On this episode of Retina Mentor Moments, John W. Kitchens, MD, and Sophie Bakri, MD, MBA, the ophthalmology chair at Mayo Clinic in Minnesota, discuss her journey in ophthalmology and the importance of technology, particularly artificial intelligence (AI), in enhancing patient care and treatment personalization at Mayo Clinic.
Professional journey and education
Dr. Bakri discussed her journey from studying medicine in the UK to moving to Albany, New York, to pursue retina, and completing a retina residency at Lions Eye Institute, Albany Medical College, and a fellowship at the Cole Eye Institute, Cleveland Clinic Foundation.
She chose to pursue medical training in the US because of the highly structured nature of its training programs, fellowships, and research opportunities. In contrast to the US system, a notable aspect of medical training in the UK—especially at the University of Nottingham—is the early exposure to clinical practice, such as shadowing general practitioners to understand the roles within a care team.
However, she pointed out that the US requirement for a 4-year undergraduate degree allows students to explore diverse fields, such as music or languages, before entering medical school, even though this may delay the start of their medical careers. Ultimately, Dr. Bakri emphasizes that the key is how passionate and caring doctors are, regardless of their educational background.
A key motivation for her journey here is Dr. Bakri's early research on contrast sensitivity in macular degeneration. As her interest in the research topic piqued, she noticed that much of the research came from the US. While this topic was once deemed uninteresting, it has now become a significant endpoint in clinical trials.
Institutional excellence at the Mayo Clinic
Mayo Clinic is renowned for its agility and ability to adopt new technologies and processes to improve patient care quickly. It operates under a physician-led model, utilizing an "administrative dyad" that pairs physician leaders with administrative specialists to ensure patient needs remain the primary focus in all decision-making. The clinic's fundamental value is prioritizing patient needs, a core principle deeply embedded in its culture and guiding every decision.
The future of AI in medicine
Dr. Bakri emphasizes that “data is the future.” While she doesn’t believe AI will replace doctors entirely, she argues that without embracing AI, doctors risk becoming obsolete. Dr. Kitchens echoes this sentiment, noting that AI enhances users' effectiveness and could potentially replace those who do not adopt it.
She was recently appointed Medical Director at the Center of Digital Health, where she oversees AI and imaging development. Ongoing efforts focus on integrating AI into clinical workflows through ambient listening for scribing and triage tools for specialties like glaucoma. Additionally, tools like Opus enable physicians to search massive datasets of imaging, lab, and genomic data to identify associations and develop new algorithms.
AI can analyze decades of patient history and phenotype data, helping forecast which patients will respond most effectively to specific drugs or at specific times.
Pharmacokinetics and treatment personalization
Patient response to treatment depends not only on pharmacokinetics, as individual drug clearance rates and disease physiology vary. Some patients need treatment every 4 weeks, while others can extend to 12 weeks.
Although initial hopes existed to predict if a drug was suitable for 4- or 6-week treatment schedules, research has not yet succeeded in using human-analyzed OCTs to forecast more frequent treatment requirements.
There is hope that AI models can be trained to identify phenotypes and physiological changes that are too minuscule for humans to observe, helping to predict how individual patients will respond to specific treatments.
Check out this recent episode of Retina Mentor Moments for a discussion on the pharmacokinetics of anti-VEGF therapies in vitreoretinal diseases!
