In this podcast episode, host Dr. Andree Bates talks with Justin Byers, founder & CEO of Axio BioPharma, about a transformation taking hold in biologics manufacturing: how artificial intelligence and automation are collapsing timelines that once stretched over years into just weeks.
What might sound like science fiction is quickly becoming standard practice. As Byers explains, AI models can now simulate and predict key process parameters before experiments ever reach the bench. Instead of relying on long, trial-and-error lab cycles, development teams can test thousands of variables in silico, then validate only the most promising conditions in the lab. The result is a faster, leaner path from concept to clinic.
1. Monoclonal antibodies as the ideal first use case
Because monoclonal antibodies (mAbs) are better understood and historically more standardized than some other biologics, they act as a proving ground for AI‑enabled biomanufacturing. Byers argues that if you can accelerate mAbs development, that lays the groundwork for applying the same AI tools to more complex biologics, vaccines, and cell therapies.
2. Digital twins & in silico modeling cut risk and waste
One of the episode’s most compelling parts is the discussion of digital twins of bioreactors which are virtual models that simulate fermentation, purification, and downstream processes. These allow researchers to test “what‑if” scenarios before ever running an experiment in the lab, helping to avoid failed batches, lower impurities, and reduce wasted resources.
3. Cell line selection, upstream & downstream enhancements
Byers walks through how AI is applied to cell line selection, upstream fermentation (growth, yields, stress responses), and downstream purification (removing impurities, optimizing yields). The point is that AI doesn’t just optimize one step, it can help coordinate across the entire pipeline.
4. Regulation, trust & adoption
Adoption in pharma always runs into regulatory guardrails. Interestingly, the FDA is becoming more open to AI models, so long as they are transparent, validated, and integrated into risk frameworks. Byers and Dr. Bates discuss how trust, interpretability, and alignment with existing regulatory standards will shape real adoption.
5. Unlocking rare disease & smaller players
One of the most exciting promises is that AI can democratize biologics development. By drastically lowering cost and time barriers, smaller biotech companies can compete, and rare or ultra‑rare disease therapies, which often aren’t commercially viable under traditional cost structures, may become more feasible. Byers claims Axio’s platform is already saving clients 12–18 months and over $1 million+ per project.
Why This Matters (Especially Now)
The intersection of AI and biomanufacturing matters now more than ever, as the demand for faster, safer, and more scalable biologics continues to grow, especially in response to global health threats like pandemics. Traditional development timelines, which often span years, are no longer sustainable when the need for innovation is urgent. By leveraging AI to drastically shorten the path from concept to production, the industry can not only respond more quickly to emerging diseases but also reduce costs, improve safety, and expand access. This shift could fundamentally change the bottlenecks in drug development, moving from scientific uncertainty to challenges around computational robustness, interpretability, and regulatory approval. As AI tools mature and regulatory bodies become more receptive, the opportunity to transform how biologics are discovered and manufactured is becoming a practical reality.
Where Innovation Meets Impact
This episode offers a compelling glimpse into the intersection of AI and biomanufacturing, not as futuristic speculation, but as an emerging frontier already delivering tangible results. Justin Byers’ insights paint a picture of a future in which more biologic therapies can be explored, faster, and with less wasted effort. For anyone in biotech, pharma, or health tech, it’s a must‑listen.