September 19, 2023
Congratulations to 40 Under 40 Winner: Joseph Zabinski, PhD, MEM, Managing Director of AI & Personalized Medicine, OM1
Get To Know Joseph:
Age (as of December 31, 2023): 35
Hometown: Cortlandt Manor, NY
Alma Mater: Boston College (BS), Dartmouth (MEM), UNC (PhD)
Number of Years of Experience in Healthcare: 8
Favorite Hobby: foreign languages & hiking
Your Favorite thing about healthcare: getting to use data and AI to make real differences in people’s lives
Why is this candidate a good fit for 40 under 40?
Artificial intelligence (AI) and real-word data (RWD) are no longer buzzwords but table stakes as the healthcare industry evolves to better care for patients. However, tactical applications of AI today are not yet mature, and leaders miss opportunities to harness technology already available to address ongoing challenges, including mis- and underdiagnosing patients, for example. This is where Managing Director of AI & Personalized Medicine at OM1, Joseph Zabinski, PhD, MEM is focused, helping lead innovation with new AI products, while also splitting his time to advocate as a thought leader, encouraging the industry to evolve with technology to improve patient care and outcomes. As an experienced healthcare AI executive, Dr. Zabinski is motivated to unlock the potential of AI across the care continuum – for patients, providers, and life science partners. Most recently, he spearheaded the launch of OM1’s PhenOM™ Platform, an AI-powered system for digital phenotyping. By using AI to isolate patterns across patients’ healthcare journeys and synthesizing them into outcome-specific phenotypic ‘fingerprints,’ providers and life science researchers can learn from trends across millions of patients, and then personalize care plans. Translating these population-level insights down to specific patients is one of most powerful applications of AI available in the industry today. Dr. Zabinski’s work in applied AI is contributing to unlocking previously hidden patterns to allow clinicians to obtain actionable insights to better diagnose and treat patients, resulting in better outcomes while also automating processes to reduce clinician burnout. AI in healthcare has suffered from significant hype and corresponding disillusion in recent years. Dr. Zabinski is charting a course balanced between the power, and limitations, of this exciting technology, founded in a deep understanding of the realities of the life science industry and clinical medicine. He is helping bring AI’s real-world impact to diagnostic and treatment applications while maintaining high standards and strong ethics, vital in an industry where patients’ needs should motivate everything we do. In addition to his everyday work at OM1, Dr. Zabinski frequently attends industry and academic events and participates in thought leadership at the intersection of AI, RWD, and clinical practice. He has presented at the Annual Meetings of the American Psychiatric Association, the American Academy of Dermatology, the American Association of Neurological Surgeons, the International Society for Pharmacoepidemiology, the Society for Risk Analysis, and the Medical Affairs Professional Society, leading conversations on how we can best adopt advanced AI to yield actionable insights in clinical care. He has coauthored a number of abstracts, posters, and peer-reviewed publications on these topics, and continues to contribute actively to the field. Dr. Zabinski is working to bridge the gap between emerging AI technology and real-world clinical applications, demonstrating how we can embrace this technology to solve difficult industry challenges and revolutionize patient and clinical care. Dr. Zabinski is an ideal candidate for 40 Under 40, as he’s not only making significant contributions to OM1, but also to the industry as a whole – ultimately, helping to improve and better patient outcomes.
Explain this candidate’s professional accomplishments:
Throughout his career, Dr. Zabinski has demonstrated passion and effectiveness in finding ways to leverage cutting-edge technologies to improve patient outcomes across chronic conditions via AI-based phenotyping for diagnosis, treatment, and clinical trials. In 2017, prior to his work at OM1 and after receiving a Ph.D. focused on environmental human health risk assessment from UNC Chapel Hill, Dr. Zabinski joined McKinsey & Company. As a specialist management consultant in the Firm’s Pharmaceutical and Medical Products Practice, he advised senior executives in the life science industry on emerging applications of advanced analytics, focused on pharmaceutical R&D, regulatory policy, and data science organization design. He used machine learning to contribute to identification of upside opportunities of more than $100M through coordinated re-deployment of resources across a seven-brand product portfolio for a top-20 pharma company, built a roadmap to scale an emerging player in real-world clinical data to $300M in revenue in three years, and designed key components of a major pharmaceutical company’s strategy for entry into the respiratory disease space. In his time at McKinsey, Dr. Zabinski also designed ‘lighthouse’ analytics applications (e.g., label expansion through real-world data, enhanced patient finding) across a top-10 pharma company’s therapeutic areas and clinical operations as part of a $100M data science reorganization. These experiences form the foundation of Dr. Zabinski’s expertise in applying AI to life science industry challenges in real-world settings. After McKinsey, Dr. Zabinski joined OM1 in 2019 as Director of Data Solutions. He became Senior Director of AI & Personalized Medicine in 2020, and in 2023 was promoted to Managing Director of AI & Personalized Medicine, with his roles growing in scope and responsibility as OM1’s AI business has grown and matured. In his current role, Dr. Zabinski manages strategy, go-to-market planning, partnerships, AI thought leadership, and ongoing operations in OM1’s AI & Personalized Medicine business unit. He is responsible for driving growth through new business development, team expansion, strategic positioning, partnership evolution, and thought leadership. In collaboration with OM1’s data science team, Dr. Zabinski oversaw the design, build, and launch of OM1’s AI-powered PhenOM™ Platform, a first-in-class application of AI to real-world healthcare data and digital phenotyping. Dr. Zabinski leads OM1’s efforts in expanding PhenOM™ deployment in key therapeutic focus areas, including immunology, mental health, neuroscience, and cardiovascular disease. While also managing key client relationships in the pharmaceutical, medical device, health system, and payer spaces, Dr. Zabinski drives use of AI to support patient identification, treatment optimization, and clinical trial success. He serves as a subject matter expert and thought leader at the intersection of AI technology, life sciences, and healthcare.
How does the candidate show commitment to the industry and bettering their professional career?
By working to champion research and successfully bringing AI products to market, Dr. Zabinski not only excels within his professional domain, but is actively working to bring understanding and acceptance to AI within the healthcare industry. With the current narrative in the landscape, paired with perceptions of fear and lack of patient understanding of technology within the care continuum, Dr. Zabinski is working to dissuade hesitancy associated with AI and other technology that aids clinical decision-making. While 39% of respondents in a recent survey from Pew Research Center are comfortable being treated via some AI usage, nearly 60% of patients are uncomfortable with healthcare providers using AI in their own healthcare procedures. Dr. Zabinski has devoted much of his professional development to building strategies and techniques to position AI as a benefit to patients and their providers, rather than a replacement for them. Furthermore, Dr. Zabinski works to locate AI’s potential for ‘disruption’ at a productive point in healthcare settings – demonstrating how AI tools can help clinicians understand disease-signaling patterns in undiagnosed patients, leading to faster diagnoses and more effective treatment plans, rather than attempting to replace these pathways and displace providers of care. At a time when the industry is figuring how to best utilize AI and RWD in routine clinical care, Dr. Zabinski dedicates his time to spearheading conversations to further the industry’s grasp of what these terms mean and how we can best apply them in clinical care, including how extracting as much information as possible from real-world datasets is essential for understanding the complete patient journey. As mentioned above, with cutting-edge technology like AI and ML, we are able to evaluate subtle patterns in structured and unstructured data to provide insight into disease diagnosis, progression, treatment efficacy, and overall outcomes – but this promise requires careful translation and work with stakeholders to make real. Dr. Zabinski is dedicated to this work. With his relentless pursuit and belief that AI and ML can improve the healthcare landscape – from advanced subtype phenotyping, enhanced diagnostic screening and evaluated risk and treatment differences to improved clinical trial enrollment – Dr. Zabinski is paving the way forward in uncovering ways in which the healthcare industry and its stakeholders can utilize these advanced tools. Dr. Zabinski sees his own career growth intertwined with that of the broader industry. He maintains focus on emerging applications of new AI technology, including large language models, and stays connected to other thought leaders in the space to exchange ideas and best practices. Dr. Zabinski is also active in helping others – both current professionals, and the next generation – learn about AI applications in healthcare. For the past two years he has co-taught a course on Machine Learning for Pharmacoepidemiologists at the International Conference on Pharmacoepidemiology. For the past four years, he has mentored student teams at Dartmouth’s Thayer School of Engineering in course-based assessments of emerging AI technology and applications in healthcare.