Dr. Ayoola Ademola
Positions
Adjunct Assistant Professor
Cumming School of Medicine, Department of Surgery
Biostatistician
Alberta Health Services
Member
Arnie Charbonneau Cancer Institute
Contact information
Background
Biography
Dr. Ayoola Ademola is a Biostatistician with over five years of experience at Cancer Care Alberta and an Adjunct Assistant Professor at the Department of Surgery, University of Calgary, Calgary. His research interest focuses on the interplay between statistics and clinical trials to uncover novel methodological alternatives. He is enthusiastic about using statistical methodology to examine clinical trial data for treatment effect heterogeneity, which is critical to the advancement of precision medicine. He is interested in developing a risk prediction tool that can be used to identify cancer patients who are at risk of developing competing risks, such as cardiovascular disease, and to estimate the net risk benefits of cancer treatment.
Research
Areas of Research
- Patient report outcome
- Risk prediction
- Knowledge translation
I am a biostatistician with expertise in clinical trials methodology, identifying heterogeneity of treatment effects, and development of risk prediction tools. My research integrates advanced survival analysis, Bayesian methods, machine learning, and decision‑analytic approaches to support patient‑centered and precision medicine.
- Methodological Contributions to Heterogeneity of Treatment Effects in Stroke Trials
My research contributes to understanding heterogeneity of treatment effects in stroke trials by addressing limitations of traditional subgroup analyses and advancing rigorous analytic strategies. I have evaluated methods for subgroup identification, credibility assessment, and covariate‑adjusted analyses in randomized trials. These contributions have been disseminated through peer‑reviewed publications and international presentations, strengthening methodological standards in acute stroke research and clinical trial design. - Leadership in Randomized Clinical Trials
I have provided statistical leadership in the design, analysis, and reporting of multicenter randomized clinical trials, including the AcT trial (published in The Lancet), a pragmatic registry‑linked randomized trial comparing thrombolytic agents for acute ischemic stroke. As trial statistician for the PERK multicenter randomized trial, I led development of statistical analysis for an orthopedic trial. These studies informed clinical practice and policy decisions in stroke care and were published in high‑impact journals including Stroke and JAMA Neurology. - Development and Validation of Clinical Risk Prediction Models
I contributed to development and validation of prognostic models using population‑based and administrative health datasets. My research integrates competing‑risk frameworks, penalized regression, and machine learning to generate clinically actionable risk estimates for cardiovascular disease, stroke outcomes, cancer care, and postoperative complications. - Integration of Patient‑Reported Outcomes and Decision Science
Through multidisciplinary collaborations, I have contributed to studies and meta‑analyses on patient‑reported outcome measures, response shift, and quality‑of‑life assessment in clinical trials. This work integrates patient‑centered data into predictive modelling and decision‑analytic frameworks.
Collectively, these contributions form a coherent research program advancing biostatistics, clinical trials, cardiovascular outcomes research, and oncology analytics, supporting clinical trial and patient‑oriented research.
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