RWD Helps Abbvie Bridge Oncology Trial Data Gaps

A conversation with Svetlana Kobina, MD, Ph.D., vice president of global and U.S. medical affairs oncology, AbbVie

Randomized controlled trials (RCTs) have been the gold standard for assessing the safety and efficacy of interventions in oncology, generating robust data for endpoints like survival and response rates. Yet, strict eligibility criteria mean that many real-world cancer patients remain underrepresented, leaving critical gaps in evidence that underappreciate the full patient experience.

In this Q&A, AbbVie Vice President of Global and U.S. Medical Affairs Oncology Svetlana Kobina, MD, Ph.D., discusses how integrating real-world data (RWD) alongside RCTs can bridge that divide — helping researchers better understand diverse patient populations, address unmet needs, and generate evidence that more closely aligns with day-to-day clinical practice.

Clinical Leader: Clinical trials capture patient experiences in a controlled setting. Historically, what data have oncology RCTs been good at capturing? Conversely, what can’t they capture?

Svetlana Kobina: RCTs excel at evaluating the efficacy and safety of a particular intervention, often in carefully selected patient populations. In oncology, these trials can deliver robust, structured data for clinically meaningful endpoints, such as overall survival, objective response rates, progression-free survival, and treatment-related adverse events – endpoints that are critical for establishing a therapy’s benefit/risk profile and any potential future regulatory evaluations.

However, strict eligibility criteria in oncology trials can often exclude patients with comorbidities and poor performance status and, furthermore, geographic and demographic constraints may impact patient diversity – meaning that many patients seen in daily clinical practice could be underrepresented within the RCT setting. Trials also do not always include measures of patient experience, such as quality of life, treatment adherence, symptom relief, or other meaningful outcomes that are of value to patients, instead focusing on clearly predefined efficacy and safety endpoints.

Given that the 2025 World Conference on Lung Cancer (WCLC) has just taken place,, taking non-small cell lung cancer (NSCLC) as an example, in the metastatic setting, this disease commonly spreads to the bone, brain, and liver, and patients have a very poor prognosis. Yet this population with very high, complex unmet needs can be underrepresented in trials. At AbbVie, we recognize that bridging this gap requires integrating real-world data (RWD) into our evidence generation strategy as a complement to RCTs to bring us closer to the lived experience of patients. AbbVie is pursuing innovative evidence generation strategies to address unmet medical needs and improve patient outcomes through these approaches.

Why is that data gap a problem, and how can RWD address it to improve clinical decision-making?

When a gap exists between what is seen in RCTs and the real-life complexity of clinical practice, it can hinder clinical decision-making and perpetuate inequities. Data gaps may be driven by various factors in RCTs, such as selective patient population, limited diversity in patient groups, and focus on specific efficacy/safety measures (e.g., tumor shrinkage) that may miss broader aspects of patient well-being, treatment adherence, and healthcare utilization. Thus, HCPs must extrapolate the evidence from RCTs to guide real-world care in groups underrepresented, such as, for example, those with comorbidities or poor performance status.

This is where RWD can come in to bridge the gap. RWD helps contextualize efficacy, improves external validity, and provides clinicians with evidence that is more representative of the patients they actually treat. Sourced from anonymized electronic health records, insurance claims databases, and academic registries, it captures how therapies perform outside of RCTs – and therefore provides a far broader, more diverse range of patient populations to derive insights from. RWD also enables longitudinal tracking of treatment patterns and sequencing, adherence, long-term safety, and cost-effectiveness, offering insights that are often unattainable in RCTs. The combination of RCTs and RWD provides a very compelling evidence base that enables HCPs, payers, and policy makers to make better decisions.

Our focus at AbbVie is to leverage RWD to inform both clinical development and medical strategy. For example, our RWD abstract at WCLC explored the prognosis of non-squamous NSCLC patients with liver, bone, or brain metastases treated with standard-of-care frontline therapies. Findings showed us that there is still an unmet need in this patient population despite the advent of novel immunotherapies in the first-line setting. In addition to our RWD efforts, we are constantly focusing on new evidence generation through innovative partnerships, including strategic alliances with organizations, such as the Sarah Cannon Research Institute (SCRI), to further enhance our R&D efforts.

Can you give an example from the oncology program where you’ve identified a gap and sought to fill it with RWD?

This is of continual focus for our oncology medical affairs teams, and we have about 200 ongoing trials that focus on evidence generation, including clinical prospective interventional and real-world settings.

By using RWD to uncover gaps, validate biomarkers, and understand treatment dynamics in diverse populations, we’re going beyond supplementing trial data and expanding the lens through which we view patient care.

What role does medical affairs have in filling that gap between trial and data that reflects a lived patient experience?

Medical affairs is where science meets the clinic and care – it acts as a strategic bridge interpreting RCTs and RWD and translating them into actionable insights to advance patient care. Medical affairs can facilitate the integration of RWD into evidence generation by collaborating with healthcare professionals, gathering insights on unmet needs, and communicating clinical evidence beyond trial populations. We sit at the intersection of clinical research, real-world practice, and patient experience. Many of us in medical affairs are ex-treating physicians, so we understand first-hand how complex and nuanced clinical and real-world patient care can be. That experience helps us ask the right questions and interpret data in ways that matter to practicing oncologists as we work to innovate new therapies for patients.

By contextualizing trial data within real-world settings, medical affairs teams have the unique opportunity to also identify remaining unmet needs related to patient care, access, and education. This information can be used to develop educational initiatives, drive adoption of RWD into clinical guidelines and inform future trial designs, for example.

Is there any change management or education that needs to happen for RWD to be better integrated into research?

Absolutely, and it starts with shifting how we think about evidence. RCTs have always been considered the gold standard in terms of evidence generation, and they still are for many of the critical questions. Yet acceptance of RWD has come a long way in recent years, especially in rare tumor types where patient recruitment is particularly challenging. RWD brings a different kind of value, and integrating it into research requires both education and infrastructure.

First, there needs to be a mindset shift with respect to how researchers and clinicians understand and interpret RWD, as well as its limitations. Because it’s observational, it comes with challenges like missing data, confounding variables, and inconsistent documentation, so knowing how to navigate those issues is key. Stakeholders may require training on data standards, collection methods, and interpretation of RWD to ensure its quality and relevance. Change management is important to address cultural and operational barriers, promote collaboration across multidisciplinary teams, and establish clear processes for incorporating RWD into evidence generation.

These challenges are the reason we need to build the right tools and systems that facilitate appropriate interpretation of RWD, which is why we’ve invested in platforms and partnerships that give us access to high-quality, curated data sets. Regulatory bodies are also developing or expanding their RWD frameworks, but standardization in methods and establishing appropriate endpoints will be key. And then there’s alignment across stakeholders. Regulators, payers, and the medical societies that spearhead clinical guidelines are increasingly open to real-world evidence, but expectations are still evolving. Medical affairs and patient advocates alike can help shape that conversation, ensuring the evidence we generate meets both scientific standards while remaining practical.

At AbbVie, we are actively working to better integrate RWD into research and evidence generation. This includes investing in data infrastructure, building partnerships with healthcare providers and data organizations, and developing frameworks to ensure the quality and relevance of RWD. AbbVie’s medical affairs, R&D, and other cross-functional teams collaborate to educate stakeholders, support change management initiatives, and implement processes that bridge clinical trial data with real patient experiences. The goal is to create a more holistic understanding of patient outcomes and needs, ultimately informing better decision-making and advancing patient care in areas like oncology and beyond.

What are the challenges with ensuring that RWD is high quality and that it's interpreted properly?

RWD is powerful, but it’s not without its challenges. Unlike clinical trial data, which is collected in a controlled and standardized way, RWD is inherently complex and heterogeneous given that it comes from a variety of sources that may also be incomplete and with variable formats. This can make RWD time-consuming to collate and difficult to interpret in its entirety. Country-level differences in collection and availability can also limit analysis. In oncology, specifically, the potentially unstructured nature of RWD – for example, in the form of doctors’ notes – may make it difficult to classify and group patients according to tumor type or cancer stage, thus limiting its interpretability and comparisons to RCT data. However, advances in AI/ML may enable better extraction and standardization of key tumor attributes and patient characteristics across large data sets.

Additionally, because RWD is observational, it can be subject to bias. Another consideration is generalization. RWD might reflect a specific health system or patient population, so we need to be thoughtful about how broadly we apply the insights. That’s why we work with partners who specialize in curating and linking data sets across modalities to help ensure the data is interpreted in a way that’s meaningful for real-world practice.

Is that where RWD turns into RWE? Or, how can we best understand the relationship between those two concepts?

Exactly. RWD is the starting point; it’s the raw information collected from patient care. But it’s only when we apply rigorous scientific methods that it becomes RWE. RWE is the insight we gain from analyzing RWD in a structured, validated way. It helps us answer questions like: How does a therapy perform in real-life practice? What outcomes can we expect in different patient groups? How do biomarkers vary and influence response across demographics?

Transforming RWD into RWE requires rigorous methodology: cleaning, harmonizing, structuring, and find missing piececontextualizing the data. We’ve applied such transformations in our work on immunotherapy resistance and biomarker prediction in lung cancer to guide our R&D approaches. By linking clinical and molecular data, we’ve uncovered patterns that inform treatment decisions and guide future research. In short, RWD is the “what,” and RWE is the “so what.” Ultimately, it’s about turning data into meaningful insights that fuel improved care for future patients.

About The Author:

With over two decades of leadership in R&D and medical affairs within the pharmaceutical sector, Svetlana currently serves as the vice president of global and U.S. medical affairs oncology at AbbVie. Holding both MD and Ph.D. degrees, Svetlana leverages her unique expertise in oncology and hematology in her work at AbbVie. Svetlana’s work spans across global medical affairs, R&D, and integrated data science functions, ensuring unparalleled standards of quality, safety, and efficacy.

Prior to her work at AbbVie, Svetlana held senior vice president and vice president roles within Bayer’s global medical affairs and data science oncology division for 12+ years. In addition to Bayer, she also worked at Sanofi, leading their EU and U.S. medical affairs group within oncology and hematology for more than five years.