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Pharmaceutical industry embraces digital health for drug development, trials

Artificial intelligence and big data collection are playing a larger role in the drug development process, shaping the way precision therapies are matched to a patient and driving changes in the clinical trial process along the way, according to experts.

Many industry leaders agree that the pharmaceutical sector was slower to pick up on digital trends than others like banking, PricewaterhouseCoopers partners said at the J.P. Morgan Healthcare Conference in San Francisco.

"The stakes are high — we've seen what happens when a drug doesn't get approved, and when you're trying to do it in a different way, the hurdles are more immense," PwC's U.S. Pharmaceutical and Life Sciences Leader Karen Young said in an interview. "The purpose of the data is to help with innovation and to speed up the go-to-market process."

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The 2020 J.P. Morgan Healthcare Conference, one of the largest industry gatherings of the year, is underway in San Francisco.

Source: S&P Global Market Intelligence

Novartis AG CEO Vas Narasimhan said during a presentation that the company has 1,500 data scientists on hand and training programs for artificial intelligence. He also highlighted partnerships with Microsoft Corp. in artificial intelligence and Amazon.com Inc. in operational scaling.

Smaller companies like women's health specialist Myovant Sciences Ltd. are also embracing the digital health revolution. For example, the company's partnership with the Flo Period Tracker app enables women to recognize signs of abnormal menstrual health, a symptom of uterine fibroids. Myovant has a drug nearing U.S. approval for the condition, which affects an estimated 19 million women between the ages of 15 and 49 years of age.

"We really want to engage with the community in helping educate women, helping empower women to make active decisions in their healthcare," Myovant CEO Lynn Seely told S&P Global Market Intelligence. "The women we serve are ideally suited and need to embrace this technology and partnering in digital innovation is a great thing to bring together medical advances and gather our strengths together."

IBM's Watson in health

One of the biggest investors in healthcare's embrace of artificial intelligence and big data is International Business Machines Corp. The technology company has partnered with research organizations like the Broad Institute, Vanderbilt-Ingram Cancer Center, Brigham and Women's Hospital, Memorial Sloan Kettering Cancer Center and more.

IBM's Watson platform applies artificial intelligence to provide researchers with access to data around the world to bring the right therapies to patients, IBM Watson General Manager Paul Roma said.

"Once you marry the right diagnostic with a therapy, that's when you make amazing differences," Roma said. "To bring this level of intelligence to a doctor, the only way to do that is technology. It doesn't tell them what to do, but it augments their ability as doctors to make the right decisions."

For pharmaceutical companies, Watson's big data capabilities allow for more precise matching of diagnostics to a therapy, improving outcomes for those patients with the genetic makeup that benefits most from a certain treatment.

But progress with Watson has been slow and IBM has been relatively quiet about its progress after an initial period of media hype. Patient outcomes did not match the expectations the company set forth at the outset.

"Part of being less vocal was giving it more time and making more progress and letting our technology speak for itself," Roma said. "It's now being used in 5,000 hospitals across 80 countries, and so something is working well."

Part of the evolution of IBM's approach was to focus on area-specific patient outcomes rather than a broad platform.

"We are the only ones spending more than a billion dollars specifically in healthcare. IBM has already been through a cycle of broad approach," Roma said.

Next hurdle: trial design

IBM is preparing to deploy a new platform for trial design in February that Roma said will inform the way clinical studies use data, predict efficacy and enroll the right patients for a therapy.

"In 2019, it's true we had more drugs approved than any year in history, but we also had more trials stopped than any year in history," Roma said. "That means we're failing more, and it is extremely costly."

Roma believes trial design in the U.S. is going to change dramatically to operate within a system, much like the U.K.'s National Health Service.

"When conducting trials in a system, you can cut out more than 80% of a billion dollars, and that is a conservative estimate," Roma said. "The question is, how is the U.S. going to create a similar system — our system is so distributed."

Roma pointed to a comparative study from Johnson & Johnson that pulled together a dataset with more than 600,000 patients with HIV, leading to drugs that are now commonplace to treat the disease.

"Most trials are informed by datasets, and we play a big part in a lot of those findings," Roma said.