In recent years, there has been an introduction of exciting new immunotherapies for hematologic malignancies, offering innovative approaches to tackle significant unmet needs. This year, at the annual American Society of Hematology (ASH) Meeting & Exposition there was a noticeable shift among clinicians as they continue to consider the role these treatments have in practice, placing a strong emphasis on prioritizing patient experiences. This, alongside recalibrating the way the life science industry looks at clinical trials and what really matters to patients at large, as well the impact of AI and machine learning, headlined the list of biggest takeaways for our team at MERGE over the course of this much anticipated four-day event.
The Double-edged Sword of New Therapies
Year after year, ASH stands as a significant event on the life science calendar, bringing together experts and practitioners across the field of hematology. Over the past few years in particular, the center of attention has been on innovative cell therapies, which have revolutionized the approach to treating for blood disorders. However, this year's meeting brought into sharp focus the impact of these therapies on patients’ lives. While they hold tremendous clinical potential, the associated adverse events of these treatments and their management are being integrated into the treatment decision process.
Clinical studies are now being designed to specifically assess the severity and the incidence of hematologic toxicities with immunotherapies. With the accumulating real-world data on well-established side effects such as cytokine release syndrome (CRS) or neurotoxicities, and on additional toxicities (coagulopathies, bleeding and thrombosis) newly recognized as both frequent and clinically relevant, there is a compelling imperative to develop new methodologies to effectively assess their impact on patients.
A Patient-Centric Approach to Clinical Trials
This year’s ASH Meeting prompted clinicians to discuss the optimal approach for determining the value of hematology treatments, highlighting how overall survival (OS) and quality of life remain the paramount concern for patients. These questions encouraged the audience of hematology experts and key industry players to reexamine the role of progression free survival endpoints in clinical trial designs. Providing sustainable care and keeping patients’ best interests at the forefront were the main topic of discussions in several sessions. The latter also included striking the balance between offering potentially beneficial therapies to patients and considering the increasing associated costs.
Harnessing AI and Machine Learning in Hematology
Another important topic of discussion at ASH was the role of AI and machine learning in hematology. With the vast amounts of data available for analysis, these technologies can help to uncover patterns and insights that would otherwise be virtually impossible for humans to detect.
Of course, there are questions about the reliability of AI models in predicting the success of drugs or the degree to which they should be used in establishing the right treatment path for patients. However, some AI models have correctly predicted the benefit-risk gap of certain drugs, including CAR-T therapies, or demonstrated alignment with current treatment algorithms. Still, despite these early successes, there are still valid questions about how these predictive tools can best serve clinicians in their practice, and whether pharmaceutical companies should rely on them to make substantial investment decisions.
The insights gleaned from this year's ASH meeting have far-reaching implications for pharmaceutical marketers navigating the dynamic landscape of hematology. As therapies evolve and patient-centricity takes center stage, marketers face a pivotal shift in their approach. The focus on patient experiences and quality of life during treatments demands a nuanced communication strategy—one that goes beyond efficacy data and delves into the tangible benefits and potential drawbacks of therapies. Understanding and articulating the balance between therapeutic advantages and real-world implications will be crucial.
Moreover, as AI and machine learning become increasingly integrated into hematology, marketers need to assess the reliability and relevance of these technologies in informing their messaging to healthcare practitioners. The key lies in crafting narratives that not only highlight therapeutic efficacy but also address the broader spectrum of patient well-being, fostering trust and transparency in pharmaceutical marketing while keeping clinicians informed about the holistic impact of these innovations.
For more on how your organization can integrate AI and machine learning in hematology, connect with MERGE's Life Science team.
