In a time when chronic diseases are on the rise and people are living longer than ever before, novel solutions for better patient care are urgently needed. In healthcare’s next chapter, a new type of technology will play a bigger role than ever before.
Enter artificial intelligence, or AI. Rooted in the simulation of human intelligence by computer systems and machines, AI has the potential to transform how humans learn, work and interact with one another in every aspect of life.
It’s also primed to revolutionize healthcare.
“The rapid growth in available healthcare-related data in recent years allows us to ask bigger questions,” says Jeff Headd, Vice President, Commercial Data Science, Janssen North America Business Technology. “Using the latest innovations in AI and machine learning (ML), we are able to quickly analyze these vast datasets (including electronic medical records, lab results or even medical imaging like X-rays, MRIs and CT scans), uncover new insights and then drive actions with real potential to improve patient outcomes.”
The promise that AI holds is why Johnson & Johnson is actively using the technology in different ways, from speeding up the process of discovering new medicines to helping surgeons analyze the results of procedures. It’s also why, during this year’s South by Southwest conference, the company hosted a panel about AI’s role in transforming healthcare.
“There’s a deep demand for solutions in the healthcare space,” says Shan Jegatheeswaran, Global Head of MedTech Digital, Johnson & Johnson, who spoke on the panel. “But it’s important to remember that the most sophisticated thing in the clinical workflow is still the human brain. The role of AI is to augment a human decision or action in a way that improves speed, quality or both.”
We’re taking a closer look at five ways AI is helping drive healthcare forward—and how Johnson & Johnson is using it to help improve the quality of medical care around the world.
When it comes to catching and diagnosing diseases earlier, AI can be a real game changer. By applying AI to data derived from or generated by common diagnostic tests, such as electrocardiograms and echocardiograms, providers could diagnose diseases more accurately, prevent delays in care and potentially save lives.
Take pulmonary hypertension (PH) and cardiac amyloidosis, two progressive and often-fatal diseases. Despite the existence of treatments, both diseases are commonly misdiagnosed early on, given that their respective symptoms mimic those of other, more common diseases.
To help diagnose these diseases, Johnson & Johnson has teamed up with collaborators Anumana and Mayo Clinic for pulmonary hypertension, and Ultromics Ltd. and Atman Health for cardiac amyloidosis to develop AI algorithms aimed at helping detect these diseases early on.
“Our goal has been to develop AI-enhanced tools that can be seamlessly integrated into the current clinical workflow of physicians,” says Mona Selej, Senior Director, Cardiovascular-Metabolism and Pulmonary Hypertension, Data Science & Digital Health, R&D, Janssen Pharmaceutical Companies of Johnson & Johnson and a PH physician by training. “We determined which tests patients commonly receive early in their journeys to diagnosis—electrocardiograms in the case of PH and echocardiograms in the case of cardiac amyloidosis—and developed AI algorithms that could detect subtleties that are invisible to the naked eye, suggesting patients should be flagged for confirmatory testing.”
The PH algorithm and Ultromics’ cardiac amyloidosis algorithm have both received Breakthrough Device Designation from the U.S. Food & Drug Administration and, if approved, could help facilitate earlier, more accurate diagnoses, leading to patients receiving treatment sooner.
Beyond early detection algorithms, medical devices, including connected devices, robotic platforms and digital solutions are also evolving with AI to enhance their capabilities.
Johnson & Johnson MedTech’s Monarch™ Platform for bronchoscopy, for example, lets physicians examine areas of the lung that are more difficult to access with conventional bronchoscopes—and that can aid in earlier lung cancer diagnosis. The flexible robotics system uses preoperative CT scans of the lungs to inform the procedure, but tracking objects in such a dynamic environment in real time can be complex. The Monarch R&D team uses AI and ML algorithms to develop and refine the Monarch Platform’s navigation, which helps physicians guide the bronchoscope during lung biopsy procedures and allows them to locate a potential tumor more accurately. This leads to more accurate diagnosis and treatment.
Traditionally, discovering and developing new drugs to treat disease is a long and complex undertaking, but AI is primed to help accelerate this process.
To develop medicines, researchers need to understand what biological and genetic variations cause diseases to develop. By applying AI to anonymized medical datasets, such as electronic health records or lab results, scientists can fill in missing information as to what causes those diseases.
AI is also enabling researchers to develop more targeted medicines, driving progress toward precision medicine.
For example, in oncology an AI algorithm can be applied to digitized images of biopsies to help identify subtle differences between tumors, pointing to the presence of genetic mutations in a subset of patients. Researchers can use these findings to develop medicines specifically designed for that subset of patients. Those same algorithms that can help identify genetic mutations could then be used to find these patients in the real world to facilitate clinical trial recruitment and clinical decision-making.
“Drug discovery is an extremely challenging process with only a small percentage of lead compounds moving into clinical trials and an even smaller percentage becoming approved medicines,” says Chris Moy, Scientific Director, Oncology, Data Science & Digital Health, R&D, Janssen. “AI is not only helping us identify the right targets for complex diseases, but it’s also helping us design fit-for-purpose molecules to treat diseases and optimize them to provide targeted treatment to the disease while also reducing the impact of side effects.”
Together, these applications of AI will help researchers place the most promising candidate drugs into clinical development, with the ultimate goal of improving the probability of successfully bringing a drug to market and rapidly getting new treatments to patients who need them the most.
One of the biggest challenges when it comes to running clinical trials is quickly and efficiently recruiting and enrolling patients that meet the selection criteria. Adopting AI technology into the process may help solve this problem.
Example: At Johnson & Johnson, researchers are applying AI and ML algorithms to large anonymized datasets to identify and locate clinical research sites with patients who could potentially benefit from medicines being studied. The clinical trial operations team can then work to determine the likelihood of enrolling the newly identified sites into their trials.
“Historically, many clinical trials have largely taken place at major academic medical centers, but we know that not all patients have access to these centers,” says Nicole Turner, Senior Director of Global Development, Data Science & Digital Health, R&D, Janssen. “Our goal is to leverage the power of AI to bring trials to more patients, rather than waiting for patients to come to us.”
Data and AI are also helping researchers diversify clinical trials, as advanced analytics are finding locations and healthcare institutions where diverse patients are more likely to be treated. Researchers can then prioritize recruiting eligible patients from those study sites into clinical trials. This is critical, given the importance of ensuring medicines are studied in diverse patient populations representative of those impacted by diseases.
First comes the discovery and development of therapies, medications and other healthcare products. Then, the next critical juncture is making sure these products reach patients, and AI can help with that, too.
Stocking products in the hospitals, pharmacies, clinics and other healthcare facilities where they’re needed requires an accurate prediction of supply and demand. This can be challenging, as a wide range of factors can impact the supply chain, including market trends, economic disruptions, supplier issues and more.
“It’s our responsibility to make sure patients and customers have reliable access to the transformational therapies our company creates,” says Vishal Varma, Director, Supply Chain Digital & Data Science and Operations Research, Johnson & Johnson Services, Inc. “AI is helping us build a stable and resilient supply chain so we can deliver on that obligation.”
For example, Johnson & Johnson is using advanced ML algorithms to sift through and analyze large amounts of data, including demand fluctuations and supplier performance, as well as to help predict the impact of real-time events that may disrupt the supply chain (think severe weather events and economic disruptions). AI-powered solutions can help prioritize which locations will be greatly impacted in order to quickly respond to risk factors that may otherwise affect the ability to deliver products to people who count on them.
Ensuring patients have access to the right products also requires timely communication with healthcare providers.
“Another way Johnson & Johnson is using ML is to improve our understanding of disease progression, which allows us to anticipate when a patient may benefit from one of our medicines,” says Headd.
This application is part of a Johnson & Johnson global capability known as Engagement.ai, designed to guide the company’s engagement with healthcare professionals. Engagement.ai is powered by AI and ML models trained on extensive datasets to provide insights that maximize the company’s ability to support providers and their patients.
“These insights from Engagement.ai allow us to prioritize when, where and how we connect with healthcare providers to ensure they have relevant and appropriate information when making treatment decisions,” says Headd.
In the operating room (OR), surgical video is frequently taken during procedures to provide education, research methodologies and quality improvement strategies to medical professionals.
Johnson & Johnson MedTech is evolving a portfolio of digital solutions for the OR that use AI algorithms to essentially “cut a highlight reel of these videos” in a matter of minutes, Jegatheeswaran explains, so surgeons can re-watch significant events from their procedures. Without AI, this process could take hours—even days—to complete.
“Surgeons are a lot like high-performance athletes,” says Jegatheeswaran. “New and learning surgeons want to see how they performed and learn from their performances and how others performed. But no one wants to sit and watch hours of footage from the full procedure.”
Now, surgeons can look at what happened during procedures practically in real time and share the video with residents and peers, offering valuable post-case analysis and learning opportunities.
“Once you get enough of these enriched surgical videos, you can start running algorithms on the behaviors, tactics and movements that create positive and negative outcomes during surgery,” Jegatheeswaran says.
Surgical video is one of many potential applications of AI in the OR, according to Larry Jones, Chief Information Officer, Johnson & Johnson MedTech.
“Our vision in Johnson & Johnson MedTech is to make healthcare smarter, less invasive, more personalized and more connected,” Jones says. “By combining a wealth of data stemming from surgical procedures and increasingly sophisticated AI technologies, we can transform the experience of patients, doctors and hospitals alike.”
Ultimately, that’s what AI in healthcare is all about: better serving providers and patients. “When we use AI, it’s always with a purpose,” Jegatheeswaran says. “Our Credo states that our patients and customers come first, and that will continue as we move forward with this technology.”
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