Drug development startup Qrativ has been launched by the Mayo Clinic and nference to exploit an artificial intelligence (AI)-based platform for systematically identifying new applications for developmental drugs, in particular against rare diseases. Qrativ launches with $8.3 million in Series A financing from Matrix Capital Management, Matrix Partners, and the Mayo Clinic.
Qrativ’s Darwin.ai platform combines nference’s knowledge synthesis platform with the Mayo Clinic’s medical expertise and clinical data. The nference platform nferX uses neural networks to extract knowledge in real time from commercial, scientific, and regulatory literature. Qrativ partners can leverage the drug-purposing platform to search for all potential uses of a drug candidate, including identifying potential rare disease indications and finding subsets of patients who are most likely to respond to a given candidate.
“In the last three years, the AI field has gained incredible momentum driven by major breakthroughs in deep learning neural networks,” says Murali Aravamudan, co-founder and CEO of Qrativ and nference. “Our core technology based on a neural network ensemble identifies nascent drug–disease, drug–gene, and other therapeutically relevant associations from the vast biomedical literature.”
Although drugs have previously been repurposed for rare diseases, this repurposing has typically been carried out late in the development process. Qrativ aims to carry out more systematic drug repurposing, starting during the earlier stages of drug development. The firm is keen to call this approach drug purposing, rather than “repurposing.” “This is a bold step for Mayo Clinic and complements our patient-centered care approach with an innovative way to uncover new therapeutic indications for drugs in the collective industry pipeline,” explained Andrew Badley, M.D., co-founder and CMO Qrativ. “It enables us to search for all possible uses of a drug starting at the early stages of development.”
Qrativ is based in Cambridge, MA, and at the Mayo Clinic’s main campus in Rochester, MN. “The ingenuity of Qrativ is that it will combine clinical insight and clinical need from Mayo Clinic with robust informatics capabilities,” added Dr. Badley, who also is director of the Office of Translation to Practice at Mayo Clinic. “By taking into account genomic predictors of both desired treatment response and unwanted toxicity, Qrativ will be able to identify potential drug candidates more swiftly. This will enable us to use nference’s big data capabilities to define highly targeted patient populations and then leverage the deep clinical expertise of Mayo clinicians to design and implement optimal proof of concept trials to meet the unmet needs of our patients.”
The exploitation of machine learning for drug discovery and development is on the rise. Earlier this month, U.K.-based AI-driven drug discovery and design firm Exscientia inked a potentially $43 million drug discovery collaboration with GlaxoSmithKline (GSK). In May, Excientia agreed a strategic research collaboration and license option deal with Sanofi, worth up to €250 million (approximately $287 million). And in April, the firm partnered with Evotec to identify new bispecific small-molecule immuno-oncology drugs.
Other players in the field include California-based computational drug design company Numerate, which in June reported a drug development deal with Takeda Pharmaceutical, and separately established a drug design collaboration with Servier.