Stanford inks computer-driven liver cancer drug discovery pact with twoXAR

A team at Stanford University School of Medicine has struck a liver cancer drug discovery deal with twoXAR. The pact will see Andreessen Horowitz-backed twoXAR use its computational drug discovery capabilities to make disease-to-candidate predictions, an approach the partners think could uncover drugs with different, more effective mechanisms of action than Bayer’s Nexavar.

Hepatocellular carcinoma (HCC), the most common form of liver cancer, has proven to be a tricky disease to address, with Bristol-Myers Squibb ($BMS) among the companies to swing and miss in the clinic. The failed Bristol-Myers candidate, like Nexavar and Exelixis’ ($EXEL) Phase III HCC program cabozantinib, is a tyrosine kinase inhibitor. But, while tyrosine kinases are a popular HCC target, the late-phase blowups that have blighted the field have raised doubts at twoXAR about their merits.

“New drugs in development for HCC primarily target tyrosine kinases, but they have demonstrated mixed success in clinical trials, suggesting a need for new therapies targeting a more diverse set of biomarkers,” twoXAR CEO Andrew Radin said in a statement.

Whitepaper Download

Reducing the Complexity and Costs of Channel Planning and Logistics

How can you make the process of bringing your product to market less complex while also reducing costs? This Whitepaper identifies opportunities to simplify channel strategies for biopharma companies, their customers and patients. Discover how you can deliver savings and innovation to your business.

TwoXAR is aiming to help the Asian Liver Center at Stanford expand the pipeline of HCC assets beyond tyrosine kinase inhibitors. This will entail the use of the same technologies and methods the computational biology startup has applied to its collaborations with the University of Chicago, Mount Sinai Hospital and Michigan State University. Once twoXAR has suggested HCC candidates, the Asian Liver Center will validate them in preclinical tests.

Regardless of the indication being researched, the process starts with sourcing datasets and looking for disease signals. This leads to the generation of a drug-disease model, which, in turn, underpins work to predict the efficacy of different candidates. By applying its algorithms to data and seeing where they lead, twoXAR thinks it can uncover unforeseen links between drugs and diseases, making it a good fit for indications such as HCC in which the dominant therapeutic paradigm has disappointed.

TwoXAR is yet to rack up the consistent successes needed to validate its confidence in the platform. But, equipped with cash from Andreessen Horowitz’s recently established $200 million bio fund and collaborations with academic institutions, the startup is positioned to find out whether it can live up to its own optimism.

Suggested Articles

A few years ago, one of our Fierce editors met a Big Pharma R&D chief for the first time. “You’re the ones with the scary name,” he joked.

There's no evidence personal patient information leaked during the 11-week breach, but the same can't be said about Sangamo's own secrets.

Through a new online tracker, AllTrials names sponsors who fail to report clinical trial results on time per the FDAAA Final Rule.