Digital health tools and technologies were thrust into the spotlight during the pandemic and were able to help many people get much needed medical advice and treatment when few other options were available. However, whether this boost to the industry will remain after a year of relative normalcy and a reduction in the COVID-19 threat is less clear.

“We’re just scratching the surface,” University of Pittsburgh Medical Center (UPMC) chief technology officer Christian Carmody told Inside Precision Medicine. “I think COVID helped change that mindset of where, when, and how we get our health care, when we were forced to stay away and stay in isolation, and I think that’s stuck. Things like telemedicine and telehealth visits really enabled us to continue delivering care in that very difficult time. Consumers were open to receiving care that way and engaging with clinicians much more quickly, and more conveniently than ever before.”

Technology has the potential to bring precision medicine to more people and to really democratize the patient journey, but there are also significant challenges that need to be addressed before digital health can really become mainstream.

Regulation of digital health technology in the U.S. still lags behind innovation, although the FDA and the Office of the National Coordinator for Health Information Technology (ONC) are working to improve and update official standards and regulations.

Improved regulatory standards should also help improve uptake and reimbursement of these tools by payers increasingly looking to implement preventative “value-based” medicine, as championed by the Affordable Care Act.

“In the next five years, the Centers for Medicare & Medicaid Services (CMS) wants providers that do Medicare to go from about 6% value-based care to 40%,” explained Jim Kean, CEO of digital health company Molecular You, which has developed an affordable metabolic and proteomic screening test that can alert individuals to health problems such as early-stage cancer.

This is an admirable goal and there is no doubt digital healthcare innovation can go some way to making it happen, but whether challenges such as limited system interoperability; payer, investor, and regulator caution; and healthcare provider education and uptake can be overcome in time remains to be seen.

The promise of digital health

“The promise of digital health is the ability to rethink many aspects of healthcare delivery,” said Ariel Stern, an associate professor in the Technology and Operations Management Unit at Harvard Business School, who has a research focus on digital health.

“From a health equity perspective, instead of forcing patients to come into a physical building and location, we’re able to meet them where and when it’s convenient for them,” explained Carmody.

Uses of digital tools and technology in healthcare are broad and continually expanding, ranging from making time for clinicians and nurses by automating admin tasks to monitoring patients in their homes, as well as predicting and improving outcomes for different patient groups.

UPMC is a large health care provider and insurer in the state of Pennsylvania, operating 40 hospitals and more than 700 doctors’ offices and outpatient centers. During the last decade, Carmody and team have developed several different digital tools and models to help improve patient care at UPMC.

These include a predictive model that can assess a patient’s risk of undergoing a given surgical procedure in advance and another model that can predict the probability that a patient will be readmitted to the hospital in 7 or 30 days.

“This model changes how we intervene with that patient in terms of sending them home with the care managers. They will take different steps to help keep that person on the path to wellness and recovery and to not have them come back into the hospital,” explained Carmody.

“We’ve seen tremendous improvements across all of our hospitals because of that data, because of those insights that our very brilliant physicians and researchers and data scientists have developed to identify those situations.”

Canadian biotech company Molecular You is providing a combination of lab testing and digital health tools. Customers can have an inexpensive blood test that assesses 250 proteomic and metabolomic biomarkers that are linked to disease risk. They are then provided with risk scores and advice via one or more telehealth appointments and are given access to relevant health and fitness information.

“One of our longtime subscribers has had a test every year. On her most recent test, she had a risk profile of stage one pancreatic cancer… We caught it, it was stage one, and she had three little lesions so she could have laparoscopic surgery. After the surgery, we reran the tests and the biomarkers have returned to normal levels,” said Kean. “You have to think about what that implies for the health system. It means that everybody, every year should get a cheap, broad-based screen.”

Verily, formerly Google Life Sciences, is owned by big tech company Alphabet and combines tech and life science knowledge and research to create new health solutions. It has developed a number of different products, including Dexcom G7 continuous glucose monitors, in collaboration with Dexcom, and Onduo, a chronic disease management platform for patients with diabetes, developed in partnership with Sanofi.

Erich Huang is head of clinical informatics at Verily and was instrumental in developing Onduo. “The issue with traditional health care is that interactions with your patients are pretty sparse, so even if someone is seeing a primary care doctor or an endocrinologist on a somewhat regular basis, that’s only going to be a few times a year, whereas chronic disease is a disease of every day,” he emphasized.

“A lot of those important signals and interactions are unaccounted for and we need to actually figure out ways to get in there to start discovering that space and discovering our opportunities there.”

Regulating and paying for digital products

Digital health products fall into a difficult area from a regulatory perspective. Arguably, products or technology used to monitor people’s health or treat disease should be regulated like a medical device or drug to ensure they are safe for people to use. However, current regulatory systems in many countries are not set up to regulate software or applications in a timely and effective manner.

“The way we define medical devices in the United States goes back to an act of Congress from 1976, and in 1976 we just simply weren’t thinking about software as a medical device,” explained Stern.

“It matters because we’ve statutorily defined medical devices with such a broad definition, that many of our digital health tools meet the legal definition of a medical device or diagnostic. Therefore, many, but not all, of these tools will fall under the umbrella of being devices that are overseen in some way by the FDA.”

Regulators are moving slowly in the right direction. In 2019, Germany brought in a combined system (DiGa) for assessment, approval and reimbursement of digital health applications, which is designed with fast moving digital health companies in mind, and France and Belgium have recently brought in similar systems.

“Going forward, we absolutely need to think more about how we update regulations in the United States to keep pace with innovation and what we actually want to be doing both in clinical research and practice,” said Stern.

“The FDA is being quite thoughtful, but we will need new regulatory authorities at some point in time that are more fit for purpose for digital technologies and for software in particular.”

Micky Tripathi is National Coordinator for Health Information Technology at the Office of the National Coordinator for Health Information Technology (ONC) in the U.S. The ONC forms part of the Department of Health and Human Services and its main task is to promote and oversee development of a national health information technology infrastructure.

“Our rules require that by the end of last calendar year, December 31, 2022, every certified electronic health record vendor, which covers 97% of hospitals and over 80% of Ambulatory providers, were required to make available to their customers a standard API, a standard interface based on modern interoperability principles,” said Tripathi.

Although there is still a way to go before there is true interoperability between providers in the U.S., this program and related schemes such as the Trusted Exchange Framework and Common Agreement (TEFCA) are definitely a step in the right direction.

“For all the great activity we’ve seen, we should really start to look back and see 2023 as an inflection point, because that’s when that foundation was built that’s going to provide the opportunity for more apps to come in and build those scalable technologies,” added Tripathi.

Another challenge for the digital health field, once regulation is addressed, is who is going to pay for the tools that are being developed. “Getting an FDA approval doesn’t mean that anybody agrees to pay for it,” explained Kean, although he acknowledged that it can help.

Kean previously worked at Blue Cross Blue Shield and has drawn on the expertise of ex-colleagues to gauge how likely the insurer would be to pay for Molecular You’s tests. “They looked at what we had, and they said, “Well, this would be pretty breakthrough. It’s more predictive than anything we have, and it would completely change our actuarial tables, but it’s not approved so we’re not going to talk to you yet.”

Despite this, Kean says that many insurers are keen to move toward a more preventive and value-based system to help reduce healthcare costs. He explained that in any given year 3% of the population is going to cause 25% of the expense in the healthcare economy and anything that can help predict who these people might be is very valuable for payers.

“The thing that’s holding back doctors on value-based care is they just get a flat payment per year … that’s based on an average payout and if they have a sicker than average population, they may end up eating a lot of money and getting into financial distress,” he noted.

“We’re actually a good tool for that, because what we’ll propose after we get approved will be to test every single patient once a year. That will accurately stratify the risk for the next 12 months. Then you can go to the CMS and say, “My population is sicker than average and I can prove it.”

What’s next for digital health?

Although the excitement about digital health during the pandemic is dying down, it has not completely gone away. Like many other healthcare providers, UPMC saw a massive increase in telemedicine consultations during the pandemic from approximately 12,000 in the 6 months prior to the pandemic to 10,000-12,000 per day. This has decreased somewhat but use remains high at around 6000-8000 consultations per day, according to Carmody.

New technologies continue to be developed at a fast pace and innovations such as generative AI and machine learning (ML) are improving the accuracy and scope of existing digital health tools and helping to create new ones. They are also helping drive a slow move towards value-based care in the U.S.

High quality data is and will continue to be key for implementation of accurate and equitable digital health tools. “Data is the common denominator that links precision medicine and digital health. Large volumes of deep, representative, and context-specific data combined with advanced analytics, AI, and ML enable us to detect meaningful variations at the genomic, physiological, or other levels that influence the potential effectiveness of therapy,” said Meghan Dierks, Chief Data Officer of Komodo Health.

Real world data, which is collected from a variety of sources including wearables and other remote monitoring devices, is becoming increasingly relevant for both precision medicine and digital health. The collection and analysis of such data is a focus for Komodo.

“Wearable devices or home-based environmental digital sensing technology captures millions of physiological or activity-based response variables under real-world conditions. In the context of clinical trials, patients use other digital health technologies to self-report outcomes, health status, or mood, which can be vital in identifying heterogeneity or subtle differences in treatment effects or side effects of investigational therapies,” said Dierks.

Of course, challenges remain about how best to use the new technologies that are now available. Stern and her colleague and doctoral student Mitchell Tang caution that as remote monitoring devices are rolled out more widely, it is important to use them sparingly.

“If we’re taking a very blanket approach to the provision of remote patient monitoring, or any digital tool, what we could end up with is evidence that suggests remote patient monitoring is not effective. But it could be extraordinarily effective for a subset of patients and cease to be effective for other patients, once their medications are well calibrated,” explained Stern.

Another consideration that currently stands in the way of wider rollout is lack of healthcare provider knowledge about digital health tools and their uses. “Most doctors finished their medical training before the iPhone existed,” she adds. “I think that’s a very real barrier.”

Huang notes that data empathy, or data reflective of people and their needs, is just as important as data quality. For example, pulse oximetry technology has saved many people, but is inaccurate in people with darker skin. Thinking about the oximetry data for the population as a whole and asking questions about accuracy at an earlier stage could have helped a lot of people sooner.

He emphasized the importance of two-way communication when designing digital health solutions. “You shouldn’t be just sending information to a patient and not know whether that information was useful to them. Making that feedback loop and allowing software and data to talk to you and talk to the patients in a conversation, as opposed to a unidirectional flow, I think that’s going to be a really important part of how we do things,” he added.

“I think what we’re increasingly seeing are hybrid approaches where we’re augmenting traditional health care delivery with tools that help patients, like with medication management adherence,” said Stern.

Carmody agreed, adding that digital solutions are not always needed. “We can’t just assume that digital solutions are going to solve every problem… we have to be flexible, we have to be available for different types of care, the more traditional care where people do want to come into a physician’s office and see a doctor and have that experience.”

Helen Albert is senior editor at Inside Precision Medicine and a freelance science journalist. Prior to going freelance, she was editor-in-chief at Labiotech, an English-language, digital publication based in Berlin focusing on the European biotech industry. Before moving to Germany, she worked at a range of different science and health-focused publications in London. She was editor of The Biochemist magazine and blog, but also worked as a senior reporter at Springer Nature’s medwireNews for a number of years, as well as freelancing for various international publications. She has written for New Scientist, Chemistry World, Biodesigned, The BMJ, Forbes, Science Business, Cosmos magazine, and GEN. Helen has academic degrees in genetics and anthropology, and also spent some time early in her career working at the Sanger Institute in Cambridge before deciding to move into journalism.

The post The Digital Pathway to Widespread Precision Medicine appeared first on Inside Precision Medicine.

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The first AI-designed drugs have ended with disappointment.

Over the last year-plus, the first handful of molecules created by artificial intelligence have failed trials or been deprioritized. The AI companies behind these drugs brought them into the clinic full of fanfare about a new age of drug discovery — and have quietly shelved them after learning old lessons about how hard pharmaceutical R&D can be.

Earlier this month, UK-based Exscientia slipped into a pipeline update that a Phase I/II study of its cancer drug candidate EXS-21546 was winding down. That cut followed a decision last year by its partner Sumitomo Pharma to abandon another of its AI-designed drugs. In April, a test of BenevolentAI’s dermatitis drug fell short as well. And Recursion Pharmaceuticals — the third of AI’s early generation — hasn’t recorded a trial failure but has had a handful of clinical setbacks that don’t necessarily bode well.

There’s no shortage of AI naysayers, and the 0-for-3 start suggests that AI hype has set unrealistic expectations. Clinical wins are rarities in biotech, where an estimated 5% or 10% of drugs that head into human testing actually get approved.

“If you take the hype and PR at face value over the last 10 years, you would think it goes from 5% to 90%,” Patrick Malone, a principal at KdT Ventures, said of AI. “But if you know how these models work, it goes from 5% to maybe 6% or 7%.”

These three companies have been at this for roughly a decade, combining to rack up an accumulated deficit of over $1.5 billion.

Ivan Griffin

The reality check of the clinic, paired with a dour biotech market, has beaten up these first-generation biotechs that went public in 2021 or 2022. Their stock prices are all down at least 75%, underperforming the biotech market, even as new AI startups have continued to raise substantial sums of money. Generate:Biomedicines, Inceptive, Iambic and Genesis, for instance, have combined to raise $673 million over the past few months.

Executives at these first-generation companies say it’s too early for a verdict on whether or not AI boosts the odds of success, particularly given the vast likelihood that any drug candidate — AI-developed or not — will fail.

“The things that are easiest to show — speed and cost, particularly on the preclinical — have been done,” Ivan Griffin, BenevolentAI’s co-founder and chief operating officer, said in an interview with Endpoints News. Increasing the probability of success “will inevitably take the longest to prove out.”

Milestone moments to quiet cancellations

Back in the final days of January 2020, as Covid-19 was emerging as a pandemic threat, Exscientia CEO Andrew Hopkins hailed a “key milestone in drug discovery.”

His biotech announced the first AI-designed drug had entered the clinic. Its partner Sumitomo led the Phase I study in obsessive-compulsive disorder, with the Financial Times calling the trial’s start a “critical milestone for the role of machine learning in medicine.”

About two years later, in January 2022, Sumitomo disclosed they had abandoned the drug, which failed to meet the study’s criteria. In an interview, Hopkins said Exscientia’s job was to just design the molecule, with Sumitomo making the clinical decisions.

Exscientia had more control over the next drug, a cancer treatment called EXS-21546, which it brought into the clinic in December 2020. Earlier this month, the biotech said it was discontinuing an ongoing Phase I/II study with modeling suggesting “it will be challenging for ‘546 to reach a suitable therapeutic index.”

Andrew Hopkins

Hopkins said that the trial didn’t fail, as the biotech doesn’t have full results back.

“It wasn’t a clinical data decision,” he said. “It was a strategic decision” to prioritize two other cancer drugs that the company believes have better chances.

“We don’t want to be one of those companies that keeps pushing a program forward because it’s the only thing they have,” Hopkins said.

Clinical failure is less contestable for BenevolentAI, a fellow UK-based AI enthusiast whose lead drug was unable to beat a placebo in a Phase IIa atopic dermatitis study, the biotech announced earlier this year. That readout led to the drug’s end, a stock plunge, and sizable layoffs.

Recursion stands apart as the only one of the three to maintain a valuation above $1 billion today. (Exscientia is worth about $650 million, while BenevolentAI is valued at $117 million.)  The biotech has had several positive Phase I readouts centered on safety and tolerability, such as a C. diff drug recently clearing a healthy volunteer study of 42 people. The company used AI to identify existing compounds rather than design new drugs for its early pipeline.

Dylan Reid

“The market has never known what to make of these companies,” said Dylan Reid, a partner at Zetta Venture Partners. “They’ve been way too excited and way too down. At one point, they value the platform at X billions of dollars, and today, it’s probably a drag on valuation.”

While Recursion hasn’t had a clinical failure, its development plans have had hiccups. It quietly dropped a rare disease drug last year, citing “noise in the potency” and delays in getting a trial going. Earlier this month, the Salt Lake City-based biotech slimmed down an ongoing Phase II study for another of its drugs, dropping a placebo arm and cutting expected enrollment to 37 people. A spokesperson said the changes will help get to data and Phase III faster.

If a decade sounds too soon to judge these biotechs, consider Recursion’s leaders set that timeline themselves, publicly declaring the goal of discovering 100 clinical-stage drug candidates in its first 10 years. Roughly 10 years on, Recursion’s pipeline has four clinical-stage molecules.

Recursion expects two Phase II readouts in the second half of 2024. All three biotechs have ongoing partnerships with drugmaking giants like Merck, Bristol Myers Squibb, and Roche’s Genentech.

The AI clinical pipeline is full of other players as well, such as Verge Genomics’ ALS drug, BPGbio’s brain cancer treatment, Insilico Medicine’s idiopathic pulmonary fibrosis drug, Generate:Biomedicines’ Covid-19 antibody, and Auransa’s liver cancer therapy.

Strategies evolve as more players emerge

AI backers say successful programs like Moderna’s Covid-19 vaccine or Nimbus Therapeutics’ TYK2 inhibitor used AI to a degree. But those drugmakers don’t brand those medicines as AI-designed, while Exscientia, BenevolentAI, and Recursion market their approach as AI-driven or AI-enabled.

A decade in, leaders of the first-generation companies say they are still learning.

BenevolentAI, for instance, says its failed atopic dermatitis drug candidate didn’t use the company’s target identification approach, which is behind its ulcerative colitis drug that entered the clinic earlier this year.

Exscientia has incorporated more human tissue samples in its research process and hired experienced clinical hands like Michael Krams, Hopkins said.

“We’ve also now realized if we want to change the probability of success in the clinic, it’s not just better molecules,” Hopkins said. “We also need better translational models.”

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Australian equity investors enamoured with the study of consumer behaviour might take an interest in the cycling industry, especially as it impacts the ASX-listed Flight Centre (ASX: FLT).

To many, including those in the cycling industry itself, the surge in demand during the pandemic was a complete surprise. What happens next might offer important insights into many retail sectors beyond cycling.

The cycling industry in the U.S. and worldwide was once a hubbub of frenzied activity and an intense boom between 2020 and 2022. Today, however, the industry seems to be taking a “big exhale,” as some industry insiders have remarked. Experts had anticipated a decline after the pandemic-inspired boom, but its duration and magnitude remain uncertain.

The global pandemic sent shockwaves across various sectors, with bicycle retailers experiencing unprecedented turbulence. Once familiar with the annual rhythms of a seasonal business, bicycle stores suddenly faced an overwhelming surge in demand, dwindling product availability thanks to fractured supply chains, and a daily grind (pun intended) defined by unpredictability (Figure 1.).

Figure 1. June 2020 year-on-year sales performance of key bike categories

Source: The NPD Group

And Figure 1., reflects the surge in sales in the first few months of the pandemic, which continued for nearly two more years.

Three years after this unpredictable surge, its aftermath, as revealed by Figure 2., is still evident. As the industry gradually transitions back to what feels like “business as usual”, the landscape of the industry has evolved significantly.

Figure 2. Real U.S. personal consumption expenditure on bicycles and accessories ($U.S.)

Fresh faces entered the market, while established giants took audacious steps that garnered varied responses. Retailers who ventured into stockpiling and digital commerce at the pandemic’s onset reaped exponential revenue growth. In contrast, those who couldn’t adapt swiftly often struggled with the sudden and overwhelming demand.

In an email to customers and investors, niche Denver-based brand, Rodeo Labs, offered insight into the most recent reverberations in industry dynamics, noting, “we’re operating in one of the least settled periods in the bike industry”.

The most recent tumult became evident in late 2022, a time which typically sees a seasonal slowdown due to the onset of colder, darker winter months in the northern hemisphere. For Rodeo Labs, the question as to whether they would face the same challenges as larger companies in the industry was answered by early summer, when “there was a palpable decrease in energy in the global bike party.”

The shift wasn’t limited to bike sales. Major cycling events, once selling out almost instantly, are witnessing slower registrations. The once-popular trend of large group rides seems to be making way for smaller, more intimate rides, with many participants even opting for other activities entirely.

Reflecting on this change, Rodeo Labs observed, “I think there just isn’t as much interest in ‘events’ as there was in previous years. People seem less inclined to spend money to go on a ride with a bunch of other people than they were 12-24 months ago.” Sponsored athletes also seem to be moving away from events, with many focusing more on other careers.

With the cycling community seeing significant shifts, bike companies are grappling with the change. “In the next six months, you’re going to see a number of bike companies fail,” an industry representative reportedly shared with Rodeo Labs earlier this year. Denver recently bid farewell to Guerilla Gravity brand, a promising brand that showcased the feasibility of scaling bike production in the U.S. While the exact reasons remain undisclosed, many brands have faced challenges with inventory and financial constraints, a fact that has become a subject of industry talk.

And that talk is not restricted to the U.S.. Here, in Australia, booming COVID sales were also met with a shortage of stock and furloughed manufacturing in Taiwan. Massive orders were submitted to meet the demand, but those orders are only being delivered now, when demand has slumped.

The Australian Financial Review (AFR) recently reported the value of Brisbane-based 99 Bikes-owner Pedal Group, which is unlisted and 47 per cent owned by Flight Centre, 22 per cent owned by Flight Centre CEO Graham Turner and 15 per cent owned by his son Matt, has “almost halved since the peak of cycling mania during the coronavirus pandemic, as an oversupply of bicycles bites.”

After generating earnings before interest and tax (EBIT) of $51.6 million in 2021 and $18.7 million in 2022, as pandemic lockdown orders triggered massive demand for bikes, Pedal Group posted EBIT of $5.5 million in the 2023 financial year and an overall loss of $12.4 million.

According to documents seen by the AFR, Pedal Group is now valued at about $127 million, following a planned issue of equity to staff at $5.18 a share, which is down materially from $10.73 a share in November 2021.

Consumer bicycle buying behaviour through the pandemic and following its conclusion, is reflected across a range of leisure equipment industries. The extent to which operators can cancel orders made during the height of the buying boom will determine, in many instances, who survives. Those that do will reap the rewards not only of a return to stable conditions but also a larger share of the market.

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