Though humans can offer a caring bedside manner, there are some skills machines excel at. And they may benefit you more than you know.

From accelerating data processing to developing life-saving drugs to analyzing imaging, AIs possess skills human brains can’t compete with. But that doesn’t mean human doctors will be out of a job. They’ll just work with machines to help us get better faster.

LISTEN TO THE DEEP DIVE:

IT’S A CLINICAL THING

Drug development is an exhausting amount of trial and error, with researchers spending years developing and analyzing data. The potential for failure looms at every step. And then there’s the seemingly endless process of testing and acquiring approval to get it on shelves. The process can take up to 15 years.

If there’s anything COVID-19 has taught us, it’s that drug development needs to be safe and effective, but it also needs to be speedy. New developments in AI are poised to reduce the waiting game.

A 2023 study led by Rizwan Qureshi from Hamad Bin Khalifa University in Qatar suggests AI can assist drug development at every stage. With an average price tag of U.S.$2.5 million to bring a drug to market, this is good news. After all, time is money.

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How much money? AI could save U.S.$70 billion in the drug-discovery process by 2028, according to Bekryl Market Analysts.

And investment bank Morgan Stanley says the pharmaceutical industry might spend U.S.$50 billion a year on AI within 10 years.

One way AI is improving the process is in drug design.

Antibody designs at the beginning of the drug-development phase are normally built on existing designs or data. AI, however, can do this from scratch. This is called zero-shot.

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Absci in 2023 became the first company to develop a zero-shot generative AI model with its de novo (new) antibody designs via computer simulation. Its antibodies are crucial segments of a drug used to treat breast cancer.

Although the technology is new, Absci says it could cut the time it takes to get a drug to market by up to two years.

The company has introduced a pipeline of projects on its website after opening an innovation center in Switzerland focused on dermatology, inflammatory bowel disease and immuno-oncology.

“Our wet lab can experimentally validate the candidates that work right out of the computer – without the slow and costly step of lead optimization. This potentially reduces the time it takes to get new drug leads into the clinic, while unlocking treatments for traditionally ‘undruggable’ diseases and improved therapeutic possibilities for many others,” according to Absci’s website.

Absci is only one of many drug developers using AI to move research along. As of the last quarter of 2022, a survey by global management-consulting firm McKinsey and Co. concluded there are close to 270 companies working in the drug-discovery market, some partnering with large biopharma companies. The survey also concluded that using AI accelerates the generations of protein structures by 100 times and image screening and analytics by 10 times.

But what about the diseases these drugs are designed to treat?

DIAGNOSTICS AND EARLY DETECTION

It can take medical specialists decades to acquire diagnostic skills. Typically, these skills come from experience. It’s the same for AI – it has to learn from somewhere. Using computerized records, machine learning can interpret data based on patterns in a database as long as there are lots of samples and they’re neatly digitized and organized.

The main difference between the well-trained human eye and the AI, however, is that the AI can interpret data in seconds.

AI algorithms that are trained to examine X-rays, CT, and MRI scans can in virtually no time find, identify and classify tumors and offer information about a potential growth rate and risk of metastasis.

Furthermore, AI could produce a health-risk score based on lifestyle, health and predisposal aligned with genetic data, using blood work and imaging to warn before a disease becomes medically significant.

One such risk, infection, can lead to life-threatening sepsis and is considered the second-most cause of death globally.

Although anyone can get sepsis, it has a genetic component. And researchers hope AI can help to identify the missing markers in the research.

Asrar Rashid, acting chairman of pediatric services at NMC Royal Hospital and head of the Department of Pediatric Critical Care in Abu Dhabi, has spent many years treating babies and children with sepsis, often too late to help them, so he’s excited about the clinical benefits of AI.

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Rashid’s Ph.D. focuses on finding the missing piece of the genetic puzzle. He published a 2009 paper that concluded it was difficult to find a pattern and thus link genetics to predisposition to sepsis.

Fast forward to 2023 and with the help of AI, he’s made headway finding a pattern in the DNA chaos.

Because AI can process thousands of pages of historical data, find patterns within and allow for use of techniques in which he can look at genes in a novel way, Rashid has found insight into the underlying mechanisms of complex biological systems.

“Our work at NMC Royal Khalifa, for the first time, moves medical practice from one-point to potentially two-point biomarking (triangulation),” Rashid tells KUST Review.

This means there is only a third point left to uncover to complete the triangle. “A novel contribution is the fact that we can use changes at the level of the genes to give clues about the dynamic landscape of cellular processes. If we can affect change at the level of the gene, this might be more useful to the patient, for example, by minimizing sepsis damage to the organs,” he adds.

AI AND PATIENT MANAGEMENTT

The pandemic taught us when a crisis arises on a global scale, streamlining processes and simpler tasks frees health-care workers to tend to more critical situations. And hospitals and clinics all over the world are adopting AI to meet these challenges.

For example: medical concierge service Forward’s AI diagnostics.

At Forward’s tech-driven clinics, subscribers check themselves in on an iPad and get a 3D body scan. Algorithms interpret the data before the patient reaches a physician.

A touch-screen panel can record your discussion with your physician, eliminating the need to take notes.

A high-tech tongue depressor can check blood pressure, temperature and heart health in under a minute, with the information immediately added to your file in the cloud.

IMAGE: Freepik, AI generated

Tools for mental health

AI is also making its mark in the world of mental health.
“Using ethically trained AI models, we can empower clinicians to observe invisible biomarkers that signpost different mental health conditions, in the same way that a blood test or ECG might be used to detect and monitor physical health conditions,” says Gabrielle Powell, COO and co-founder at Thymia. Read more›››

Thymia provides gaming technology that collects voice, behavior and video data to help diagnose mental illnesses such as anxiety and depression. The AI processes such data as reaction times, error rates and how the keys on the gaming controller are used.Thymia is rolling out its tools across several global mental-health settings. It is also developing a tool to help diagnose cognitive illnesses like Parkinson’s, Alzheimer’s and ADHD, Powell tells KUST Review.

“We’ve been using the same tools to diagnose and treat mental health for decades. AI has the potential to radically improve the speed and accuracy of mental-health diagnoses, making it far easier for patients to get the right help,” Powell says. “There’s so much room for improvement in mental health-care systems globally – and the right tech tools, when deployed responsibly and ethically, have immense potential to improve how care is delivered.”

But the team at Thymia is clear the tech is meant to assist, not replace, the mental-health professional: “The way we work with clinicians is as a support tool; we support them to decide if intervention is required and to identify the most appropriate intervention,” Powell says.‹‹‹ Read less

All of your health data is accessible via Forward’s app and is intended to work in a preventative, rather than a reactive manner — recording wearable devices that track behaviors, offering DNA analysis for predispositions and allowing for health-care professionals to monitor conditions around the clock.

Forward’s website refers to these clinics as a “stepping stone.”

If Forward co-founder and CEO Adrian Aoun has his way, medicine will be viewed as a product rather than a service, all thanks to another service, his “Doc in a box.”

Aoun’s CarePod looks like a modern photo booth. Step inside the 2.5-square-meter box, choose from a menu of requests, get scanned, and out pops a diagnosis and a plan of action or prescription. Though skepticism abounds, Forward recently raised U.S.$100 million to bring 25 CarePods to U.S. malls.

“You walk up to it and unlock it with your phone. You choose something like the body scan app and it actually spins you around in a circle and takes a whole bunch of readings, then shows you the results and gives you any treatment you need, a prescription or a plan,” Aoun tells Fierce Healthcare.

A cloud AI filing system is a data-rich industry’s dream. With medical records at their fingertips, and devices that provide instant medical test results, doctors can make timely decisions based on history and AI can determine the patient’s likelihood of response to different drugs.

PATIENT HOMECARE

But if you’d rather enjoy the comfort of your living room, Nader Abu Yaghi, director of NMC ProVita Homecare in Abu Dhabi, says his aim is to revolutionize homecare with AI.

AI within the sector is in its infancy, Yaghi says, but there are systems aiming for release in 2024 that could make homecare easier, safer and less costly.

NMC ProVita Homecare is developing an AI-powered system to remotely monitor patients’ vitals and activity levels and allow for early intervention. It could monitor, for example, diabetic patients’ blood sugar levels.

AI systems are also being developed to manage chronic conditions. This might mean personalized diets, exercise programs and medication, and creating treatment plans.

These proactive monitoring and personal-care systems in testing reduced hospital readmission rates by 15 percent and the cost of care for homecare patients by 6 percent.

“AI is a powerful ally for our telemedicine efforts,” Yaghi says. “It (telemedicine) is essential for our hospital’s home-based patient-care strategy, as it allows us to reach and serve patients in their homes directly. It is especially important for maintaining continuity of care and providing access to health-care services for patients who cannot travel to the hospital.

“AI also helps manage patient schedules and follow-ups by optimizing appointment times and ensuring regular monitoring. This is particularly important in a homecare setting, where consistent engagement and timely intervention can have a significant impact on patient outcomes,” he adds.

IT’S ALL ABOUT THE DATA

Data-rich industries like health care are primed for AI development, but the data is just the first step, says Dirk Richter, director of health innovation at Abu Dhabi’s Department of Health.

The Department of Health has spent the past three years creating a central health-information exchange system called Malaffi — Arabic for ”my file”— containing essential patient records for the emirate’s medical system. No matter which medical facility patients enter across the country, their data will be accessible.

This means a full history, emergent care, routine check-ups, test results and scans, without having to tell your medical history again and again.

Included is an app to see your own reports and everything that’s happening, Richter says. This offers peace of mind to a patient, convenience to both doctor and patient and saves money by avoiding duplication of costly scans or tests. It also includes such features as predictive patient-risk profiles.

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With the influx of AI devices, it’s important to choose the right tools. Based on a newly issued policy, the Department of Health has established a health technology assessment team that applies an AI algorithm against global data for the safety and effectiveness of AI medical tools, treating all new tools as they would a new drug.

Medical establishments will be obliged to use them so that insurance coverage is factored in. After all, there’s no point in adopting these tools if they aren’t being used because people can’t or won’t pay for their use. “Otherwise, it’s like they don’t exist,” Richter says.

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Already, the Department of Health is using advanced imaging algorithms, assisting physicians who may have spent a full day looking at hundreds of scans. Algorithms are also helping ophthalmologists to determine at what stage of diabetes a patient might be by reading retinal scans. And AI assistive technology is analyzing images taken during colonoscopies to spot abnormalities or tumors that the person performing the procedure might not see.

All AI diagnoses are dependent on the data AI has learned from, so big data is essential.

Richter says several research and development centers are underway and partnerships have been formed to further the Department of Health’s AI innovation. Universities and research establishments, including Khalifa University, continuously apply for grants.

Though Richter’s role is AI- and technology-focused, he believes these tools will bring patients and physicians together, creating more time for communication, which can also be considered important data in diagnostics.

“So a radiologist, instead of spending two hours looking at chest X-rays every day could spend their time talking to the patient who really has important findings in their X-ray,” he tells KUST Review.

THE POWERHOUSE COUPLE

But just as there are things human brains can’t do, there are things humans can do that AI can’t — like express true human emotion.

Not to mention, doctor-patient relationships foster trust. But that trust is based on positive interactions over time.

According to 2022 data from patient-engagement platform PatientPoint, the typical waiting time once a patient enters the office for a doctor’s appointment is 26.2 minutes. This waiting time is mainly due to the volume of patients and administrative tasks that might be done instead by AI.

Given that doctors are typically allotted 15 minutes for patient interaction — comparable to an assembly line — letting AI handle triage and admin work could allow a doctor to become a doctor again with time to listen, hear pertinent information, empathize and strategize with a patient.

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A 2023 University of Arizona study concludes that 50 percent of people will trust an AI medical diagnosis only if it’s backed up by a human doctor.

Skeptics say AI will simply be a way to push more patients through the door at an even faster rate, money being the driver. And for good reason — there are 3,147 medical start-ups in the United States alone. The information is clear, however: AI has great potential, but it’s up to us how we use it.

“In short, both mind and machine need to work in synergy,” says Hamad Bin Khalifa University’s Qureshi.