Samuel Ajjarapu, MD
Assistant Professor, Pathology & Laboratory Medicine
Biography
Dr. Samuel J. Ajjarapu is an Assistant Professor of Medicine at Boston University Chobanian & Avedisian School of Medicine and a Computer Scientist at the MAVERIC Division of Interdisciplinary Clinical Research, Translation, and Informatics at the VA Boston Healthcare System. He earned his Medical Doctorate (MD) from Spartan Health Sciences University, St. Lucia.
Dr. Ajjarapu’s work focuses on leveraging artificial intelligence and data science to advance precision oncology and healthcare informatics. His research integrates clinical, genomic, and imaging data to improve patient outcomes, particularly in lung cancer and other malignancies. He has co-authored numerous peer-reviewed articles in journals such as Frontiers in Immunology, Patterns, and Studies in Health Technology and Informatics, contributing to innovations in clinical trial workflows, predictive modeling, and digital pathology.
Dr. Ajjarapu previously served as Co-Chair of the Digital Pathology Panel Discussion at the International Summit for AI in Healthcare and participates in multiple VA-APOLLO working groups focused on imaging and data management. He is a dedicated reviewer for the AMIA Annual Symposium and was a Visiting Scientist at Dana-Farber Cancer Institute.
Websites
Publications
- Published on 2/4/2024
Foran DJ, Chen W, Kurc T, Gupta R, Kaczmarzyk JR, Torre-Healy LA, Bremer E, Ajjarapu S, Do N, Harris G, Stroup A, Durbin E, Saltz JH. An Intelligent Search & Retrieval System (IRIS) and Clinical and Research Repository for Decision Support Based on Machine Learning and Joint Kernel-based Supervised Hashing. Cancer Inform. 2024; 23:11769351231223806. PMID: 38322427.
Read at: PubMed - Published on 1/25/2024
Elbers DC, Fillmore NR, La J, Tosi HM, Ajjarapu S, Dhond R, Murray K, Valley D, Shannon C, Brophy MT, Do NV. Building Research Infrastructure to Develop Greater Learning Efficiencies (BRIDGE). Stud Health Technol Inform. 2024 Jan 25; 310:1131-1135. PMID: 38269991.
Read at: PubMed - Published on 1/25/2024
Do NV, Elbers DC, Fillmore NR, Ajjarapu S, Bergstrom SJ, Bihn J, Corrigan JK, Dhond R, Dipietro S, Dolgin A, Feldman TC, Goryachev SD, Huhmann LB, La J, Marcantonio PA, McGrath KM, Miller SJ, Nguyen VQ, Schneeloch GR, Sung FC, Swinnerton KN, Tarren AH, Tosi HM, Valley D, Vo AD, Yildirim C, Zheng C, Zwolinski R, Sarosy GA, Loose D, Shannon C, Brophy MT. Matching Patients to Accelerate Clinical Trials (MPACT): Enabling Technology for Oncology Clinical Trial Workflow. Stud Health Technol Inform. 2024 Jan 25; 310:1086-1090. PMID: 38269982.
Read at: PubMed - Published on 11/11/2021
Whiteaker JR, Lundeen RA, Zhao L, Schoenherr RM, Burian A, Huang D, Voytovich U, Wang T, Kennedy JJ, Ivey RG, Lin C, Murillo OD, Lorentzen TD, Thiagarajan M, Colantonio S, Caceres TW, Roberts RR, Knotts JG, Reading JJ, Kaczmarczyk JA, Richardson CW, Garcia-Buntley SS, Bocik W, Hewitt SM, Murray KE, Do N, Brophy M, Wilz SW, Yu H, Ajjarapu S, Boja E, Hiltke T, Rodriguez H, Paulovich AG. Targeted Mass Spectrometry Enables Multiplexed Quantification of Immunomodulatory Proteins in Clinical Biospecimens. Front Immunol. 2021; 12:765898. PMID: 34858420.
Read at: PubMed - Published on 8/17/2020
Elbers DC, Fillmore NR, Sung FC, Ganas SS, Prokhorenkov A, Meyer C, Hall RB, Ajjarapu SJ, Chen DC, Meng F, Grossman RL, Brophy MT, Do NV. The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database. Patterns (N Y). 2020 Sep 11; 1(6):100083. PMID: 33205130.
Read at: PubMed - Published on 10/2/2019
Do N, Grossman R, Feldman T, Fillmore N, Elbers D, Tuck D, Dhond R, Selva L, Meng F, Fitzsimons M, Ajjarapu S, Ayandeh S, Hall R, Do S, Brophy M. The Veterans Precision Oncology Data Commons: Transforming VA data into a national resource for research in precision oncology. Semin Oncol. 2019 Aug - Oct; 46(4-5):314-320. PMID: 31629530.
Read at: PubMed - Published on 8/21/2019
Do NV, Ramos JC, Fillmore NR, Grossman RL, Fitzsimons M, Elbers DC, Meng F, Johnson BR, Ajjarapu S, DeDomenico CL, Pierce-Murray KE, Hall RB, Do AF, Gaynor K, Elkin PL, Brophy MT. Machine Learning Methods to Predict Lung Cancer Survival Using the Veterans Affairs Research Precision Oncology Data Commons. Stud Health Technol Inform. 2019 Aug 21; 264:1453. PMID: 31438177.
Read at: PubMed - Published on 3/20/2017
Fiore LD, Brophy MT, Ferguson RE, Shannon C, Turek SJ, Pierce-Murray K, Ajjarapu S, Huang GD, Lee C, Lavori PW. Data Sharing, Clinical Trials, and Biomarkers in Precision Oncology: Challenges, Opportunities, and Programs at the Department of Veterans Affairs. Clin Pharmacol Ther. 2017 May; 101(5):586-589. PMID: 28182272.
Read at: PubMed