Cancer is a group of related-but-different diseases with various underlying molecular networks that complicate treatment. Dr. Shraddha Pai’s research goal is to improve data-driven clinical decision-making by finding genomic and multi-omic signatures that match cancer patients to the most effective treatments with the fewest side effects.
Her team uses population-scale data with multiple layers of information (e.g. transcriptomic, DNA methylation, proteomic, brain imaging, clinical), and develops algorithms and software that incorporate prior knowledge of genotype-phenotype impact and systems-level organization for predictive modeling. Dr. Pai is also interested in the role of developmental epigenetics in altering the risk of childhood- and adult-onset disease.
Prior to joining OICR’s Computational Biology Program, Dr. Pai led the development of netDx – a general-purpose patient classifier algorithm integrates heterogenous patient data into a single model to predict clinical outcome. It adapts a recommender system model similar to that used by Netflix (“find movies like this one”) to precision medicine (“find patients like non-responders”), and uses prior knowledge of cellular pathways to organize genomic data. Separately, Dr. Pai co-led the first epigenome-wide association study in neurons isolated from post-mortem brain samples in major psychosis. This study led to the identification of a novel biomarker that unifies two distinctive features of psychosis: dopaminergic increase and reduced synaptic structure.
Dr. Pai’s work and expertise in genomics and precision medicine apply to cancer as well as other diseases with genomic contribution.
- Postdoctoral Fellow, Bader Lab, University of Toronto
- Postdoctoral Fellow, Department of Psychiatry, University of Toronto
- Trainee, Precision Medicine Initiative at the University of Toronto (PRiME)
- PhD, Cold Spring Harbor Laboratory
- Early-Career Investigator, OICR
- Pai S, Hui S, Isserlin R, …, Bader GD. netDx: interpretable patient classification using integrated patient similarity networks. Mol Syst Biol. 2019; 15, e8497.
- Pai S, Li P, Killinger B, …, Labrie V. Differential methylation of enhancer at IGF2 is associated with abnormal dopamine synthesis in major psychosis. Nature Communications. 2019;10(1):2046.
- Pai S, Bader GD. Patient Similarity Networks for Precision Medicine. J Mol Biol. 2018; 430(18):2924-2938.
See more of Dr. Pai’s publications on Google Scholar.
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- netDx: a patient classifier algorithm that can integrate several types of patient data into a single model