Securing AI in Healthcare and Life Sciences

Artificial Intelligence is transforming healthcare, life sciences, and pharmaceuticals—driving breakthroughs in drug discovery, diagnostics, clinical trial optimization, and patient engagement. But innovation brings new risks. AI increasingly powers critical workflows and decisions, often through third-party models or tools that fall outside traditional compliance controls.

This guide offers a structured approach to AI risk management—spanning discovery, testing, runtime defense, and governance. It aligns with modern AI stacks and the regulatory, security, and audit demands of life sciences. Sections of the comprehensive guide include:

• Understanding the AI Security Stack
• Defining a New MLSecOps Pipeline
• What Are the Risks to AI?
• Step 1: Discover Your AI Footprint
• Step 2: Test AI Models and Assess Risks
• Step 3: Secure AI Development and Deployment
• Step 4: Prevent Data Leaks and Threats During Runtime
• Step 5: Protect the Full AI and Application Stack
• Step 6: Operationalize AI Security
• Conclusion: Building Resilience in the AI Era

Each section details:

• Key Questions You Should Ask
• Challenges
• AI Security Best Practices
• How PointGuard Meets these Challenges