Ken Drazan: Building an LLM that speaks the language of the immune system
How ArsenalBio is targeting cancers and accelerating the speed of biomedical research
What successes has this approach yielded so far in the battle against cancer?
We have five different solid-tumor cancer programs, two of which are with our partner, Bristol Myers Squibb, and three of which are internal at ArsenalBio. We currently have two of those internal programs in human clinical trials. They have demonstrated early proof of concept, which is that we can administer a single drug — one shot — that can potentially lead the patient toward a path for cure. It’s early days in our testing, but the evidence that we’ve been able to collect thus far is encouraging.
So you originally set out to develop therapies for cancer, but in the process you leveraged your data and AI to build this platform. And now you seem on the cusp of something that could have much broader applicability. What are the lessons in that?
First of all, this opportunity started in a company that had very big ambitions. We started with more of an engineering approach than a classic wet lab research approach. And, as our capabilities became operational, they started to generate large data sets. At the time, AI in the life sciences was nascent, and frankly, not necessarily accessible. Fast forward several years, and our datasets got bigger and better, and we became more sophisticated at handling that data.
In parallel, the cost of GPU started to come down, and hyperscalers became increasingly accessible for small customers. That’s what began the platform shift. Instead of us trying to do things by hand, we could do more in the cloud. And things ballooned from there, as we were able to generate tons more data. And when you start to think big, new business partners, investors, and thought leaders show up because they want to enable the platform shift of the future. So, we basically created a startup within a startup. By having a culture that allows inquiry, as soon as our platform started to answer questions that seemed impossible to answer in our laboratories, we started to ideate how this could become a platform for many.
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