How the world of biobanking is changing with artificial intelligence

Area of Science:

• Biobanking
• Health Informatics
• Data Science

Background:

• Biobanking has evolved from sample collections to complex data and sample infrastructures.
• Emerging technologies, policies, and societal expectations continually reshape biobanking practices.
• The intersection of health research and healthcare is a historical root of biobanking.

Purpose of the Study:

• To analyze the impact of Artificial Intelligence (AI) technologies on biobanking operations.
• To present biobanks as dynamic boundary objects in the context of AI.
• To explore how AI influences the transformation of biological material and data into biovalue within the bioeconomy.

Main Methods:

• Assessment of four key parameters: size, site, speed, and access.
• Analysis of AI technologies' influence on biobank evolution and operation.
• Conceptual framework of biobanks as boundary objects producing biovalue.

Main Results:

• AI significantly impacts biobanking operations, particularly concerning data management and accessibility.
• Biobanks are increasingly functioning as dynamic boundary objects due to AI integration.
• AI facilitates the transformation of biological samples and associated data into valuable assets for the data-driven bioeconomy.

Conclusions:

• AI is a key driver in the evolution of biobanks towards data-centric infrastructures.
• Biobanks, enhanced by AI, play a crucial role in generating biovalue and contributing to the bioeconomy.
• Understanding the impact of AI on parameters like size, site, speed, and access is vital for future biobank development.