CAMBRIDGE, UK — May 7, 2020 — AI VIVO, the Cambridge-based company combining systems pharmacology and artificial intelligence (AI) to accelerate drug discovery, has announced that it is seeking pharma and biotech collaboration partners to progress therapeutic candidates that have been identified by the company as “top-ranked” for COVID-19. The announcement follows the finding that 41 of the candidate drugs from AI VIVO’s top-ranked list for COVID-19 are now in clinical trials for COVID-19 by multiple groups globally.
This underlines the ability of AI VIVO’s platform to systematically and correctly identify candidates with the highest chance of therapeutic success. AI VIVO is now seeking partners to test other candidates identified by the platform as top-ranked, which provide anti-viral, anti-inflammatory and cytokine storm suppressive effects. Using its unique technology, the company also compiled a list of drug combinations from its top-ranked list and they are keen to share the results with pharma companies and clinical trial investigators.
On April 6, 2020, AI VIVO announced that its systems pharmacology platform, which is powered by AI, had identified several candidate drugs that are highly likely to be effective in treating the disease. At that time, five drug candidates from their top ranked list had already been selected by other groups for COVID-19 clinical trials. In less than a month, the number of compound candidates from AI VIVO’s top ranked list that are registered for COVID-19 clinical trials has grown from five to 41 candidates*.
This overlap is significant because AI VIVO’s ranking system is based on the company’s unique phenotypic drug discovery methodology and does not rely on any prior knowledge or known information related to the disease or compounds. To identify the candidate drugs most likely to be effective in treating the disease, AI VIVO used samples from COVID-19 infected cells to build its model for the disease, which was then used to rank 90,000 compounds. The top candidate compounds list represents only 0.3 percent of the evaluated drugs.
The overlap of candidates identified by AI VIVO that pharma companies have also selected from their pipelines includes:
- Tyrosine kinase inhibitors such as Imatinib (Novartis) and Nintedanib (Boehringer Ingelheim)
- Rheumatoid arthritis drugs including Tofacitinib (Pfizer)
- Ruxolitinib (Incyte) and Baracitinib (Eli Lilly) as JAK inhibitors
- Valsartan (Novartis) as an angiotensin receptor inhibitor
- Ibrutinib as a BTK inhibitor (Janssen Pharmaceutica – AbbVie)
- Dapagliflozin as a SGLT2 inhibitor (AstraZeneca)
This is a great validation of AI VIVO’s phenotypic approach to modeling diseases and the effects of drugs," said Dr. Peyman Gifani, AI VIVO founder and CEO. "Our panel of experts believe there are combinations of other top-ranked drugs that will be more effective than any single drug and we are keen to share our results with pharma companies and clinical trial investigators to support the fight against COVID-19. We are also offering to cross check the candidates from other investigators to help predict combinations to improve drug efficacy, reduce undesirable side effects and optimize the dosage.’’
Dr. David Cleevely CBE, lead investor in AI VIVO, said: “Now that our approach has been validated, we are expanding our interactions with government agencies and pharmaceutical companies to review the top ranked drugs which have not yet been selected for trials, but have the potential to make a real difference in the fight against COVID-19.”
Amongst AI VIVO’s top ranked list of candidates are a number of proprietary compound candidates currently in phase II or phase III clinical trials. AI VIVO will now be proactively reaching out to the pharma companies who have developed these compounds to provide more information on why the compounds are top ranked and how they might be used as single drugs and in combinations.
For the list of 41 top-ranked candidates please visit: www.aivivo.co/covid-19
For more information about the other top-ranked list please contact: email@example.com