By SHANNON O. WELLS
In the U.S., around $3 trillion is spent each year to manage chronic diseases. Counterintuitively, as those costs continue to rise, so do the diagnoses of obesity, diabetes, cancer and Alzheimer’s disease.
In short, prices go up, while too few patients get healthier as a result.
A Pitt-based healthcare initiative focused on managing chronic diseases through a comprehensive, AI-based collaborative approach involving patients, physicians and payers is poised to transform this conundrum into a considerably healthier and more affordable patient landscape.
“Part of the initiative is going to be looking at how we can transform healthcare, particularly for management of chronic and severe illnesses,” said Anantha Shekhar, senior vice chancellor for Pitt Health Sciences. “As you all know, our healthcare is quite expensive in the U.S. … yet our outcomes are not as good as they should be. And our management of chronic diseases is continuing to escalate … and the cost, of course, will continue to keep going up.
“We need to think about how to manage these differently than the traditional way, so we believe that there is a better way to manage these common conditions.”
Shekhar discussed the fledgling public-private partnership between Pitt and Vizzhy Inc., and GAINMED, called a “transformative” AI-powered health care platform, on April 30 in Scaife Hall’s third-floor auditorium.
Shekhar was later joined by Vishnu Vardhan, co-founder of Vizzhy Inc., an Austin, Texas-based global leader in AI health care technology. In December, Vizzhy announced Pitt’s new Vijayalakshmi Innovation Center in Women’s Health Analytics and Research (VIHAR).
The media event preceded a day-long symposium on May 1, during which memorandums of understanding were signed to solidify the partnership.
The initiative establishes the Pitt-Vizzhy Longevity Labs, in partnership with Illumina Inc., to provide multiomics laboratory services designed to expand precision, or “P5 Medicine” — precise, predictive, preventive, personalized and participatory care — to optimize patient care for complex diseases across the United States and globally.
With other corporate members on board, including L&T-Cloudfiniti, LTIMindtree, AWS, Thermo Fisher Scientific and AMD, the goal is to have one million patients on board with the technology in the next few years.
While delivered in his typically low-key fashion, Shekhar’s enthusiasm for the initiative’s and GAINMED platform’s potential is nonetheless palpable.
“It’s not about research. It’s not about discovery,” he said. “This data will provide ample opportunities for all of those things, but this would be the first, I would say, comprehensive AI-driven medical diagnostic and management tool that an academic medical center will be releasing.
“So in that sense, it’s both a big deal, but it’s also a very complex kind of effort,” he added. “But the point of this whole effort is to create new models of healthcare, as opposed to our traditional bricks and mortar, and come to the hospital (approach).”
Shared vision
He described GAINMED as an “asynchronous or generative and agentic AI-navigated multiomic medicine” platform built with AI and omics tools. Specifically, the laboratory will provide nine “omics” — such as genomics, transcriptomics, metabolomics and proteomics — measuring different components of person’s body in a comprehensive manner.
“And that would be part of everyone’s medical records,” Shekhar explained. “That becomes part of this, and patients will have access to it. They can own their data, and we will be able to provide that in a very cost-effective way using current technologies.”
A patient can use it as a mobile app, a physician can have it as a dashboard, or a payer can use as population databases. “So we can manage that in multiple ways,” Shekhar said.
Without the partnership, this treatment approach could cost as much as $5,000 per person. “But we hope to be providing that for less than $1,000 per person,” he noted. “And we are also planning to have roughly a million patients sequenced through this technology over the next three years.
“You can imagine the revenue stream that we hope to generate for Pittsburgh and variety of other support that happens through that.”
Vishnu Vardhan of Vizzhy said the initiative is an opportunity to combine two “great technologies” — generative AI and multi-omics — to transform healthcare by mapping patients’ biological data.
“We collect data points from one person, but that’s huge data, so you need AI to transform that, so we do it at a scale, at half a (currently) double price. With this kind of technology, we can really transform and improve outcomes, reduce the cost,” he said, “and we really make this very accessible to most of the population of the world.
“That was the vision I had when I started Vizzhy, that would be bringing (together) these two technologies, and I saw that same vision was (at Pitt) regarding improved outcomes, lowering costs and making healthcare more affordable and accessible to people.”
This formed the basis for a partnership, he added, “where we are trying to enable two things, using generative AI and then the whole Multi-omics Lab, which we are bringing to transform the healthcare, reduce the cost, and increase (access to) the cutting-edge care … to everyone.”
Right now, Shekhar said enrolling new patients is the priority. “That’s the first step, and all of that would be used for generative AI for creating the knowledge base for data-decision support to physicians and guidance to patients or consumers,” Shekhar said.
The partnership team is conversing with several health systems in creating the GAINMED platform, he said, with the primary goal of serving thousands of patients who have “high-complex” diseases. “People who have five or six diseases and taking seven or eight medications.”
The initiative’s rollout will begin with establishing the multi-omics laboratory followed by the GAINMED platform.
Game-changing approach
Responding to a question about the partnership’s “uniqueness,” Shekhar said it stands apart as an AI initiative that’s “purely focused on patient care” from molecular, behavioral, lifestyle and cost-effectiveness sides. “That is the foremost impact of this.”
Shekhar offered an example of a patient with severe diabetes, obesity and high risk of heart disease who takes at least four medications and is told to closely monitor their diet.
“All of this requires that person to, first of all, be totally compliant with every one of these instructions and take all of these multiple medications every day — and also hope that they can change their entire lifestyle and their diet,” he said. “And we know how successful that approach has been. What happens is that we try that for six months or a year, (and) it doesn’t get better.”
Applying a “$10,000 drug” such as Ozempic to the treatment may lead to 60% of such patients losing weight and improving, but also likely to remain on the medications. “We don’t even know how long they have to be on it. So that’s the classic kind of a patient we would be looking at.
“Now imagine that person will now have a multiomic database that we would look at, so we’ll understand their biology completely. With that we should be able to (say) ‘Are you going to benefit from particular types of diet? Are you going to benefit from particular types of medication regimen, including Ozempic?’” he said.
Biomarker data can determine a patient’s likelihood to respond to certain medication.
“With mobile apps and various types of decision support, we can now help the physicians say, ‘This is the person that you should prescribe X to, and you should not prescribe X to,” he explained. “This is the person that would benefit more from diet as opposed to exercise or a combination, and this is the person that would have side effects from medicine, or worse.”
Owning your treatment
Doctors will benefit from such data optimization, while patients can monitor their blood sugars or various types of biological measurements weekly.
“Now they can essentially monitor their own body and their behaviors and their biology,” Shekhar said. “Once people start counting the steps on their mobile app, suddenly they start walking a little more than they usually do. So you start to compete with yourself and say, ‘Oh, yesterday, I only put in 4,000 steps. Tomorrow, I’ll do a little better.
“… You’ll have a couple of days when you’re a couch potato, but you’ll have that kind of continuous reinforcement of your behavior. So that’s how we see patients responding,” he added. “And then for payers, if we said to them, ‘Oh, you don’t have to pay for Ozempic for some of these folks who are not going to benefit from it … they (won’t) be paying $10,000 a month for the next six months before they realize it’s not healthy.
“That’s an example of a complex patient that we think can be not only improved, but kept out of the hospitals, and kept out of very expensive treatments,” he said.
While the partners are in talks with various “payers,” aka insurance providers, and will be announcing some partnerships in the future, Shekhar emphasized this is “not about just partnering with insurance companies.
“It’s really about extending care and access for the right people, so that who benefits from what treatment will not only make every dollar go further in healthcare, but also actually improves care (from) the trial-and-error method that we do today,” he said.
“That’s what’s going to sustain this model. If we can change provider and payer behavior in addition to patient behavior, that’s how we’re going to transform healthcare.”
Shannon O. Wells is a writer for the University Times. Reach him at shannonw@pitt.edu.
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