What happened in health care technology this week – and why it’s important.
Papa and Uber Health team up on curbing social isolation among seniors
Senior assistance company Papa is partnering with Uber Health to provide transportation and decrease social isolation among seniors. As reported by Emily Olsen in MobiHealthNews. The collaboration with Uber will allow Papa’s care team to work with Pals and seniors to get rides to medical appointments and other events and find transportation for running errands.
Why it’s important – Transportation generally can be a challenge for older adults, especially if they can’t drive. A report from the National Academies of Sciences, Engineering, and Medicine found nearly one-fourth of adults age 65 and older are considered to be socially isolated. That can have serious health risks, including an increased risk of premature death and dementia.
Quris combines AI with ‘patient on a chip’ to speed drug development and reduce animal testing
The necessity of animal testing is a sad one for the process of drug discovery. Still, there’s seemingly no reasonable alternative to mice, even though they’re not particularly accurate human analogs. Devin Coldeway reports on an alternative in his article on Tech Crunch. Quris claims to have the first real option in its combination of AI with data from a “patient on a chip” that provides remarkably robust testing and automation, all at a considerably lower cost — no mouse required. The Israel-based company’s approach builds on a major study at Harvard concerning the use of so-called “organs on a chip.” These systems, still relatively new but established in the field, use a small amount of stem cell-derived tissue (“organoids”) as a testbed for drugs or treatments — providing a good idea of how, for example, a human liver might respond to a combination of substances.
Quris, which will initially focus on uncommon genetic illnesses that cannot be modeled in animals, has said that it is preparing the platform’s first medicine for clinical trials in 2022. The first Quris medication is intended to treat Fragile X syndrome (FXS), the most prevalent genetic cause of autism and intellectual disability worldwide.
“It’ll no longer be just doing expensive experiments for pharma companies. In five-10 years time this may well be what hundreds of millions of people are doing.”
Isaac Bentwich, CEO and co-founder, Quris
Why it’s important – The basic idea makes perfect sense: build a better small-scale simulation of a human body and use it to gather data that a machine learning system can easily interpret. Considering drug candidates can cost hundreds of millions to get to the clinical stage, it’s more than worth spending even a small fortune (think tens of millions) to weed out a few destined for failure. If the technique is accurate — and indications are that it is — then the risk is practically nil, and it will pay for itself if even a single expensive dead-end is avoided.
DarioHealth launches MSK platform Dario Move
Digital therapeutic company DarioHealth is launching a digital, physical therapy and musculoskeletal (MSK) care platform dubbed Dario Move. As reported by Emily Olsen in MobiHealthNews, Dario Move includes a biofeedback sensor, real-time feedback and support from physical therapists and coaches, and personalized exercise programs designed by therapists.
Why it’s important – Musculoskeletal conditions are the leading contributor to disability worldwide, affecting about 1.71 billion people, according to data compiled by the World Health Organization. Physical therapists are also in demand; the Bureau of Labor Statistics reports the employment of physical therapists is expected to grow 21% between 2020 and 2030.
In a First, Surgeons Attached a Pig Kidney to a Human, and It Worked
Surgeons in New York have successfully attached a kidney grown in a genetically altered pig to a human patient and found that the organ worked normally, a scientific breakthrough that one day may yield a vast new supply of organs for severely ill patients. The New York Times’ Roni Caryn Rabin reported on research being conducted at N.Y.U. Langone Health where surgeons, with the family’s consent, attached the pig’s kidney to a brain-dead patient who was kept alive on a ventilator and then followed the body’s response while taking measures of the kidney’s function. It is the first operation of its kind.
The transplanted kidney was obtained from a pig genetically engineered to grow an organ unlikely to be rejected by the human body. In a close approximation of an actual transplant procedure, the kidney was attached to blood vessels in the patient’s upper leg, outside the abdomen.
“This is a huge breakthrough. It’s a big, big deal.”
Dorry Segev, M.D., Professor of transplant surgery at Johns Hopkins School of Medicine
Why it’s important – As reported, a steady supply of organs from pigs — which could eventually include hearts, lungs, and livers — would offer a lifeline to the more than 100,000 Americans currently on transplant waiting lists, including the 90,240 who need a kidney. Twelve people on the waiting lists die each day. An even larger number of Americans with kidney failure — more than a half-million — depend on grueling dialysis treatments to survive. In large part, because of the scarcity of human organs, most dialysis patients do not qualify for transplants, which are reserved for those most likely to thrive after the procedure.
Many questions remain to be answered about the long-term consequences of such an operation. While the procedure will not be available to patients any time soon, as there are significant medical and regulatory hurdles to overcome, this is a big advance for xenotransplantation.
VR treatment for lazy eye in children gets FDA approval
Nicole Wetsman’s article on The Verge reported on the recent FDA approval of a virtual reality-based treatment for children with the visual disorder amblyopia, or lazy eye. Patients watch modified TV shows or movies through a virtual reality headset to improve their vision. Luminopia’s approach uses TV and movies to develop the weaker eye and train the eyes to work together. Patients watch the show or movie through a headset that shows the images to each eye separately. The images shown to the stronger eye have lower contrast, and the images are presented with overlays that force the brain to use both eyes to see them correctly.
Why it’s important – Around 3 percent of children have amblyopia, which develops when the brain and eyes stop communicating correctly. The brain favors one eye, which leads to vision problems in the other eye. It’s the leading cause of vision problems in children. The authors of the clinical trial wrote that they think that the option to pick popular videos might be one reason users stuck to the program — people followed the treatment plan 88 percent of the time. Less than 50 percent of patients adhere to eye patches or blurring drops.
Machine Learning Can Make Lab Testing More Precise
In his blog this week, Dr. John Halamka, President of the Mayo Clinic Platform, highlighted work being done to move beyond standard lab value ranges to personalize lab testing. Almost every patient has blood drawn to measure a variety of metabolic markers. Typically, test results come back as a numeric or text value accompanied by a reference range representing normal values. If the total serum cholesterol level is below 200 mg/dl or serum thyroid hormone level is 4.5 to 12.0 mcg/dl, clinicians and patients assume all is well. But suppose Helen’s safe zone varies significantly from Mary’s safe zone. If that were the case, it would suggest a one-size-fits-all reference range misrepresents an individual’s health status. That position is supported by studies that found the distribution of more than half of all lab test results, which rely on standard reference ranges, differ when personal characteristics are considered.
“In the ‘era of big data and analytics,’ it is almost unconscionable that we still use ‘normal reference ranges’ that lack contextual data, and possibly statistical power, to guide clinicians in the clinical interpretation of quantitative lab results.”
William Morice, M.D., Ph.D., chair of the Department of Laboratory Medicine and Pathology (DLMP) at Mayo Clinic and president of Mayo Clinic Laboratories
Quoting from the blog post: “With these concerns in mind, Israeli investigators from the Weismann Institute and Tel Aviv Sourasky Medical Center extracted data on 2.1 billion lab measurements from EHR records, taken from 2.8 million adults for 92 different lab tests. Their goal was to create “data-driven reference ranges that consider age, sex, ethnicity, disease status, and other relevant characteristics.” To accomplish that goal, they used machine learning and computational modeling to segment patients into different “bins” based on health status, medication intake, and chronic disease. That, in turn, left the team with about half a billion lab results from the initial 2.8 million people, which they used to model a set of reference lab values that more precisely reflected the ranges of healthy persons. Those ranges could then be used to predict patients’ “future lab abnormalities and subsequent disease.”
Why it’s important – This approach offers the potential to diagnose certain diseases much earlier and helps clinicians determine more effective therapies at the N of 1. It also opens the door to things like more equitable organ transplant risk calculations, early identification of cardiac risk, and more. Really impressive stuff!