Abstracts

Poster Presentation Dates

All odd numbered posters will be presented on Friday, November 8, 2019, while even numbered posters will be presented on Saturday, November 9, 2019.

Posters will be on display from 7 a.m. - 8 p.m., with the presenting authors required to be at their posters during lunch (12:30 - 2 p.m. on Friday, Nov. 8, and 12:35 - 2:05 p.m. on Saturday, Nov. 9) and also during the poster reception (6:30 - 8p.m. on Friday, Nov. 8, and 7 - 8:30 p.m. on Saturday, Nov. 9).

#	Title	Authors	Category	Keywords
O65	Artificial intelligence-powered retrospective analysis of PD-L1 expression in nivolumab trials of advanced non-small cell lung cancer	Vipul Baxi, MS; Andrew Beck, MD, PhD; Dimple Pandya; George Lee, PhD; Cyrus Hedvat, MD, PhD; Aditya Khosla; Dayong Wang; Hunter Elliott; Harsha Pokkalla; Abhik Lahiri; Benjamin Glass; Jennifer K. Kerner; Ilan Wapinski; Scott D. Chasalow; Han Chang, PhD; Robin H. Edwards, PhD; Michael Montalto;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Inflammation; Monocyte/Macrophage
P726	Applying deep learning classification for tumor identification across immunohistochemical markers on serial sections to eliminate the need for image co-registration	Mark Anderson, BSc; Karen McClymont; Lorcan Sherry, PhD; Alison Bigley, CSci, FIBMS;	Machine Learning, Artificial Intelligence, and Computational Modeling	Biomarkers; Immune contexture; T cell; Tumor microenvironment; Tumor stroma
P727	Single-cell systems neuroimmunology reveals immunosuppressive checkpoint blockade receptor expression correlates with ventricular stem cell niche contact in human glioblastoma	Todd Bartkowiak, PhD; Sierra Barone, BS.; Allison R. Greenplate, PhD; Justine Sinnaeve, BS.; Nalin Leelatian; Akshitkumar M. Mistry, MD; Caroline E. Roe, BS.; Bret C. Mobley, MD; Lola B. Chambless, MD; Reid C. Thompson, MD; Kyle D. Weaver, MD; Rebecca A. Ihrie, PhD; Jonathan M. Irish, PhD;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Immune monitoring; Immune suppression; Monocyte/Macrophage; Myeloid cells; Solid tumors; Tumor infiltrating lymphocytes (TILs); Tumor microenvironment
P728	Inference of immunotherapy response-predictive biomarkers in lung adenocarcinoma from hematoxylin and eosin (H&E) stained images	Kimary Kulig, PhD, MPH; Cory Batenchuk, PhD; Peter Cimermancic; Huang-Wei Chang, PhD; Eunhee S. Yi, MD; Vanessa A. Velez; Hardik L. Patel; Ali Behrooz; Kamilla Tekiela; Robert Findlater; Cory Batenchuk, PhD;	Machine Learning, Artificial Intelligence, and Computational Modeling	Biomarkers; Checkpoint blockade; Tumor microenvironment
P730	An empirical framework for validating artificial intelligence-derived PD-L1 positivity predictions using samples from patients with urothelial carcinoma	Andrew Beck, MD, PhD; Benjamin Glass; Hunter Elliott; Jennifer K. Kerner; Aditya Khosla; Abhik Lahiri; Harsha Pokkalla; Dayong Wang; Ilan Wapinski; George Lee, PhD; Vipul Baxi, MS; Cyrus Hedvat, MD, PhD; Dimple Pandya; Michael Montalto;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Inflammation; Monocyte/Macrophage
P731	Identification and Validation of Shared Neoantigens for Cancer Immunotherapy	Jennifer Busby, PhD; Melissa Rotunno; Tyler Murphy; William Brinton; Michael Zhong; Lina Kim; Abu Jalloh; Amanda Costa; Michael Fray; Aaron Yang; Meghan Hart; Matthew Davis; Rita Zhou; Elizabeth Maloney; Alexis Mantila; Karin Jooss, PhD; Aleksandra Nowicka; Christine D. Palmer, PhD; James Sun; Roman Yelensky, PhD; Jennifer Busby, PhD;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Neoantigens; Proteomics
P732	Reverse causal inferencing on lung adenocarcinoma patients reveals a stem cell-like molecular subtype associated with pack year history	Renee M. Deehan; Sergey Korkhov; Alexis Foroozan; Scott Marshall, Ph.D; Renee M. Deehan; Nimisha Schneider;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Checkpoint blockade; Solid tumors
P733	Quantitative systems pharmacology modeling of B-cell acute lymphoblastic leukemia treatment with bispecific T-cell engaging antibodies for investigation of bell-shaped dose response	Oleg Demin Jr, MSc;	Machine Learning, Artificial Intelligence, and Computational Modeling	Antibody; Leukemia/Lymphoma; Systems biology; T cell
P734	Prediction of target occupancy in tumor after treatment with anti-PD1 antibodies using physiologically based pharmacokinetic modeling	Oleg Demin Jr, MSc; Dmitry Shchelokov;	Machine Learning, Artificial Intelligence, and Computational Modeling	Antibody; Checkpoint blockade; T cell
P735	Accelerating biomarker discovery using AI powered multi- omics approaches	Madhuri Gadekar; Mohan Uttarwar; Shruti Desai; Sanjay Khare;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Clinical trial; Immune monitoring; Immunoscore
P736	Combining Multiplexed Ion Beam Imaging (MIBI) with Convolutional Neural Networks to accurately segment cells in human tissue	Noah F. Greenwald, BA; Leeat Keren; Shirley Greenbaum; Mara Fong; Gautam Chaudhry; Zion Abraham; Jackson Moseley; David Van Valen; Michael Angelo, MD, PhD;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Solid tumors; Tumor microenvironment; Tumor stroma
P737	Model-Based Meta-Analysis of the Exposure-Response and Clinical Efficacy across Approved Anti-PD(L)1 Agents	Apurvasena Parikh, PhD; Sreeneeranj Kasichayanula, PHD; Rajeev Menon; Megan Gibbs; Sven Mensing; Benjamin Engelhardt;	Machine Learning, Artificial Intelligence, and Computational Modeling	Antibody; Checkpoint blockade; Solid tumors
P738	Artificial intelligence-based tumor purity assessment of digitized histology samples in multiple tumor types from clinical trials of nivolumab	George Lee, PhD; Sujaya Srinivasan; Natallia Kalinava; Ariella Sasson; Vipul Baxi, MS;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Clinical trial; Tumor stroma
P739	Analysis of H&E Images Using Deep Learning for the Prediction of Distant Metastatic Recurrence in Early Stage Melanoma	Michael R. Moore, BA; Eric J. Robinson, BA; Prathamesh M. Kulkarni, PhD; Robyn Gartrell, MD; Jaya Pradhan, DMD, MPH; Emanuelle M. Rizk, BA; Chen Yang, MD; Acs Balazs, PhD; Robert Phelps, MD; Tammie Ferringer, MD; Andrew X. Chen, BS; Raúl Rabadán, PhD; Bethany Rohr, MD; Basil A. Horst, MD; David L. Rimm, MD, PhD; Jing Wang, MD; Yvonne Saenger, MD;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Solid tumors; T cell; Tumor microenvironment; Tumor stroma
P740	Leveraging Artificial Intelligence to Advance Immuno-oncology Drug Development using Functional Ex-Vivo 3D-Tumor Organoid Platforms of Fresh Patient Tissue Samples.	Jenny Kreahling, PhD; Daniel N. Santiago, PhD; Vijayendra Agrawal, PhD; Mibel Pabon, PhD; Soner Altiok, MD, PhD; Melba Page, PhD;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Checkpoint blockade; Gene expression; Immune monitoring; Solid tumors; Systems biology; T cell; Tumor infiltrating lymphocytes (TILs); Tumor microenvironment
P741	Prediction of biomarkers and combinational therapies for anti-PD1 therapy using a computational network approach	Chia Chin Wu, PhD; Andrew Futreal; Jianhua Zhang; Chia-Chin Wu;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Carcinogenesis; Checkpoint blockade; Immune suppression; Immunoscore; Systems biology; Targeted therapy
P742	Computational analysis of feedback regulations of TIM-3	Jian Zhu, PhD; Rebecca L. Zhu;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Checkpoint blockade; Regulatory T cell (Treg cell); Systems biology
P743	Impact of IDO1 expression and inhibition on the sensitivity of anti-PD-1	Jian Zhu, PhD; Rebecca L. Zhu;	Machine Learning, Artificial Intelligence, and Computational Modeling	Bioinformatics; Biomarkers; Checkpoint blockade; Systems biology