PALO ALTO, Calif.—As we noted in an article in October 2016, artificial intelligence (AI)-driven biopharmaceutical company twoXAR Inc. has entered into a collaboration with the Asian Liver Center at the Stanford University School of Medicine to support research focused on the identification of drug candidates targeting hepatocellular carcinoma (HCC).
In this drug discovery collaboration, twoXAR was to make disease-to-candidate predictions using the company’s software-driven discovery platform. From that point, researchers at the Asian Liver Center—under the direction of Dr. Mei-Sze Chua, senior scientist in the laboratory of Samuel So—would tackle preclinical studies to validate those candidates.
Now comes news this March that, utilizing gene expression and other data along with AI algorithms, twoXAR has identified a potential promising new treatment in concert with the Asian Liver Center at Stanford University, which is performing additional preclinical studies to validate the candidate.
This candidate targeting HCC, TXR-311, has shown positive results in cell-based assays. TXR-311 is a molecule that twoXAR identified as having a high probability of being effective in treating HCC. Proof-of-concept studies were performed by The Asian Liver Center, with the objective of these studies to establish preliminary cytotoxicity data in cell-based assays for 10 separate candidates.
HCC is a primary malignancy of the liver and occurs predominantly in patients with underlying chronic liver disease, often caused by hepatitis B or C virus infection. HCC is generally refractory to chemotherapy, and only one targeted treatment, the tyrosine kinase inhibitor sorafenib (Nexavar), is indicated for HCC. However, sorafenib has been shown to marginally extend survival and can elicit severe side effects.
“We are excited by the results of this preclinical study and believe they make a compelling case for continuing our investment in toxicity and patient-derived xenograft studies,” said Andrew A. Radin, co-founder and CEO of twoXAR. “In just one month, we went from formalizing our collaboration to identifying candidates and completing our initial proof-of-concept cell-based assays. This is another great example of how our AI-driven platform is helping accelerate early-stage drug discovery.”
In a panel of genetically diverse HCC cell lines, TXR-311 was shown to be potently cytotoxic with an average half maximal inhibitory concentration (IC50) in the nanomolar range. Activity in HCC cell lines was shown to be approximately 500-fold more potent than in a panel of primary hepatocytes isolated from three different donors with no liver diseases, indicating high selectivity for cancer cells vs. healthy cells. In addition to its cytotoxic activity, there are also data suggesting that TXR-311 may target other aspects of HCC pathology. These mechanisms will be explored in later stage in-vivo studies.
twoXAR computationally screened a library of more than 25,000 potential drug candidates. The 10 with the strongest evidence for potential efficacy and safety were selected for these studies. Each candidate was identified using twoXAR’s computational drug discovery platform which utilizes AI to rapidly perform unbiased analyses of biological, chemical and clinical data to predict and rank potentially efficacious drugs. This strategy potentially offers a new route to unique intellectual property rights that allow for the rapid development of a drug while maximizing the opportunity to identify the most efficacious molecule.
Preclinical studies were conducted by researchers at The Asian Liver Center, which will now conduct follow-on toxicity and patient-derived xenograft studies.
