The biggest risk in drug development is getting a new treatment to work safely in humans. That's a hefty burden, and a new artificial intelligence startup has snagged $9 million in an attempt to reduce the risks and costs of failed clinical trials.
Boston and Tel Aviv-based Quris has built an AI platform it says is capable of predicting which investigational drugs will work safely in humans. The AI-powered "patients on a chip" platform aims to reduce the risks associated with clinical trials that go bust as well as tamper the reliance on animal testing by predicting the safety and efficacy of drugs before they get into humans.
The startup's initial focus is on rare genetic diseases that can't be modeled in animals. The first drug developed on the platform addresses fragile X syndrome, a common inherited cause of autism. Clinical trials for the drug are slated for 2022, Quris said.
Quris is using stem cell automation technology from the New York Stem Cell Foundation Research Institute. The nonprofit's CEO and founder, Susan Solomon, joined the Quris advisory board.
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“Put simply: We are not mice so what works in animal-based trials is not a proper indicator of what will work for people," said Aaron Ciechanover, M.D., a Nobel laureate, in a statement. Ciechanover is one of the scientific leaders of Quris alongside Moderna co-founder Robert Langer, an MIT professor.
The platform is trained on known safe and toxic drugs so that the AI can screen thousands of potential drug formulations on genetically diverse "patients-on-a-chip" using stem cell disease modeling.
Backing the startup with angel funding are Judith Richter, Ph.D., and Kobi Richter, Ph.D., co-founders of stenting system maker Medinol, and Moshe Yanai, founder of data storage tech company Infinidat.