[1S01m] 10. ASPIRE - Part 1

10:30 AM - 11:00 AM JST(1:30 AM - 2:00 AM UTC)

[1ASPR-01-KL] Keynote Speech: Automated labs and AI - Opportunities and Challenges for Engineering and Generative Biology

○Paul Simon Freemont¹ (1. Imperial College London (UK))

Keywords:

Engineering Biology,AI,automation

[In the late 1990s and early 2000s, synthetic biology emerged as a new field of research where biologists began applying engineering design principles, and computational and molecular biology methods, to the design and redesign of biological systems and organisms. Whilst technically very challenging, the concept of designing and creating new biological genetic code at a genetic and organismal level is now firmly established and the field of engineering biology continues to grow and develop. As a platform technology, many countries are currently investing in engineering biology, as the same technology can be applied in many industrial sectors including materials, fuels and chemicals, drugs and therapeutics, agritech and food and environment, climate change and waste. With the rapid developing convergence of AI with biological sciences, exemplified by alpha-Fold protein structure predictor and the Evo 2 biology foundation model, a new adjunct field is emerging called ‘generative biology’, or GenBio. GenBio aims to design and create novel biological molecules, systems and genomes by combining AI and machine learning (ML) and large-scale biological data with automation and large-scale DNA construction. The overall aim of GenBio is to define the genetic design rules for living systems by essentially understanding the language, syntax and grammar of DNA as written in genomes and chromosomes and expressed in living cells. If we can define the generative rules of biology, then we will be able to predictably apply these rules to many application sectors and accelerate the transition to a circular and sustainable bioeconomy based on biomanufacturing. However, such capability also brings biosecurity, ethical and societal issues that need to be addressed in advance of the development of such capability. In this talk I will discuss the global growth of biofoundries as key infrastructure hubs, providing automation and analytical measurement to accelerate engineering biology research and development. I will explore how biofoundries are becoming key facilities to enable and accelerate biomanufacturing developments and that pre-competitive global cooperation between biofoundries is essential to enable a future transition to more sustainable bioproduction of chemicals, material, drugs and food. I will provide examples of biofoundry workflows including the role of cell free systems for rapid prototyping of engineering biology designs. I will promote the concept of a biofoundry abstraction hierarchy and the need for a shared understanding of biofoundry workflows including unit operations, standards and metrics which can be used to benchmark biofoundry activities. Finally, I will discuss the development of fully autonomous biofoundries and the convergence of AI-Bio and the need for AI-ready data standards for model development. I will imagine a future era of fully programmable biology and what would be needed to achieve this and what risks would need to be addressed including societal acceptance.