Absci Corp., a Vancouver company behind a multifaceted drug development platform, went public Thursday. It’s another sign of growing interest in new approaches to drug development, a traditionally risky business.
Absci is focused on accelerating drug development in the preclinical stages. The company has developed and acquired a handful of tools that can predict drug candidates, identify potential therapeutic targets, and test therapeutic proteins on billions of cells and identify which ones are worth pursuing.
“We are offering a fully integrated end-to-end solution for pharmaceutical drug development,” Absci founder Sean McClain told TechCrunch. “Think of this like searching the Google index for protein drug discovery and biofabrication.”
The initial public offering had an initial price of $ 16 a share, with a pre-money valuation of around $ 1.5 billion. through S-1 presentations. The company offers 12.5 million common shares, with plans to raise $ 200 million. However, Absci shares have already skyrocketed to $ 21 per share at time of writing. Common shares are traded under the ticker symbol “ABSI”.
The company has chosen to go public now, McClain says to increase the company’s ability to attract and retain new talent. “As we continue to grow and scale rapidly, we need access to top talent, and the IPO gives us amazing visibility for talent acquisition and retention,” says McClain.
Absci was founded in 2011 with a focus on manufacturing proteins in E. coli. By 2018, the company had released its first commercial product called SoluPro, a biogenerated E. Coli system that can build complex proteins. In 2019, the company expanded this process by implementing a “protein printing” platform.
Since its founding, Absci has grown to 170 employees and raised $ 230 million; The most recent influx was a $ 125 million cross-financing round closed in June 2020 led by Casdin Capital and Redmile Group. But this year, two major acquisitions have rounded out Absci’s offerings, from protein manufacturing and testing to AI-enabled drug development.
In January 2021, Absci acquired Denovium, a company that uses deep learning artificial intelligence to categorize and predict the behavior of proteins. Denovium’s “engine” had been trained with more than 100 million proteins. In June, the company also acquired Totient, a biotech company that analyzes the immune system’s response to certain diseases. At the time of the Totient acquisition, the company had already reconstructed 4,500 antibodies extracted from the immune system data of 50,000 patients.
Absci already had the capabilities to manufacture, test and detect proteins, but acquiring the knowledge allowed it to identify potential targets for new drugs. The Denovium acquisition added an artificial intelligence-based engine to aid in protein discovery.
“What we are doing now is feeding [our own data] in deep learning models and that’s why we acquired Denovium. Before Totient, we were doing drug discovery and cell line development. This [acquisition] it allows us to go fully integrated where we can now also do target discovery, ”says McClain.
These two acquisitions place Absci in a particularly active niche in the world of drug development.
To begin with, there has been notable fiscal interest in developing new approaches to drug development, even after decades of low returns in drug R&D. In the first half of 2021, Evaluate reported that the developers of new drugs raised $ 9 billion in IPO on western stock exchanges. This is despite the fact that drug development is traditionally high risk. R&D returns for biopharmaceuticals hit a record low of 1.6 percent in 2019, and have recovered to just about 2.5 percent, according to Deloitte 2021. report notes.
Within the world of drug development, we have seen AI play an increasingly important role. That same Deloitte report notes that “most biopharmaceutical companies are trying to integrate AI into drug discovery and development processes.” And drug discovery projects received the most AI investment dollars in 2020, according to the Stanford University Artificial Intelligence Index. annual report.
More recently, perspectives on the use of AI in drug development have been bolstered by companies that have carried a candidate through the preclinical development stages.
In June, Insilico Medicine, a Hong Kong-based startup, announced that it had brought an AI-identified drug candidate for idiopathic pulmonary fibrosis through the stages of preclinical testing, a feat that helped close a Series C round of $ 255 million. Founder Alexander Zharaonkov told TechCrunch that the PI drug would begin a clinical trial on the drug later this year or early next year.
With a hand in artificial intelligence and protein manufacturing, Absci has already positioned itself in a crowded but hype-packed space. But going forward, the company will still have to work out the details of its business model.
Absci pursues a business model of partnership with drug manufacturers. This means that the company has no plans to conduct clinical trials of its own. Rather, it expects to earn revenue through “milestone payments” (conditional on reaching certain stages of the drug development process) or, if drugs are approved, royalties on sales.
This offers some advantages, says McClain. The company can avoid the risk of drug candidate failure after millions of money are invested in R&D in testing and can invest in the development of “hundreds” of drug candidates at once.
At this point, Absci has nine “active programs” with pharmaceuticals. The company’s cell line manufacturing platforms are used in drug testing programs at eight biopharmaceutical companies, including Merck, Astellas and Alpha Cancer technologies (the rest are undisclosed). Five of these projects are in the preclinical stage, one is in Phase 1 clinical trials, one is in a Phase 3 clinical trial and the last is focused on animal health, according to the company’s S-1 filing.
One company, Astellas, currently uses Absci’s discovery platforms. But McClain notes that Absci just rolled out its drug discovery capabilities this year.
However, none of these partners have formally licensed any of Absci’s platforms for clinical or commercial use. McClain notes that all nine active programs have milestones and royalty “potentials” associated with them.
The company has some ground to regain when it comes to profitability. So far this year, Absci has generated about $ 4.8 million in total revenue, compared to about $ 2.1 million in 2019. Still, costs have remained high, and S-1 filings note that the company has incurred net losses in the last two years. In 2019, the company reported $ 6.6 million in net losses in 2019 and $ 14.4 million in net losses in 2020.
The company’s S-1 attributes these losses to expenses related to the cost of research and development, establishing an intellectual property portfolio, hiring staff, raising capital, and providing support for these activities.
Absci recently completed construction of a 77,000-square-foot facility, McClain notes. So in the future, the company envisions the potential to increase the scale of its operations.
In the immediate future, the company plans to use the money raised from the IPO to increase the number of programs that use Absci’s technology, invest in R&D, and continue to refine the company’s new AI-based products.