing their most valuable IP.

Research IP does not look like the sensitive data traditional controls were built to find.

• Compound identifiers, sequences, and formulas evade generic detectors.
• Scientists paste unpublished results into public AI tools.
• Collaborators and CROs connect AI tools to shared research data.
• A single leak can undermine patents and competitive position.

AI Data Protection and Runtime Guardrails enforce custom research data policies across AI workflows.

1. Define custom data types. Create detectors for compound IDs, chemical structures, sequences, trial identifiers, and project code names, alongside built-in PHI and PII detectors.

2. Set policies by tool and team. Decide which AI applications may process which research data, and where results can be sent.

3. Inspect and enforce. Scan prompts, responses, and tool calls in real time. Redact or block research data headed to unapproved destinations.

4. Review and refine. Report detections by project and team. Tune detectors as programs evolve and feed events into IP protection and incident response processes.

• OWASP Top 10 for LLMs: LLM02 Sensitive Information Disclosure and LLM07 System Prompt Leakage, covering disclosure of proprietary research and exposure of sensitive context in prompts.
• OWASP Top 10 for Agentic Applications: ASI02 Tool Misuse and Exploitation and ASI03 Identity and Privilege Abuse, addressing research agents that misuse tools or access to move IP.
• NIST AI RMF: MAP identifies sensitive research data; MEASURE evaluates exposure; MANAGE enforces policies; GOVERN defines ownership.