Crucial Technological Advancements for Future Pandemic Preparedness and Supply Chain Stability

In this Pharmaceutical Executive video interview, Marcel Botha, CEO of 10XBeta, discusses shortcomings in the US' emergency plans for rapid innovation and manufacturing during public health crises, highlighting the need for innovation pipelines, supply chain resilience, and regulatory clarity. He also emphasizes the importance of localized manufacturing, public-private partnerships, and advanced manufacturing techniques like AI and additive manufacturing. Botha notes the success of the Spiro Wave project in reducing ventilator size and the need for better coordination and funding structures. He also advocates for a more agile and collaborative approach to ensure rapid response in future emergencies.

Pharmaceutical Executive: Looking forward, what are the most significant technological advancements or innovations in medical device manufacturing that will be crucial for future pandemic preparedness and supply chain stability?

Marcel Botha: There are lots of interesting things coming down the pipe. Obviously, it's been two years of AI mayhem. Going from machine learning and large data lakes, to actually have an understanding of where our data can actually have an impact on these LLMs and critical feedback loops with AI tools. AI will play a huge role in everything from biotech to drug development, both discovery orphan drug reuse or repurposement and medical device design.

When I look at AI as a tool to reinforce what we build, it plays a role from the very inception of an idea all the way to regulatory clearance and post market surveillance. It plays a role in how we think about risk and risk analysis, and how we analyze large swaths of data to make sure that we can be risk averse and have a clear understanding of the potential risks outside of just a human assessment.

Does the machine mean that we don't have a human in the loop? Everything we do, a human has to look and scrutinize what comes out of the trained AI data, but it's advancing at a speed faster than we can learn. It's like when Bill Gates wrote a book, Business at the Speed of Thought, in 1997, which was a comment about how fast we're going to be learning with the age of the internet. This was first.com, and I would say that we are definitely at an age where AI has surpassed the speed of thought.

What is interesting is what type of innovation, opportunities, challenges, objections, or enlightenment we're going to want to get from this. AI is also affecting how we design physical product, how we scrutinize physical product, how we do critical, finite element, and flow analysis. Any tool that we use today can be augmented with an AI layer. Some of them are extremely clunky. I think we're in AI version 1.0 right now, and so I'm very excited to see where we are a couple of generations later, and where it becomes an extension of our intellectual capacity to contribute to the sector.

Anything with data or any physical device that is connected has a data stream, and you can build intelligence layers on top of any data stream. Real time monitoring brings the ability to move a lot of health care to the home, then intelligent systems like AI and ML, that can be run on top of those data streams from those devices in real time, bring the ability to reframe the quality of care. I see a future where we have better care at home than we have in the hospital today. That's an interesting future where we move from a reactive medical industry to a proactive medical industry.

Lastly, we see definitely opportunities for improvement. Beyond AI, there's many other opportunities that we can look up. I've touched on additive manufacturing to death, but we have advanced manufacturing, robotic manufacturing, new chemistries, new polymers, and organic chemistry.

All of these things will affect how we make products in the future, and all of this is driven by new technologies that are coming on board. We're also seeing a lot of flexible manufacturing approaches. A lot of the sort of collaborative yet competitive, network manufacturing approach that I spoke about in terms of building a resilient ecosystem, from having the tools that can manage the supply chain risk and supply chain response and manufacturing response at a higher than single entity level.

When we have tools, especially with public private partnerships that can assess industry-level flexibility, response, and resource management—especially during disaster relief times—we have an extremely valuable network effect after of technologies and technology companies that can collaborate, compete, co-locate, depending on what season it is. Is it disaster season, or is it Christmas? We need to be able to have that agility, that's what's been missing from the US manufacturing ecosystem for the longest time.