Interview Questions for Dan Chen, MD, PhD, Genesis BioCapital
- With your extensive background at Genentech and foundational contributions to the Cancer-Immunity Cycle, can you share some insights on the key challenges and breakthroughs in cancer immunotherapy over the past decade, and how these have influenced the development of new therapies?
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- How do you see the role of artificial intelligence and machine learning evolving in oncology, particularly for applications like gene therapy vector optimization and other cancer immunotherapy advancements?
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- You’ve mentioned wanting to reshape the role of investors in innovation and company creation through Genesis BioCapital. Could you share your perspective on how investors can better support scientific breakthroughs and what changes you’d like to see in the biotech investment landscape?
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1. The past decade+ has clearly brought cancer immunotherapy to the forefront of treatment in Oncology. Checkpoint inhibitors such as PD-(L)1 antibodies and synthetic immune approaches such as CAR-T, have helped increase survival for many patients suffering from terminal diagnoses- and has been life changing for some. However, next generation immunotherapy has been challenging. These challenges shouldn’t be unexpected- follow-ups to Avastin, Rituxan and Kadcyla were also challenging. For checkpoint inhibitors, the PD-L1:PD-1 axis plays such a dominant role in immune suppression, that next generation checkpoint inhibitors can be like adding a bucket of water to the ocean. Greater focus on biomarker driven identification of specific patients where a second checkpoint is playing an outsized role is important. Alternatively, generating the breakthroughs necessary to understand and properly remove the other dominant inhibitory signals, such as TGF-b. For synthetic immune approaches, I think the challenge has revolved around overstimulation leading to weakening and loss of the full ability of T cell driven eradication of cancer. Further advances and engineering that enable more precise control of both the amplitude and tonic nature of the T cell stimulatory signal will likely help- especially if we can make it better reflect a physiologic anti-cancer response in strength and quality. The challenges for next generation immunotherapy will help spur the necessary focus to come. And with rapid advances in technology emerging, I think the breakthroughs here will come in a multitude of different ways.
2. AI, particularly generative AI, has come on so fast. And what’s even more notable, is the continued pace of advancement. I think ultimately, AI will change everything. And I mean everything in society and in healthcare. It’s the truest disruptor we’ve seen in our lifetime- of which we’ve seen many. However, there are somethings that AI can do incredibly well today, and there are many things that will take longer, 2 year, 5 years and 10-20 years. I think it’s important to be very clear where different applications fall in time. People need to be working on 10–20-year problems- but that should probably be mostly tackled in academia. But applications that are coming in two years should be developed now. And to make that work, whether for gene therapy or cancer immunotherapy, one of the most important challenges is feeding it the right dataset to power generative AI. There are good pre-clinical high throughput systems where a lot of wet lab data can immediately be fed to AI. That’s a two year problem. However, one of the big bottlenecks for biotechnology is in the translation from pre clinical to clinical. And that may be a more difficult problem. For example, if we are going to design de novo proteins- how many data points do we really have to predict immunogenicity? 10,000? 100,000? I don’t think so. So we have to get smart and creative to address challenges like this.
3. Investors play an incredibly important role in innovation. And new ideas, big ideas, many of these are being seeded and built from the ground up by entrepreneurs. So it’s a really important part of innovation, technology and engineering in our field. And it plays to the strengths of a capitalist model. Investors in our system all have their own differing strategies for ensuring their financial success. But I fear there isn’t enough diversity in those strategies, and often, those strategies for investors, may be misaligned from the founders, scientists and engineers that they seek to partner with. This can be incredibly problematic, especially when new technology is being developed. With Genesis BioCapital, we are looking to create technologies and companies with alignment of the clinical problem that we are trying to solve, the specific technology being used, and how the science and technology works in pre-clinical models and in humans. That alignment means being really precise in what we are trying to achieve, and less reactive to what they see and what everyone else is doing. By incorporating science, engineering, medicine, biomarkers and financial expertise at the investment decision level, Genesis BioCapital should be able to define and chart a very specific direction and alignment for building successful innovation. And by doing so, we believe we can create true Impact Investment: where fund success is driven by successful creation of better technology, health and longevity.
