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Medical Care

How Mayo Clinic Leverages Real-World Data for Precision Medicine

2024-12-09

Mayo Clinic clinicians are now delving into the potential use of healthcare-specific large language models. These models, accessed through a generative artificial intelligence chat application, aim to enhance patient care and improve clinical decisions. In a field where ChatGPT and Google Gemini may only provide relevant answers a fraction of the time, California-based Atropos Health claims its federated healthcare data network can offer detailed and accurate consultations even for the most obscure medical questions. By drawing on data from millions of patients, clinicians can gain valuable insights to inform treatment. For instance, when treating a patient with an unusual genetic condition predisposing them to a specific cardiac disease, such data can be crucial. Last year, Atropos launched a generative AI-enhanced platform with a chat-based interface called ChatRWD. Dr. Peter Noseworthy, chair of cardiac electrophysiology at Mayo Clinic, has begun testing it. The platform provides a Real World Data Score and a Real World Fitness Score for each dataset, helping users select the most suitable data. A study led by Saurabh Gombar showed that healthcare-specific LLMs like OpenEvidence and ChatRWD were able to produce actionable, reliable evidence 42% or 60% of the time, far exceeding general-purpose LLMs. Since 2022, Atropos has been collaborating with Mayo Clinic to develop data-driven methods through automated reports called Prognostograms. This allows physicians and researchers to access Mayo Clinic's deidentified data repository. For patients in critical care, the ability to find answers through the platform saves time. Observational clinical researchers often face long timelines to generate insights from real-world data. But with a tool like ChatRWD, they can get close to research-grade information. Atropos projects more than 200% growth in additional dataset availability over the next year. The power of patient data emerges with AI as it can capture the totality of patient outcomes that traditional medical research may miss. Rare or unusual conditions are better represented in large data samples. Mayo Clinic has been working on a decentralized clinical trial program to extend the reach of clinical trials. Access to clinical trials has exacerbated health disparities, and the goal is to bring more cures to more people. While ChatRWD is yet to be deployed at scale at Mayo Clinic, it has already provided some interesting insights. Andrea Fox is the senior editor of Healthcare IT News. Email: afox@himss.org. Healthcare IT News is a HIMSS Media publication.

The Power and Potential of ChatRWD

ChatRWD has emerged as a significant tool in the healthcare field. It allows clinicians to interact with real-world data in real-time and surface those insights directly at the point of care. This is a game-changer as it saves time and provides valuable information that can inform treatment decisions. For example, in critical care situations, where traditional means of determining treatment can take weeks, an AI-driven Prognostogram can complete the process in days. This not only benefits patients but also helps clinicians make more informed decisions quickly. The ability to access and analyze large amounts of real-world data through ChatRWD is a powerful asset that has the potential to transform healthcare.

Moreover, the scores provided by Atropos' platform, such as the Real World Data Score and the Real World Fitness Score, help users select the most appropriate dataset for their questions. This ensures the accuracy and reliability of the information obtained. The study led by Saurabh Gombar demonstrated the superiority of healthcare-specific LLMs like OpenEvidence and ChatRWD over general-purpose LLMs in terms of producing actionable, reliable evidence. This highlights the importance of specialized language models in healthcare.

The Impact on Clinical Trials

Mayo Clinic's decentralized clinical trial program is another area where ChatRWD can have a significant impact. By extending the reach of clinical trials beyond major academic medical centers, more patients can participate and benefit from potential cures. Access to clinical trials has been a challenge, especially for underrepresented populations and those in underserved rural communities. ChatRWD can help bridge this gap by providing a platform for data-driven research and decision-making. It allows clinicians and researchers to access deidentified data from Mayo Clinic and analyze it in real-time, leading to more inclusive and effective clinical trials.

However, while ChatRWD shows great promise, it is still in the process of being deployed at scale at Mayo Clinic. But even in its current form, it has already provided some interesting insights and has the potential to revolutionize healthcare. As Atropos projects significant growth in additional dataset availability, the possibilities for using ChatRWD and other healthcare-specific language models become even more exciting.

The Role of Real-World Data

Real-world data plays a crucial role in healthcare with the advent of AI. It allows clinicians to capture the totality of patient outcomes that may be missed in traditional medical research. For example, rare or unusual presentations of diseases are better represented in large data samples, providing a more comprehensive understanding of these conditions. This can lead to improved treatments for patients who are historically outside the reach of clinical trials. By using real-world clinical data, clinicians can gain a deeper understanding of patient responses to treatments and make more informed decisions.

Compared to just using ChatGPT or other general-purpose LLMs, real-world clinical data offers a more targeted and relevant approach. It is based on actual patient experiences and outcomes, making it a valuable resource for healthcare. The collaboration between Atropos and Mayo Clinic in developing data-driven methods through Prognostograms is a testament to the importance of real-world data in improving healthcare.

San Francisco, CA, has witnessed a significant milestone in healthcare. The Quantum Leap Healthcare Collaborative (QLHC), the driving force behind the I-SPY 2 Trial, has successfully completed the enrollment for two crucial arms. This achievement holds great promise for the evaluation of the safety and efficacy of datopotamab deruxtecan in both single agent therapy and combination with durvalumab.

Unlocking the Potential of Healthcare with Quantum Leap

Datopotamab Deruxtecan: A Revolutionary Treatment

Datopotamab deruxtecan is a remarkable TROP2-directed DXd ADC meticulously engineered by Daiichi Sankyo. It is now being jointly developed by AstraZeneca and Daiichi Sankyo, bringing together the expertise of two leading pharmaceutical companies. This targeted therapy holds the potential to revolutionize cancer treatment by specifically targeting TROP2 receptors.The combination of datopotamab deruxtecan with durvalumab, AstraZeneca's anti-PD-L1 monoclonal antibody, further enhances its therapeutic potential. By combining these two agents, researchers aim to achieve more comprehensive tumor suppression and improved patient outcomes.

The I-SPY 2 Trial: A Pioneering Initiative

The I-SPY 2 Trial, sponsored and operated by QLHC, is a groundbreaking initiative that aims to push the boundaries of healthcare. By evaluating the safety and efficacy of datopotamab deruxtecan in different treatment regimens, the trial is expected to provide valuable insights into the future of cancer treatment.The completion of enrollment for two arms of the trial is a major step forward. It allows researchers to gather data and analyze the results, which will contribute to the development of more effective treatment strategies for patients.

QLHC's Mission and Vision

QLHC is a 501c(3) nonprofit pioneer dedicated to building and iterating creative solutions in healthcare. Their mission is to better serve patients by accelerating and innovating healthcare through approaches that challenge the status quo. By bridging the gap between research and care, QLHC is working towards their long-term vision of improving human health for all through personalized medicine.Through their operational, financial, and regulatory oversight of the I-SPY trial, QLHC is playing a crucial role in advancing healthcare. Their efforts focus on achieving meaningful results for patients and driving innovation in the field.

Contact Information

For more information on the early results of this arm or to get in touch with QLHC, please visit:https://www.nature.com/articles/s41591-024-03267-1https://www.nature.com/articles/s41591-024-03266-2Contact Jacqueline Murray at Quantum Leap Healthcare Collaborative: 415.839.8082 or j.murray@quantumleaphealth.org.

A man is currently being questioned in relation to the tragic shooting of UnitedHealthcare CEO Brian Thompson. According to Sky News' US partner NBC News, this incident has sent shockwaves through the community. Customers at a branch of McDonald's in central Pennsylvania initially noticed something "suspicious" about the man and promptly called the police. Two senior law enforcement officials provided details, stating that when officers arrived, they discovered the man had a fake ID and was taken to a police station for further questioning.

Key Discoveries at the Police Station

Once at the police station, it was revealed that the suspect had a gun similar to the one used in the killing of Brian Thompson, along with a silencer and a fake New Jersey ID. The suspect is being held in Altoona, which is around 100 miles east of Pittsburgh. Investigators are exploring whether he recently traveled to Altoona by bus from Philadelphia. This line of enquiry is crucial in understanding the suspect's movements and motives.

Details of the Shooting Scene

Mr. Thompson was shot dead by a masked gunman outside a Manhattan hotel on Wednesday morning as he was on his way to the company's annual conference. Footage shows the attacker approaching slowly from behind and opening fire outside the Hilton hotel. The scene was marked by shell casings with "deny," "delay," and "depose" written on them. The gunman then fled on foot and later on a bike into Central Park, prompting a citywide manhunt. In the park, detectives found a grey backpack believed to be used by the gunman, containing bank notes from the Monopoly board game and a jacket that may have been worn by him.

Investigation Progress and Clues

New CCTV footage has emerged showing a suspect coming out of a nearby subway station, approximately half an hour before the shooting. It is a significant lead as it provides more details about the suspect's early movements. The gunman traveled to the city by bus from Atlanta, and investigators are now searching for video from that bus station and other Greyhound Bus stops along the route. This extensive search is aimed at uncovering more evidence and piecing together the events leading up to the shooting.The shooting has not only shocked the local community but has also sparked a heated debate about US healthcare. The incident serves as a reminder of the importance of security and the need for continuous efforts to prevent such tragedies. As the investigation continues, authorities are working tirelessly to bring the perpetrator to justice and provide answers to the many questions that remain.