I’m thrilled to sit down with Ivan Kairatov, a biopharma expert with a wealth of knowledge in technology and innovation within the industry. With his extensive background in research and development, Ivan offers unique insights into the groundbreaking AYA ACCESS study, which explores how digital tools and chatbots can transform genetic counseling for adolescent and young adult (AYA) cancer survivors. In our conversation, we dive into the unique challenges faced by this age group, the potential of digital solutions to bridge gaps in care, and the broader impact this could have on long-term health outcomes for young survivors.
Can you share what sparked the focus on adolescent and young adult cancer survivors in initiatives like the AYA ACCESS study?
The focus on AYAs, those aged 18 to 39, comes from a recognition that this group often falls through the cracks in cancer care. They’re at a unique life stage—transitioning into adulthood, starting careers, or building families—while dealing with a cancer diagnosis. Research shows over 10% of AYAs have genetic predispositions to cancer, yet many don’t get the testing or counseling they need due to barriers like location or lack of specialized care in community settings. Studies like AYA ACCESS aim to address these gaps by meeting young survivors where they are, using innovative approaches to make genetic services more accessible.
Why is genetic counseling such a vital piece of the puzzle for young cancer survivors?
Genetic counseling is crucial for AYAs because it helps them understand their future health risks, not just for themselves but also for their families. Many in this age group face the possibility of developing additional cancers or chronic conditions due to their initial illness or treatments. Counseling provides clarity on these risks, empowers them to make informed decisions about prevention or surveillance, and can even guide family planning. Without it, they’re left in the dark about potentially life-saving information.
What are some of the toughest hurdles AYAs face when trying to access genetic testing and counseling?
AYAs encounter a range of obstacles, from geographic barriers to systemic issues. Many live far from specialized centers and rely on community oncology practices that may not have genetic specialists on staff. There’s also a lack of provider awareness about the specific needs of this age group, and time constraints often mean genetic screening gets deprioritized. On top of that, emotional barriers like fear or anxiety about what the results might reveal can deter young survivors from seeking these services.
How does the shortage of genetic specialists in community settings impact AYAs differently than other age groups?
AYAs are particularly affected because they’re often treated in settings geared toward either pediatric or older adult patients, where their unique needs can be overlooked. Unlike older adults who may have more established healthcare routines, AYAs are less likely to advocate for themselves or navigate complex systems to find specialists. This age group also faces a longer lifespan post-diagnosis, making early genetic insights even more critical for long-term health planning, which is often missed in under-resourced community settings.
Can you walk us through how the two different approaches in the AYA ACCESS study—standard remote counseling and the enhanced eHealth model—function?
Absolutely. The standard arm of the study offers remote genetic counseling through telehealth with a certified genetic counselor, which is already a step forward for accessibility. The intervention arm, however, takes it further with an enhanced eHealth model. This includes digital pre-test education and a chatbot called ‘Genetics Journey’ that guides patients through the process, answers basic questions, and sends reminders. Both arms provide genetic testing and post-test counseling, but the eHealth model is designed to be more interactive and tailored to AYAs’ tech-savvy nature.
What’s the role of the chatbot, ‘Genetics Journey,’ in supporting AYAs through this process?
The chatbot serves as a friendly, 24/7 companion for AYAs navigating genetic counseling. It’s designed to engage them with personalized communication, answering common questions, providing reminders for appointments or tasks, and offering support in a way that feels less clinical. For a generation that’s grown up with technology, this tool makes the process more approachable and helps reduce the intimidation factor of genetic testing by breaking down complex info into bite-sized, relatable interactions.
How do digital education tools in the study empower AYAs to understand their genetic risks on their own terms?
These tools are a game-changer because they allow AYAs to learn at their own pace. They can access educational content about genetic risks whenever they’re ready, revisit materials as needed, and even take online quizzes to test their understanding. This self-directed approach respects their busy lives and varying emotional readiness, giving them control over how and when they engage with potentially heavy information, which is especially important for young survivors processing a lot at once.
What kind of results are you hoping to achieve by integrating digital tools and chatbots in this trial?
We’re aiming for several key outcomes. First, we want to see an increase in the uptake of genetic counseling and testing among AYAs, especially in underserved areas. We also hope to improve patient knowledge about their risks and maintain or even boost emotional well-being by making the process less daunting. Finally, we’re looking at cost-effectiveness—can these tools deliver high-quality care at a lower cost than traditional models? If successful, this could set a new standard for how genetic services are provided.
In what ways might these digital tools help ease emotional barriers for young survivors seeking genetic information?
Digital tools can lower the emotional stakes by creating a safe, private space for AYAs to explore genetic information without the pressure of face-to-face interactions right away. A chatbot or online module doesn’t judge or rush them, which can help reduce anxiety or fear about what they might learn. It also normalizes the conversation around genetics, making it feel less like a scary medical ordeal and more like a manageable part of their health journey, which is huge for this age group.
How does this study strive to improve access to genetic services for AYAs specifically in community oncology practices?
The study targets community oncology practices because that’s where many AYAs receive care, yet these settings often lack genetic specialists. By using remote counseling and digital tools, we’re bringing expert-level services directly to these patients without requiring them to travel to urban centers. The trial collaborates with various oncology research groups across the U.S. to ensure broad reach, testing whether this model can sustainably integrate genetic care into everyday community practice for young survivors.
What sets the AYA age group apart in terms of their biological and psychological needs after surviving cancer?
Biologically, AYAs are often in a peak period of physical development, which means cancer treatments can have long-lasting effects on things like fertility or organ function, and genetic risks may play a bigger role over their extended lifespan. Psychologically, they’re at a stage of building identity, independence, and relationships, so a cancer diagnosis can disrupt major life milestones. They need care that addresses both the medical and emotional aspects of survivorship, tailored to their unique place in life.
How will the study evaluate success when it comes to patient understanding and emotional health?
Success will be measured through a mix of metrics. We’ll look at how much participants’ knowledge of genetic risks improves through pre- and post-intervention assessments. Emotional well-being will be evaluated using surveys that gauge anxiety, stress, or satisfaction with the counseling process. We’re also tracking engagement—how often AYAs use the digital tools or complete testing—to see if these methods resonate with them. It’s about ensuring they not only understand their risks but also feel supported throughout.
Why is assessing cost-effectiveness a key component in studying the enhanced eHealth model?
Cost-effectiveness is critical because healthcare resources are limited, especially in community settings where AYAs often get care. If the eHealth model proves to be as effective as traditional counseling but at a lower cost—through reduced need for in-person visits or specialist time—it could be scaled up to reach more patients without straining budgets. This is essential for making genetic services a standard part of survivorship care, particularly for underserved populations who need it most.
How do you envision this study reshaping the future of genetic counseling delivery for young cancer survivors?
I see this study as a potential turning point. If digital tools and chatbots prove effective, they could become a core part of how genetic counseling is delivered, blending high-tech solutions with human expertise. This hybrid approach could make services more scalable, reaching AYAs in remote or under-resourced areas while personalizing care to their preferences. It might also inspire similar innovations for other age groups or health conditions, fundamentally changing how we think about accessible, patient-centered care.
What is your forecast for the impact of digital tools on genetic counseling for AYAs in the coming years?
I’m optimistic that digital tools will become a cornerstone of genetic counseling for AYAs within the next decade. As technology continues to evolve, I expect these tools to get even smarter—think more advanced AI chatbots or apps that integrate seamlessly with electronic health records for real-time updates. The focus will likely shift toward prevention and early intervention, with digital platforms empowering young survivors to take charge of their health. If studies like AYA ACCESS succeed, we could see a future where no AYA misses out on genetic insights due to access barriers, ultimately improving long-term outcomes across the board.
