Abstract

The integration of artificial intelligence (AI) into biological sciences has revolutionized research and development (R&D) in various fields, including genomics, protein engineering, and drug discovery. AI’s ability to process and analyze large datasets, predict molecular structures, and design biological systems has accelerated scientific discoveries and innovation. However, this convergence also raises biosafety and biosecurity concerns, necessitating careful consideration of oversight and governance mechanisms. Congressional Research Service issued an insight into this in November 2023.

Introduction

Artificial intelligence (AI) technologies, methodologies, and applications are increasingly being used throughout the biological sciences. This multidisciplinary field encompasses a range of technologies and approaches, such as machine learning (ML), deep learning (DL), and neural networks (NN), which enable machines to work and react in ways that require intelligence. AI has the potential to process large amounts of raw, unstructured data, reduce the time and cost of experiments, and contribute to the broader field of engineering biology.

Associated Sciences and Technologies Enabling Engineering Biology

Impact on Biological Science

Genomic Data Analysis: AI has been instrumental in analyzing genomic data, determining the genetic basis of traits, and uncovering genetic markers linked to those traits. This has implications for personalized medicine and understanding complex biological processes.

Protein Engineering: AI-enabled tools, such as AlphaFold, have demonstrated the ability to predict protein structures accurately. This capability is crucial for designing new proteins with specific functions, which can lead to advancements in drug discovery and biochemical engineering.

Drug Discovery: AI is being used to design new chemical structures and molecules for medical applications. By predicting molecular interactions and optimizing drug candidates, AI accelerates the drug development process.

Laboratory Automation: The integration of AI in laboratory settings has led to automation and “de-skilling” of certain scientific tasks. While this increases efficiency, it also raises concerns about biosafety and biosecurity, as it lowers technical and knowledge barriers.

Biosafety and Biosecurity Concerns: The convergence of AI and biology raises several concerns regarding the misuse of technology, potential production of harmful compounds, and the need for oversight. The use of AI for biological design, in particular, poses risks that must be managed through appropriate governance mechanisms.

Example Application Areas Where AI and Bio logical Sciences Converge

Policy Considerations and Oversight: Regulating AI and its use in biology is a complex issue that requires a balance between promoting innovation and ensuring safety and security. Policymakers must consider whether to adopt broad-based or case-by-case oversight approaches and how to implement structured access to certain AI capabilities and biological data.

Conclusion: AI has a profound impact on biological science, offering new opportunities for research and development. However, it also presents challenges that need to be addressed through careful governance and oversight. As AI continues to evolve, it is crucial to navigate these challenges to harness the full potential of AI in biological sciences while ensuring safety and security.

References:

U.S. Food and Drug Administration. (2019). Institutional Review Boards Frequently Asked Questions. Retrieved from https://www.fda.gov/regulatory-information/search-fda-guidance-documents/institutional-review-boards-frequently-asked-questions
International Gene Synthesis Consortium. (2017). Harmonized Screening Protocol V2. Retrieved from https://genesynthesisconsortium.org/wp-content/uploads/IGSCHarmonizedProtocol11-21-17.pdf
Executive Office of the President (EOP), Office of Science and Technology Policy. (1986). Coordinated Framework for Regulation of Biotechnology. 51 Federal Register 23302. For additional information on the Coordinated Framework, see CRS Report R46737, Agricultural Biotechnology: Overview, Regulation, and Selected Policy Issues by Renée Johnson

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