Absci Corp., a Vancouver company behind a multifaceted drug development platform, went public on Thursday. It’s another sign of snowballing interest in new approaches to drug development — a traditionally risky business. 

Absci focuses on speeding 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 tells TechCrunch. “Think of this as the Google index search for protein drug discovery and biomanufacturing.” 

The IPO was initially priced at $16 per share, with a pre-money valuation of about $1.5 billion, per S-1 filings. The company is offering 12.5 million shares of common stock, with plans to raise $200 million. However, Absci stock has already ballooned to $21 per share as of writing. Common stock is trading under the ticker “ABSI.” 

The company has elected to go public now, McClain says, to increase the company’s ability to attract and retain new talent. “As we continue to rapidly grow and scale, we need access to the best 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 launched its first commercial product called SoluPro — a bioengineered E. coli system that can build complex proteins. In 2019, the company scaled this process up 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 crossover 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 using deep learning AI to categorize and predict the behavior of proteins. Denovium’s “engine” had been trained on 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 Totient’s acquisition, the company had already reconstructed 4,500 antibodies gleaned from immune system data from 50,000 patients. 

Absci already had protein manufacturing, evaluation and screening capabilities, but the Totient acquisition allowed it to identify potential targets for new drugs. The Denovium acquisition added an AI-based engine to aid in protein discovery. 

“What we’re doing is now feeding [our own data] into deep learning models and so that is why we acquired Denovium. Prior to Totient we were doing drug discovery and cell line development. This [acquisition] allows us to go fully integrated where we can now do target discovery as well,” McClain says. 

These two acquisitions place Absci into a particularly active niche in the drug development world. 

To start with, there’s been some noteworthy fiscal interest in developing new approaches to drug development, even after decades of low returns on drug RD. In the first half of 2021, Evaluate reported that new drug developers raised about $9 billion in IPOs on Western exchanges. This is despite the fact that drug development is traditionally high risk. RD returns for biopharmaceuticals hit a record low of 1.6% in 2019, and have rebounded to only about 2.5%, a Deloitte 2021 report notes. 

Within the world of drug development, we’ve seen AI play an increasingly large role. That same Deloitte report notes that “most biopharma companies are attempting to integrate AI into drug discovery, and development processes.” And, drug discovery projects received the greatest amount of AI investment dollars in 2020, according to Stanford University’s Artificial Intelligence Index annual report. 

More recently, the outlook on the use of AI in drug development has been bolstered by companies that have moved a candidate through the stages of preclinical development. 

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 preclinical testing stages — a feat that helped close a $255 million Series C round. Founder Alexander Zharaonkov told TechCrunch the PI drug would begin a clinical trial on the drug late this year or early next year. 


With a hand in AI and in protein manufacturing, Absci has already positioned itself in a crowded, but hype-filled space. But going forward, the company will still have to work out the details of its business model.  

Absci is pursuing a partnership business model with drug manufacturers. This means that the company doesn’t have plans to run clinical trials of its own. Rather, it expects to earn revenue through “milestone payments” (conditional upon reaching certain stages of the drug development process) or, if drugs are approved, royalties on sales. 

This does offer some advantages, says McClain. The company is able to sidestep the risk of drug candidates failing after millions of RD cash is poured into testing and can invest in developing “hundreds” of drug candidates at once. 

At this point, Absci does have nine currently “active programs” with drug makers. The company’s cell line manufacturing platforms are in use in drug testing programs at eight biopharma 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, per the company’s S-1 filing. 

One company, Astellas, is currently using Absci’s discovery platforms. But McClain notes that Absci has only 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 the nine active programs have milestones and royalty “potentials” associated with them. 

The company does have some ground to make up when it comes to profitability. So far this year, Absci has generated about $4.8 million in total revenue — up from about $2.1 million in 2019. Still, the costs have remained high, and S-1 filings note that the company has incurred net losses in the past 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 chalks up these losses to expenditures related to cost of research and development, establishing an intellectual property portfolio, hiring personnel, raising capital and providing support for these activities. 

Absci has recently completed the construction of a 77,000-square-foot facility, notes McClain. So going forward the company does foresee the potential to increase the scale of its operations. 

In the immediate future, the company plans to use money raised from the IPO to grow the number of programs using Absci’s technology, invest in RD and continue to refine the company’s new AI-based products.

Source: TechCrunch

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