PITTSBURGH, Pa. — Ocean Genomics presented our poster for their AI-driven combined transcriptomic and genomic analysis titled “Molecular Predictors and Immunomodulatory Role of Dual Checkpoint Inhibitor Blockade Using ipilimumab/nivolumab in Patients with Extensive Stage Small Cell Lung Cancer” at the American Society of Clinical Oncologists (ASCO) Annual Meeting 2023, on June 2 – June 6, 2023 at the McCormick Place Convention Center in Chicago, Illinois, and has been published in the 2023 ASCO Annual Meeting Proceedings.
Session Title: Lung Cancer—Non-Small Cell Local-Regional/Small Cell/Other Thoracic Cancers
Abstract Title: Molecular predictors and immunomodulatory role of dual checkpoint inhibitor blockade using ipilimumab/nivolumab in patients with extensive stage small cell lung cancer.
Abstract Presentation Number: 8597
Poster Board Number: 224
We had the pleasure of working with two outstanding partners at Yale University School of Medicine/Yale Cancer Center, Anne Chiang, MD, PhD (Associate Cancer Center Director for Clinical Initiatives), and Kurt Schalper, MD, PhD (Director, Translational Immuno-oncology Laboratory), in analysis of their novel single-arm, phase-2 clinical trial (NCT03670056).
The analysis combined whole exome DNA, and RNA-sequencing and was conducted using Ocean Genomics’ Intelligent Transcriptome Platform including our TxomeAI® data analysis pipeline, by members of our computational biology team.
About Ocean Genomics
Ocean Genomics is the transcriptomics AI company. We develop software, data and models and enable our partners to leverage advanced transcriptomic information with other related data and AI to advantage their discovery and development programs. We partner with cutting-edge drug developers to supply insights and evidence that enable data-driven decisions, provide confidence in the underlying biology, and increase the probability of technical and clinical success at every step. Our founders are recognized as leading experts in the fields of computational biology and AI, and developers of many of the most widely used software methods in gene expression analysis.
Our Intelligent Transcriptome computing platforms extract extensive gene expression features and analyses from raw RNA-Seq files (TxomeAI®), and automatically integrate those features with clinical and other -omics to produce accurate, actionable models, and discover drug targets and biomarkers (DiscoverAI™). Our vast database (DeepSea™) provides deeply characterized transcriptomes, curated metadata, and pre-trained AI models to add power to discovery and analyses.