‘For the first time in human history, our ability to collect data on our biology has outpaced our ability to interpret and act on it’
Brendan Frey’s passion for genomics — the science of analyzing and interpreting our DNA — was ignited in 2002. When a family member was diagnosed with a genetic disorder, there wasn’t enough information for doctors to evaluate the full scope of the problem, let alone fix it. “I thought we should live in a better world,” Frey says. “One in which we can accurately detect and treat genetic diseases.”
Developing a new medicine is a long, expensive and often demoralizing process. It can take an average of 10 to 12 years, cost upwards of $2 billion and, after all that, the drug in question may not even make it past clinical trials. At first, there was plenty of skepticism about tools like these. But according to a report from Deep Learning Analytics, a data analytics company in Virginia, AI and R&D start-ups raised more than $156 million in the first quarter of 2018 alone.
“Traditionally, drugs were designed for one target, reflecting a lock and key model where they’re developed to bind to a single protein,” says Cyclica president and CEO Naheed Kurji. “However, a growing body of research has shown that drugs often have hundreds of off-target interactions , leading to unanticipated and unwanted side effects. Our goal is to examine all possible proteins in the body that a drug can bind to.
“Using AI, we have an opportunity to diagnose early, predict the course of a disease and thus treat the disease early, potentially before symptoms manifest,” he says. Kurji is similarly enthusiastic about the potential for AI to make drug development “less of a high-stakes gamble” and lead to better, safer drugs for more indications. “Diseases that currently have no treatment, such as Alzheimer’s, and those where treatment is arduous and unreliable, like cancer or diabetes, may move into the realm of treatable or even curable much sooner than they would under the old model.
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