Workshop A – Mastering AI & ML for Life Sciences: Essential Strategies for Counsel and Executives
Zheng Yang
Worldwide Head, AI/ML Strategy and Solutions
Healthcare and Life Sciences
Amazon Web Services
This interactive workshop will provide legal, regulatory and compliance professionals in the life sciences with a solid understanding of the technology driving AI, ML and deep learning. Industry thought leaders will provide an in-depth analysis of key concepts, challenges, regulations, and practical insights, enabling participants to adeptly navigate the confluence of these technologies and the life sciences. Topics of discussion will include:
- Generative AI v. Traditional AI
- Defining basic distinctions, characteristics, and foundational tech that separate generative AI from traditional AI
- Understanding how generative AI revolutionizing areas like drug discovery, bioinformatics, and personalized treatments is relative to traditional AI in the life sciences
- Fundamentals of AI and ML
- Defining what Artificial Intelligence (AI) and Machine Learning (ML) are
- Differentiating between AI and traditional programming
- Understanding supervised, unsupervised, and reinforcement learning
- Exploring Natural Language process, neural networks, and deep learning
- AI Applications in Life Sciences
- Exploring real-world applications of AI and ML in the life sciences
- Understanding AI capabilities for drug discovery, clinical trials optimization, disease diagnosis, medical imaging, personalized medicine, and more
- The AI Lifecycle: Data, Algorithms, and Model Training
- Developing data collection and preprocessing:
- Quality, bias, privacy, and security considerations
- Selecting appropriate algorithms and models for specific tasks
- Harmonizing the training process
- Supervised learning, validation, and testing
- Challenges and Risks in AI and ML
- Anticipating bias and fairness issues in AI algorithms and their impact on decisions
- Integrating ethical considerations when using AI in medical decision-making
- Meeting regulatory and legal challenges
- FDA regulations, GDPR compliance, intellectual property, and liability
- Business and Compliance Considerations
- Identifying business opportunities and ROI through AI adoption to be more effective
- Ensuring compliance with relevant regulations, including FDA guidance and GDPR
- Managing risks associated with AI implementation and usage
- Fine-tuning transparency – what does it mean, and to whom