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IPO: Recursion Pharmaceuticals Leverages Therapeutics Discovery With Machine Learning

Recursion Pharmaceuticals Inc. uses machine learning to hunt for new therapies. The company raised $436 million in an upsized initial public offering priced at the top of a marketed range.

Last week , the Salt Lake City-based company sold about 24 million shares for $18 each.

Recursion is among a crop of new startups called digital native companies in the drug discovery business. According to Lina Nilsson, Recursion’s Vice President of Product, “we have a unified, company-wide platform with common coding languages, data storage frameworks and tools. Digital natives live fully in today’s integrated software world, without large networks of incompatible legacy systems.” Lina also comments that digital native biotech startups are already balancing and integrating the worlds of tech (e.g. engineering and data science) and science (e.g. biology and chemistry) and as such have an edge against larger companies with vastly more resources than Recursion. Yet the static or declining level of R&D output at many large companies means that they have an ongoing need for new projects to fill their pipelines.

The company develops its technical infrastructure as interlocking products, borrowing from tech’s’ use of product management to align across business, technology and science disciplines to crystallize out the most impactful areas of focus. It’s all about industrialized drug discovery. Lina says, “we develop our technical infrastructure as interlocking products, borrowing from tech’s’ use of product management to align across business, technology and science disciplines to crystallize out the most impactful areas of focus. We don’t just build new data science models, we create the frameworks to build the right models and build rigorous infrastructure to implement at scale. Rather than individual tools, the focus is on systems of products.”

Recursion reached a deal with Bayer AG in September 2020 to use AI to find new drugs for lung fibrosis and other fibrotic diseases. The deal included a $30 million upfront payment and $50 million in equity funding by Bayer’s investment arm.

Pipeline

The company is advancing 37 programs, and there are ten ‘Notable Programs’ that are key, near-term value drivers given their individual market opportunities and the validation they provide for each generation of the Recursion OS, the company’s platform software that integrates a multi-layer system for generating, analyzing, and deriving insights from biological and chemical datasets.

Brute-Force Search Programs

Eight of Recursion’s Notable Programs were identified using what the company calls brute-force search approach. Four of these programs are new uses of existing known chemical entities, or KCEs, that that company has advanced to clinical development and for which they have obtained key enabling licenses. Another four of these programs are new chemical entities, or NCEs, that have been discovered and advanced in-house.

Inferential Search Programs

Two of Recursion’s Notable Programs were identified since mid-2020 using its new inferential search approach. One of these programs is a new use of an existing KCE while the other is an NCE discovered and advanced in-house. The speed with which the company has been able to identify and initiate early discoveries with inferential search programs demonstrates the potential power of the Recursion OS to generate high-quality hits to move through the lead optimization process.

In addition to the Notable Programs highlighted above, the company is actively exploring 27 additional programs which may prove to be drivers of our future growth. Of these programs, 10 arose out of our brute-force search approach, and 17 were identified using our newer inferential search approach since July 2020.

Moving forward, the company expects that the vast majority of its new programs will be discovered using its inferential search approach. The company believes that the number of potential programs it can generate with its Recursion OS is key to the future of our company, as a greater volume of validated programs has a higher likelihood of creating value. The speed at which its Recursion OS generates a large number of product candidates is important, since traditional drug development often takes a decade or more. In addition, the company believes that our large number of potential programs makes it an attractive partner for larger pharmaceutical companies.

Image source: Recursion Pharmaceuticals Inc

Source: Recursion Pharmaceuticals Inc


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IPO: Recursion Pharmaceuticals Leverages Therapeutics Discovery With Machine Learning was last modified: April 27th, 2021 by Staff