Clinical questions and computational methods, working together.

Dr. Muanda is a clinical pharmacology and pharmacoepidemiology researcher whose program focuses on the real-world safety and effectiveness of prescription medications, particularly in older adults and people with chronic kidney or liver disease.

His work uses population-based healthcare data to study medication dosing, adverse drug events, drug-drug interactions and treatment effectiveness. Methodologically, his work includes active-comparator cohort designs, propensity-score methods, interrupted time-series analyses, sensitivity analyses and target-trial emulation, with a major emphasis on scalable post-market drug surveillance.

Dr. Abdullah is a computer scientist and health-data researcher whose work sits at the intersection of artificial intelligence, visual analytics, high-throughput computing and population-based health research. He earned his PhD in Computer Science from Western University with research focused on data science, visual analytics and healthcare applications.

His research develops scalable machine-learning models, explainable clinical AI, interactive visual analytics systems and automated computational pipelines for population-scale health data. Current work includes drug safety and drug-drug interaction screening, NLP and ontology-driven extraction from Canadian drug monographs, terminology harmonization, computational pharmacovigilance and privacy-aware multi-jurisdictional analytics.