Industrializing Pharma

Recursion Pharma raises $60 million to scale its Artificial Intelligence and Automation Platform

(this piece initially published Oct 3, 2017 by Lux Capital)

Recursion Pharma, a company we are lead Series A investors in, today is announcing an exciting and oversubscribed Series B of $60M coming from top investors in tech, biopharma, and around the world. In many ways it's a reflection of all the company has accomplished in the last year (more on that in a bit) and fuel for growing ambitions in the rapidly coming future. Moreover, it's a validating moment and a nod to a strong surge of entrepreneurial technologists we've seen and continued to fund - beyond Recursion - that have taken lessons from automation, data, systems engineering, and AI and applied them to a large industry historically seen as "outside the purview of Silicon Valley IT": Bio Pharma. I expect Recursion's early success to be indicative of a larger, macro trend as Technology continues to evolve and expand its reach, creating value in not just "Consumer" and "Enterprise", but also finding massive new industries altogether. In all of these vectors, the question will be asked: "Where is the Google of X?" Within Pharma, I'm convinced Recursion is leading the charge.

Florescent stain on human cells. Replicated 10,000 times. Quantified with Neural Nets.

We backed Recursion founders Chris Gibson, Blake Borgeson, and Dean Li last year shortly after our first meeting. Their drive to treat biology like an engineering systems problem with due attention to automation of wet lab protocols, fidelity and reproducibility of data, and a deep philosophical belief that every assumption should be turned over to remove human bias and treat underlying data as "ground truth" were theses we'd previously iterated towards and invested into. "Radical Empiricism" in biology was a philosophical stance Recursion CEO Chris and I both ascribed to, which helped cement our partnership in leading the Series A.

Our theoretical stances on how to do biology and how to marry automation with AI with pharma have since begun to manifest with tangible results. Our pipeline now stands at more than 30 early stage assets all discovered empirically vis-a-vis automation to capture data and machine learning to understand the data absent human bias - too often referred to as "intuition." We've gained confidence in our particular marriage of cellular abstraction and "phenomics" as our assets have consistently passed gold standard wet lab assays as used by traditional large Pharma -- all costing many orders of magnitudes more, and taking years, not weeks, when discovered with status quo mechanistic approaches.

Along the way we've rediscovered clinical stage assets Big Pharma continues to push, increased our ability to scale numerous joint ventures with Pharma's most radical and progressive incumbents, and broadened our scope beyond the initial focus on Rare Diseases with novel programs in Aging, Immuno-Oncology, New Chemical Entity Discovery, and Inflammation. We've more than tripled the team and brought on young superstars and industry veterans from across pharma, biology, and machine learning; with soon to come announcements of transformative industry leaders joining the company(Chris won’t let me disclose who just yet!). I'm biased given my own background as Computer Scientist... but find myself most excited in our collaboration with Deep Learning pioneer Yushua Bengio who is now an active advisor and partner with the company.

List of rediscovered clinical stage assets

$60M in and of itself isn't a milestone. But, in context of Recursion's enormous progress over the last calendar year and growing potential (Google for X) I'm thrilled to actively double down as investor and add fuel to accelerate towards massively upending how drugs are brought to bear. True north here isn't a particular philosophical or technological dogma, it's not fundraising events or even milestones - but rather it's positively impacting human health against the world's most deadly and heartbreaking diseases.