GenAI and LLMs in Pharma R&D Essentials Training by Tonex
This two-day professional training explores the transformative role of Generative AI and Large Language Models (LLMs) in pharmaceutical research and development. Participants will discover how GenAI tools are accelerating hypothesis generation, literature mining, and scientific communication while reshaping regulatory support and clinical workflows. The course also examines cybersecurity impacts, including data leakage risks, secure prompt engineering, and protection of proprietary models. By highlighting the fusion of AI and cybersecurity in pharmaceutical innovation, this course equips professionals to leverage LLMs responsibly and securely within R&D pipelines.
Audience:
- Scientists and researchers
- Pharmaceutical R&D professionals
- Digital transformation leads
- Clinical operations personnel
- Data scientists in life sciences
- Cybersecurity professionals in pharma
Learning Objectives:
- Understand the fundamentals of GenAI and LLMs in pharma R&D
- Explore applications such as drug repurposing and literature analysis
- Analyze the role of AI in regulatory documentation and scientific writing
- Identify cybersecurity concerns and mitigation strategies
- Apply prompt engineering tailored to scientific contexts
- Evaluate hybrid LLM architectures for enterprise deployment
Course Modules:
Module 1: Foundations of GenAI in Pharma
- Overview of generative AI in life sciences
- Capabilities and limitations of LLMs
- Relevance to pharmaceutical research
- AI-enhanced R&D workflows
- Security risks with model usage
- Trends shaping pharma AI adoption
Module 2: Drug Repurposing with LLMs
- Text mining for drug-disease relationships
- Accelerating target identification
- Recommender systems for repurposing
- Scientific database integration
- LLM outputs and clinical trial planning
- Data confidentiality considerations
Module 3: Scientific Writing & Regulatory Support
- Automating scientific content generation
- Summarizing peer-reviewed research
- Assisting regulatory documentation
- AI in FDA and EMA submissions
- Ensuring traceability and auditability
- Addressing compliance and IP protection
Module 4: Chatbots for Clinical Use
- LLMs in clinical inquiry resolution
- Patient-facing support tools
- Enhancing trial recruitment and retention
- Medical chatbot deployment strategies
- Privacy-preserving conversational models
- Risk mitigation in clinical interactions
Module 5: Risks and Validation
- Hallucination challenges in scientific contexts
- Establishing validation pipelines
- Prompt engineering techniques for accuracy
- Trust and explainability in LLMs
- Cybersecurity vulnerabilities and countermeasures
- Ensuring model governance in R&D
Module 6: Proprietary Models and Hybrid AI
- Advantages of fine-tuned proprietary LLMs
- Open-source vs closed-source trade-offs
- Hybrid architecture deployment models
- API access vs internal hosting risks
- Model performance benchmarking
- Secure model deployment in pharma networks
Elevate your understanding of AI-driven pharmaceutical innovation while mastering secure deployment practices. Enroll now in the GenAI and LLMs in Pharma R&D Essentials Training by Tonex and become a forward-thinking leader in digital pharma transformation.