Dr. Sam Volchenboum is a Professor in the Department of Pediatrics and Associate Chief Research Informatics Officer for the Biological Sciences Division. He is the Associate Dean of Master’s Education and the Informatics Lead for the Institute for Translational Medicine. He is the Program Director for the Clinical Informatics Fellowship Program.His clinical specialty is pediatric hematology/oncology, caring for kids with cancer and diseases of the blood.
In addition to his clinical practice, he directs the Data for the Common Good, a research group dedicated to liberating and democratizing data. Their largest project, the Pediatric Cancer Data Commons, is the world’s biggest publicly-available repository for data from children with cancer. Until 2019, Dr. Volchenboum directed the Center for Research Informatics, a 40-person group that supports biological research throughout the division. As director of this center, he oversaw high-performance computing, HIPAA-compliant storage and backup, application development to support clinical trials, development and maintenance of the clinical trials management system, the clinical research data warehouse, data analytics and visualization, and bioinformatics, including high-throughput genomic analyses and machine learning.
Dr. Volchenboum has been on the UChicago faculty since 2007, and in 2009 he was named a St. Baldrick's Foundation Scholar. He received his PhD in molecular biology and MD from the Mayo Medical School. He completed his residency at Cincinnati Children’s Hospital Medical Center before going to Boston for his pediatric hematology/oncology fellowship at the Dana-Farber Cancer Institute and Boston Children’s Hospital. He also completed a fellowship in informatics and received his Master’s in biomedical informatics from the Massachusetts Institute of Technology.
Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT).
Advancing Monogenic Diabetes Research and Clinical Care by Creating a Data Commons: The Precision Diabetes Consortium (PREDICT). J Diabetes Sci Technol. 2025 Jan 09; 19322968241310896.
PMID: 39781649
Catalyzing Pharmacogenomic Analysis for Informing Pain Treatment (C-PAIN): A Randomized Trial of Preemptive CYP2D6 Genotyping in Cancer Palliative Care.
Catalyzing Pharmacogenomic Analysis for Informing Pain Treatment (C-PAIN): A Randomized Trial of Preemptive CYP2D6 Genotyping in Cancer Palliative Care. J Pain Res. 2024; 17:4187-4196.
PMID: 39717756
Rethinking Human Abstraction as the Gold Standard.
Rethinking Human Abstraction as the Gold Standard. JCO Clin Cancer Inform. 2024 Nov; 8:e2400218.
PMID: 39586035
A subset of image-defined risk factors predict completeness of resection in children with high-risk neuroblastoma: An international multicenter study.
A subset of image-defined risk factors predict completeness of resection in children with high-risk neuroblastoma: An international multicenter study. Pediatr Blood Cancer. 2024 Oct; 71(10):e31218.
PMID: 39072986
Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology.
Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology. Pediatr Blood Cancer. 2024 Sep; 71(9):e31143.
PMID: 38924670
GDPR and data sharing: the Pediatric Cancer Data Commons experience.
GDPR and data sharing: the Pediatric Cancer Data Commons experience. Lancet Oncol. 2024 Jun; 25(6):e227.
PMID: 38821088
Accelerating pediatric Hodgkin lymphoma research: the Hodgkin Lymphoma Data Collaboration (NODAL).
Accelerating pediatric Hodgkin lymphoma research: the Hodgkin Lymphoma Data Collaboration (NODAL). J Natl Cancer Inst. 2024 May 08; 116(5):642-646.
PMID: 38273668
Extracting Electronic Health Record Neuroblastoma Treatment Data With High Fidelity Using the REDCap Clinical Data Interoperability Services Module.
Extracting Electronic Health Record Neuroblastoma Treatment Data With High Fidelity Using the REDCap Clinical Data Interoperability Services Module. JCO Clin Cancer Inform. 2024 May; 8:e2400009.
PMID: 38815188
Targeted Enrollment in Pediatric Oncology Trials: A Vision for Just-in-Time Matching.
Targeted Enrollment in Pediatric Oncology Trials: A Vision for Just-in-Time Matching. JCO Oncol Pract. 2024 May; 20(5):603-606.
PMID: 38386948
An open-source platform for pediatric cancer data exploration: a report from Data for the Common Good.
An open-source platform for pediatric cancer data exploration: a report from Data for the Common Good. JAMIA Open. 2024 Apr; 7(1):ooae004.
PMID: 38304249