Author

Brendan M. Boyle

Nationwide Children's Hospital

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pharmacology & Toxicology· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:clinical cohort / trial· 2 Research Focus:drug response / drug discovery· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Jeffrey S. HyamsiD· 3 shared Joshua D. NoeiD· 3 shared Jack ReifenbergiD· 2 shared Phillip MinariD· 2 shared Tomoyuki MizunoiD· 2 shared Andrew KasarskisiD· 1 shared Angela Mo· 1 shared Anne Marie GriffithsiD· 1 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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3 shared papersPharmacology & Toxicology

Jeffrey S. HyamsORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Model-informed Deep Q-Networks to Guide Infliximab Dosing in Pediatric Crohn's Disease

Kei Irie, Phillip Minar, Jack Reifenberg, Brendan M. Boyle, Joshua D. Noe, Jeffrey S. Hyams, Tomoyuki Mizuno

This study develops a model-informed Deep Q-Network to automate infliximab dosing in pediatric Crohn's disease, achieving high target attainment with minimal overtreatment.

Clinical Pharmacology & Therapeutics · Nov 5, 2025Peer-reviewedPharmacology & Toxicology

Hybrid Population PK-Machine Learning Modeling to Predict Infliximab Pharmacokinetics in Pediatric and Young Adult Patients with Crohn's Disease

Kei Irie, Phillip Minar, Jack Reifenberg, Brendan M. Boyle, Joshua D. Noe, Jeffrey S. Hyams, Tomoyuki Mizuno

This paper develops a hybrid population PK-ML model to improve infliximab concentration predictions in pediatric and young adult Crohn's disease patients, showing better accuracy than Bayesian estimation alone.

bioRxiv · May 1, 2025 · PreprintPharmacology & Toxicology

Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression

Angela Mo, Sini Nagpal, Kyle Gettler, Talin Haritunians, Mamta Giri, Yael Haberman, Rebekah A. Karns, Jarod Prince, Dalia Arafat, Nai-Yun Hsu, Ling-shiang F. Chuang, Carmen Argmann, Andrew Kasarskis, Mayte Suárez‐Fariñas, Nathan Gotman, , Greg C. Gibson

The paper uses measured and predicted gene expression to identify ulcerative colitis patients at elevated risk of colectomy, showing both methods independently replicate in multiple datasets.

bioRxiv · Apr 2, 2021 · PreprintGenetics