AI’s Role in Virus Design Raises Biosecurity Concerns

Artificial intelligence (AI) has revolutionized various sectors, including medicine, by accelerating drug discovery and enhancing diagnostic precision. However, recent developments have unveiled a darker side to this technological progress: the potential for AI to design novel viruses, posing unprecedented biosecurity challenges.

AI’s Dual-Use Dilemma in Biotechnology

AI-driven biological design tools (BDTs) have demonstrated the capability to create novel proteins and genetic sequences. While these innovations hold promise for therapeutic advancements, they also raise concerns about the potential for designing harmful biological agents. A study by Hattoh et al. (2025) revealed that AI models could generate toxic proteins with high toxicity scores, closely resembling known toxins such as ricin and diphtheria toxin. This finding underscores the dual-use nature of AI in biotechnology, where tools intended for beneficial purposes can be repurposed for malicious applications. (arxiv.org)

Healthcare data growth can be overwhelming scale effortlessly with TrueNAS by Esdebe.

Challenges in Biosecurity Measures

Traditional biosecurity measures primarily rely on sequence alignment and protein-protein interaction (PPI) prediction to detect dangerous outputs. However, these methods have proven inadequate in identifying novel threats. A study by Feldman and Feldman (2025) evaluated leading PPI prediction tools, including AlphaFold 3 and AF3Complex, and found that none successfully identified experimentally validated SARS-CoV-2 mutants with confirmed binding. This highlights the need for a shift toward response-oriented infrastructure, including rapid experimental validation and adaptable biomanufacturing, to effectively address AI-driven biological threats. (arxiv.org)

The Need for Robust Biosecurity Frameworks

The convergence of AI and biotechnology necessitates the development of comprehensive biosecurity frameworks. Policymakers, scientists, and industry leaders must recognize that traditional biosecurity measures are insufficient to counter emerging threats. Without proactive measures, the risk of AI exacerbating bioweapons development will continue to grow, posing serious threats to global security and public health. This evolving context necessitates a reimagining of biosecurity approaches, with discussions focusing not only on restricting access but also on promoting transparency, accountability, and innovation for defensive and beneficial purposes. (pmc.ncbi.nlm.nih.gov)

Conclusion

While AI holds immense potential for advancing medicine and biotechnology, it also presents significant biosecurity risks. The ability to design novel viruses and other harmful biological agents underscores the imperative for robust biosecurity measures. By proactively addressing these challenges, we can harness AI’s benefits while mitigating its potential for misuse.

References

• Hattoh, G., Ayensu, J., Ofori, N. P., Eshun, S., & Akogo, D. (2025). Can Large Language Models Design Biological Weapons? Evaluating Moremi Bio. arXiv preprint. (arxiv.org)

• Feldman, J., & Feldman, T. (2025). Resilient Biosecurity in the Era of AI-Enabled Bioweapons. arXiv preprint. (arxiv.org)

• Sandbrink, J. B. (2023). Artificial intelligence and biological misuse: Differentiating risks of language models and biological design tools. arXiv preprint. (arxiv.org)

• Peppin, A., Reuel, A., Casper, S., Jones, E., Strait, A., Anwar, U., Agrawal, A., Kapoor, S., Koyejo, S., Pellat, M., Bommasani, R., Frosst, N., Hooker, S., … & Frosst, N. (2024). The Reality of AI and Biorisk. arXiv preprint. (arxiv.org)

• Carter, S. J., et al. (2023). Responsible AI in biotechnology: balancing discovery, innovation and biosecurity risks. PMC. (pmc.ncbi.nlm.nih.gov)