Spotlight on: Adewunmi Akingbola

Dr Adewunmi Akingbola is contributing to public health by improving the reliability of real-world data through his work on missing data and biases in health studies. Recently, he won the Cambridge Public Health and Precision Health Initiative Early Career Researcher competition and presented his findings at the showcase event, “How Can We Make Public Health More Precise?”. In this spotlight, Adewunmi shares insights into his research journey, his current work, and the contributions it's making to public health.

What is your research about?

During my MPhil in Population Health Sciences, I tackled one of the big challenges in public health research: missing data. My focus was on people who inject drugs, a population often underrepresented in studies. I compared methods like complete-case analysis and multiple imputation to find better ways of managing missing information, ensuring results are both accurate and reliable.

Currently, at Arcturis Data, I’m investigating real-world data analysis for patients with multiple myeloma. My work explores how timing in disease progression assessments can create biases. Using both real-world datasets and randomised trial data, I simulate patterns to measure and correct these biases, improving how treatment outcomes are evaluated in oncology.

What excites you most about your work?

What excites me most is the opportunity to bridge data insights with tangible public health outcomes. My work allows me to address complex challenges and assess treatment effectiveness in real-world settings beyond clinical trials. By simulating real-world scenarios, I can uncover biases that influence decision-making in healthcare. It’s fulfilling to know that my research contributes to better evidence, ultimately improving patient care and public health strategies.

Why is this topic important?

This research addresses a key limitation in public health and oncology: the reliability of real-world evidence. With the increasing use of real-world data to complement clinical trials, understanding and addressing biases like assessment time bias is essential. By improving how we evaluate progression-free survival in multiple myeloma patients, this work strengthens evidence used for treatment decisions, regulatory approvals, and public health strategies. It’s about ensuring that patients benefit from accurate and equitable health outcomes.

Ultimately, I hope my work will enhance the accuracy and credibility of real-world evidence, leading to more equitable and effective patient care. I also aspire to inspire further research into refining methodologies for real-world data analysis, advancing evidence-based healthcare and public health policies to meet complex challenges.

Does your work improve collaboration across disciplines?

Yes, I collaborate with professionals from a variety of disciplines, including statisticians, data scientists, and epidemiologists. This interdisciplinary approach brings together diverse perspectives and expertise. Statisticians help refine models and interpretations, while epidemiologists ensure the relevance of findings. These collaborations make the research both rigorous and applicable to real-world healthcare challenges.

In your opinion, what public health challenges need more attention?

There are so many pressing issues in public health that need more focus. For example, health inequities remain a significant challenge—too many underserved populations still struggle to access basic care, diagnostics, and treatment. Another challenge is the growing threat of antimicrobial resistance. It’s a global problem that urgently requires better surveillance systems and more innovative strategies to slow its spread.

Climate change is another area where we’re already seeing the impact on health. As the environment shifts, disease patterns are changing, and we need to adapt quickly to this new reality. And of course, mental health is a major concern. Despite progress, stigma and underfunding still leave significant gaps in research and care. Each of these areas has the potential to reshape how we approach public health, and they all deserve more attention and resources.