With 4.5% of the world’s population impacted by autoimmune diseases and a continued high unmet need in some conditions, immunology drug development will continue to expand. Immunology therapeutics is projected to grow to $184B by 2030, ranking 3rd in terms of total retail drug spend by therapeutic class in the U.S. – behind cancer and diabetes.
In some conditions, like psoriasis and rheumatoid arthritis, the therapeutic market is crowded, and breaking through with new treatments is becoming increasingly difficult for manufacturers. As new drug classes and more biosimilars come to market, and other drugs lose their patents, gaining and maintaining market share is critical to success. Therapy initiation is a primary focus for obvious reasons, but understanding adherence, persistence, and discontinuation is just as important. An estimated 50% of patients with a prescription for a chronic condition stop taking it within the first year, costing the US pharmaceutical industry an estimated $250 billion annually in lost revenue - and an additional cost of $290 billion to the broader healthcare system in terms of resource utilization. Most significantly, the suffering of the patient is not abated.
Getting at why patients are prematurely stopping their medications can provide valuable insights to support brand, value, and access, as well as HCP and patient engagement messaging and strategies. Whereas claims data will show that patients are discontinuing medication, the reasons why those patients are discontinuing can’t be found in claims data. Reasons, such as tolerability, contraindication, cost or insurance coverage issues, and lack of effectiveness and remission, are typically described in clinical notes and require extraction. Due to the difficulty with accessing this information, drug manufacturers generally are left using market surveys, which are biased by physician recall. In the end, only a tiny piece of the story is revealed and the overall picture is severely limited by that clinician’s patient population and anecdotal interpretation.
Coupling real-world data based on an electronic medical record background and advanced artificial intelligence models and technologies, the reasons can be extracted directly from clinician narratives at scale. At OM1, we accomplish this by leveraging our proprietary OM1 Real-World Data Cloud™, Immunology Real-World Data Network, and artificial intelligence (AI) technology. We extract and categorize the patient characteristics from the clinical data and reason categories from clinician notes and deliver the analyses in our syndicated OM1 Reasons for Discontinuation (RfD) reports, currently available in primary rheumatologic and dermatologic conditions.
With this analysis, drug manufacturers can better identify, understand and strategize on emerging patterns for:
- Differentiation – For example, why patients are discontinuing competitive therapies, including patient demographics for sub-population patterns and insights
- Precision Messaging – For example, why subpopulations are discontinuing a therapy in the real-world market for precision messaging campaigns.
- Patient Support – For example, if patients are dropping due to issues around cost and coverage, these reports can facilitate appropriate mitigation around market access, reimbursement, HCP support, and patient education programs.