Lecture Notes: AI Influencers and Doctor Innovators Dialogue

Introduction

• Event Title: AI Influencers and Doctor Innovators Dialogue
• Program: Digital Innovation Upskilling Program (DUP)
  • Started 5 years ago
  • Certified hundreds of doctors
• Partnership: Collaboration with AKT Health
  • Involves life sciences, pharma, biotech
  • Intersection of healthcare and pharmaceutical companies

Keynote Speaker: Dr. Elias Abal Zed

• Background:
  • Principal Data Scientist at Novo Nordisk
  • 12+ years in digital health and AI innovation
  • Leads biomarker analytics
  • Former Associate Director of Data Science at Sopi
  • Education: PhD in Biomedical Engineering from the University of Toronto
  • Author, patent holder, conference speaker

Topic: Wearables and AI for Better Drug Development

Challenges in Pharma

• High cost for new drug development: approx. $2.6 billion
• High failure rate in phase three trials (70%)
• Issues with episodic and subjective clinical assessments

Real-World Data and Wearables

• Real-world data helps track disease progression and therapy effects better
• Wearables provide continuous and objective data
• Definition of digital biomarkers by European Medical Agency
• Growing acceptance and adherence to wearable technology

Comparisons: Digital Biomarkers vs Patient-Reported Outcomes

• Digital biomarkers provide objective, continuous, passive data
• Patient-reported outcomes suffer from subjectivity and recall bias
• Examples of linear correlation and activity tracking

Advantages of Digital Biomarkers

• Objective assessment of drug efficacy and safety
• Decentralization of clinical trials
• Cost reduction

AI and Wearables

• AI processes big data from wearables into health measures
• Use of machine learning, deep learning, and generative AI
• Examples of AI applications like walking speed estimation and self-supervised learning

Generative AI and Healthcare

• Generative AI allows for predictive health assessments
• Health large language models can predict health conditions using multimodal data

Success and Regulatory Perspectives

• Digital biomarkers evolving to primary/secondary endpoints
• Approval of digital endpoints (e.g., European Medical Agency's approval)

Future of AI and Wearables

• Personalized medicine and predictive health
• Real-time clinical decision support
• Integration of multimodal data

Discussion and Q&A

• Regulatory Requirements:

  • FDA and EMA guidelines for digital health technologies
  • Considerations for patient data privacy and protection

• Patient Adherence:

  • Importance of patient-centric device design
  • Engaging patients and using notifications for reminders

• Infrastructure Challenges in Low/Middle-Income Countries:

  • Solutions include memory on chip and power-efficient devices

• Global Collaboration and Standardization:

  • Need for harmonized regulatory standards through international collaboration

Conclusion

• AI and wearables can revolutionize health management, diagnosis, and treatment
• Opportunities in personalized medicine and multimodal data integration
• Importance of collaboration between industries and regulatory bodies