Addressing Inefficiencies in Drug Development With AI

Tanja Dowe, CEO, Debiopharm Innovation Fund SA, discusses the partnership between Debiopharm and VeriSIM Life and how advancements in technology can speed up the drug development process.

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Welcome back to PopHealth Perspectives, a conversation with the Population Health Learning Network where we combine expert commentary and exclusive insight into key issues in population health management and more.

In this episode, Tanja Dowe discusses how technological advancements can be used to optimize drug development.

Hi, I'm Tanja Dowe. I'm the CEO of Debiopharm Innovation Fund SA. We're a 150-million investment fund based out of Switzerland. We invest in digital health when it affects the patient journey or improves the way we develop drugs.

Thank you. Can you comment on the current state of drug development?

I think that we in the pharmaceutical world all agree that drug development takes too much time and is too expensive. We produce drugs over several years that can be highly priced to the market, maybe due to the expenses of the development, and that worked in some patient groups but not in other patient groups.

We have worked the same way for decades. Every other industry in this world has digitalized heavily and has started to work on data and using AI. I think the pharmaceutical industry has some catch-up work to do.

What inspired the partnership between Debiopharm and VeriSIM Life?

VeriSIM Life falls exactly into the paradigm of digital health for improving the way we develop drugs. It's a company that can really speed up the translational medicine, but also de-risk our drug assets that we're developing in clinical trials.

We looked at the company and saw that they are pretty unique in this in silico drug development value chain. And we really like the management team, including Jo Varshney, the entrepreneur, founder, and CEO. There was this match in values as well.

What we're trying to do is improve drug development, but also bring better drugs to patients faster.

How can AI and the other technology that you have access to be used in the drug development process?

In a lot of ways, because we use a lot of data in our drug development. We base the design of drugs on data and very complex disease models. It's a perfect environment for AI.

AI can work well in the drug development world because we work with huge amounts of data, whether it be the data that we collect in our own clinical trials or from real-world data sources. I think we're just in the beginning of discovering what all we can do with AI.

How do you think that this technology will impact patient care going forward?

These are big questions. On one hand, we look at early-stage drug development, and then patient care on the other hand. We need to bring better, personalized drugs to patients, and the more personalized we go, the narrower the patient population is. If we develop pharmaceuticals, we need to make that development very cost-efficient, so we can bring drugs to those narrow populations.

This is the real connection: with better ways to develop drugs to de-risk assets and any toxicities, as well as ensure efficacy, we're able to bring more personalized drugs to patients.

In that same vein, where do you see the future going?

I see, first, having a different wealth of data included in the clinical trials and clinical development. This includes patient quality of life, data that we collect directly from patients, and data being more patient-centric in general.

The other direction we are going toward is in silico development, modeling, simulating clinical trials, and simulating translational medicine, just like VeriSIM Life is doing, but instead of drug discovery, we're moving into drug design. We actually design drugs with the help of AI and data. I think that we're going to have a very different type of biotech industry or early drug development in the next 5 to 10 years.

Thank you, Tanja. Is there anything that we haven't covered that you would like to add today?

I would just encourage all the entrepreneurs developing AI and computational biology and medicine. Keep going on that track. Your technologies are needed. All of us in the pharma industry acknowledge the problem of our slow and expensive drug development process. We'd love to work with you.

Thanks for tuning in to another episode of PopHealth Perspectives. For similar content or to join our mailing list, visit populationhealthnet.com.

This transcript has been edited for clarity.