Digital Twins are a Key Enabling Technology for Personalized Medicine

Area of Science:

• Biotechnology and Biomedical Engineering
• Computational Biology
• Mathematical Modeling

Background:

• Digital twins (DTs) are computational models of biological systems used for health management.
• DTs are increasingly bridging the gap from research to clinical application.
• The technology has broad applications beyond healthcare, including ecology and agriculture.

Purpose of the Study:

• To highlight digital twin technology as a significant opportunity for the mathematical modeling community.
• To examine digital twin development from both academic and commercial perspectives.
• To provide a comprehensive overview of the current landscape and future potential of DTs.

Main Methods:

• Review of current digital twin applications in health and biology.
• Analysis of academic and commercial development pathways for DTs.
• Synthesis of insights from diverse fields including ecology, biotechnology, and agriculture.

Main Results:

• Digital twins represent a rapidly growing field with significant potential for innovation.
• Cross-disciplinary applications demonstrate the versatility and impact of DT technology.
• The integration of mathematical modeling is crucial for advancing DT capabilities.

Conclusions:

• Digital twins offer a powerful platform for personalized medicine and health maintenance.
• Collaboration between academia and industry is key to realizing the full potential of DTs.
• Further research and development in mathematical modeling will drive future advancements in DT technology.