About Workshop
This workshop introduces practical architecture patterns for building reliable, compliant, and value-driven AI agent workflows. Participants will explore use cases in clinical precision medicine, biomedical data analysis, pharma R&D, biomanufacturing, and enterprise automation, with emphasis on governance, validation, safety, and measurable ROI.
Aim
This workshop aims to train participants in designing agentic AI pipelines for healthcare, life sciences, and industrial biotechnology workflows. It focuses on how autonomous AI agents can plan, execute, monitor, and optimize complex tasks across clinical decision support, research automation, quality systems, and business operations. Participants will learn how to connect AI tools with data pipelines, validation frameworks, and ROI-driven outcomes.
What Participants Will Learn
- Understand agentic AI architecture and workflow orchestration.
- Learn how to design AI pipelines for clinical and industrial use cases.
- Explore tool-use, retrieval, automation, validation, and monitoring.
- Evaluate AI outputs for safety, reliability, compliance, and ROI.
- Build a practical roadmap for deploying agentic AI in life sciences organizations.
Structure
Day 1: The Diagnostic Engine & Vision Systems
- Transition from Classical CNNs to Vision Transformers (ViTs) for enhanced medical image analysis.
- Address the “Black Box” problem using Saliency Maps and Explainable AI (XAI) for clinical interpretability.
- Hands-on Lab: Tool: MONAI (Medical Open Network for AI)
- Exercise: Fine-tune pre-trained Med-ViT models for multi-class classification of medical imagery (Chest X-rays or Histopathology slides).
- Outcome: Visualize attention weights to validate clinical decision markers.
Day 2: Data Sovereignty & Synthetic Patient Modeling
- Explore the “Data Silo” paradox and balance HIPAA/GDPR compliance with AI training requirements.
- Utilize Generative AI to create Digital Twins simulating disease progression and clinical trials.
- Hands-on Lab: Tools: Gretel.ai / YData Fabric
- Exercise: Generate privacy-preserving synthetic EHR datasets from seed data.
- Outcome: Produce statistically accurate, shareable datasets bypassing IRB/Ethics Committee bottlenecks
Day 3: Clinical Deployment & Agentic Assistance
- Build Agentic AI agents for autonomous summarization and clinical pathway suggestions.
- Ensure interoperability by integrating AI outputs with legacy hospital workflows using HL7 FHIR standards.
- Hands-On Tools: LangChain, Streamlit, Cytoscape, NetworkX, CellDesigner
- Exercise: Develop a “Clinical Co-Pilot” dashboard that parses unstructured clinician notes, maps to ICD-11 codes, and visualizes molecular networks for actionable insights.
- Outcome: Deploy a functional web-based interface demonstrating real-world ROI and integrated clinical intelligence.
Important Dates
Registration Ends
7:00 PM
Workshop Dates
2026-06-10
8:00 PM
8:00 PM
What You Will Gain
Outcomes
Participants will be able to:
- Design agentic AI pipelines for healthcare and biotech workflows.
- Identify clinical and industrial use cases suitable for automation.
- Map AI pipelines to measurable business and operational outcomes.
- Apply governance, validation, and monitoring principles.
- Create an implementation roadmap for ROI-focused AI adoption.
Who Should Attend
- Undergraduate/postgraduate degree in Bioinformatics, Biotechnology, Biomedical Sciences, Data Science, Computer Science, Healthcare Management, or related fields.
- Professionals in healthcare, pharma, biotech, diagnostics, clinical research, manufacturing, or quality systems.
- AI/ML engineers, data scientists, and automation specialists interested in agentic AI for clinical and industrial workflows.
- Individuals with a keen interest in AI automation, precision medicine, and business impact in life sciences.