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How AI and Decentralized Clinical Trials are Changing Biopharma

By Scott Kirsner |  March 3, 2022
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John Orloff, Venture Partner, Agent Capital

After four years running global R&D at Alexion Pharmaceuticals, a Boston company developing drugs to treat rare diseases, John Orloff says he “stepped off the bus” at the end of July 2021. That was when the company’s $39 billion acquisition by AstraZeneca formally closed. Orloff’s next move was to join the venture capital firm Agent Capital.

InnoLead spoke to Orloff recently as part of our research report on “Retooling R&D for a New Era.”

Accelerating clinical trials. When you look at the pandemic, in many ways it did accelerate the adoption of various digital technologies that support what we call decentralized clinical trials, using telemedicine, sensors, home health services, mobile apps, and wearable devices for remote monitoring. The pandemic forced that, because patients couldn’t come into the medical centers. We’ve been talking about this for many years – including the need to tap into patients in remote areas, who don’t traditionally participate in clinical trials, because they don’t have access to an academic or tertiary care center.

A lot of companies are continuing in that trend, using those methods and tools, because it’s a more efficient way. We tap into the 95 percent of patients who don’t currently participate in clinical trials, and that can greatly accelerate our ability to conduct trials.

How science scouting happens today. I don’t really think we need brick-and-mortar meetings to go to to stay abreast of the latest developments these days, with the web and Zoom and other means. [At Alexion, we had] a team of scientists on our business development team — probably 12 people — that were just scouring the internet and publications and press releases and presentations at congresses, to reach out and gain a better understanding of what these companies are doing, and then finding competitor startups in the same space.

I think AI and machine learning technology will allow us to make better decisions and choices, and give us new insights into how to approach certain diseases.

Artificial intelligence and machine learning. As humans, we have limitations in being able to integrate and synthesize and look at data. I think AI and machine learning technology will allow us to make better decisions and choices, and give us new insights into how to approach certain diseases. [At Alexion, we] also applied AI and ML to the operational aspects of the business. We developed an algorithm for our COVID-19 therapeutic trial, because we wanted to chase the pandemic [and find regions where the virus was most active.] For other trials, we wanted to avoid it. [Those algorithms] helped us to determine which sites would be most affected and have difficulty enrolling patients. 

A version of this interview appears in our latest research report, Retooling Research and Development for a New Era.

M&A and In-licensing at Alexion. When I was at Alexion, we set out on a very aggressive business development mission to bring in new [drug] assets, either through in-licensing or acquisitions. We acquired Wilson Therapeutics, Syntimmune, Portola – a lot of things that fit our mission as a company focused on rare diseases. We made a conscious effort [to] skinny down our own internal research, which hadn’t been very productive historically, and have them focus on complement biology. That was their true expertise. 

If you look at the big pharma companies, how productive have they been in their own research?

We reduced our own research by about 40 percent, and focused on bringing in assets from the outside. Innovation is happening in those startups and small companies. If you look at the big pharma companies, how productive have they been in their own research?

Startups and BigCos. With the explosion of cloning the human genome, and understanding how that connects better to disease, biology, and physiology – a lot of that is happening in academia or startups, outside of big pharma research. And there is a steady flow of talent out of big pharma into smaller companies. [Going forward,] you need to have smart people in your R&D and business development organizations, because when you partner [with academic labs or startups], your role isn’t designing the studies or executing the studies; you’re providing input. That’s a very different role, and sometimes it’s frustrating. You might do it a different way, but you have to be collaborative. 

 

(Featured image by National Cancer Institute on Unsplash.) 

 

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