BioAI and Genomic Testing Cooperative Announce Strategic Collaboration to Provide AI-Powered Digital Pathology Solutions for Clinical Research and Diagnostic Applications
Article

BioAI and Genomic Testing Cooperative Announce Strategic Collaboration to Provide AI-Powered Digital Pathology Solutions for Clinical Research and Diagnostic Applications

Manchester, NH – June 25, 2024 – BioAI, an emerging biotech company applying multimodal artificial intelligence (AI) to novel biomarker discovery, development, and diagnostics, announced a strategic collaboration with Genomic Testing Cooperative (GTC), a leading provider of molecular diagnostics for solid tumors and hematologic malignancies. This collaboration leverages the AI capabilities of both companies to deliver innovative solutions that meet the needs of pharmaceutical companies and clinicians, ultimately enhancing patient care in oncology.  GTC will become an early technology access member of BioAI’s global ecosystem of clinical laboratories.   

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ASCO 24 posters
Innovation

ASCO 24 Posters

GTC presented abstracts at ASCO 2024 GTC’s posters from 2024 Convention of American Society of Clinical Oncology are now available to be downloaded. Please reach

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CorePath Laboratories Internalizes Genomic Testing Cooperative’s State-Of-The-Art Next-Generation Sequencing (NGS) Testing for Solid Tumors and Hematologic Neoplasms 
Press Releases

CorePath Laboratories Internalizes Genomic Testing Cooperative’s State-Of-The-Art Next-Generation Sequencing (NGS) Testing for Solid Tumors and Hematologic Neoplasms 

CorePath Laboratories is partnering with Genomic Testing Cooperative (GTC) to enhance its next-generation sequencing (NGS) capabilities for cancer diagnostics. This collaboration combines targeted DNA and RNA profiling with other pathology testing methods, providing comprehensive evaluations of patient samples. Additionally, liquid biopsy capabilities offer a non-invasive way to monitor therapy and detect relapse.

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Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation
Publications

Using Targeted Transcriptome and Machine Learning of Pre- and Post-Transplant Bone Marrow Samples to Predict Acute Graft-versus-Host Disease and Overall Survival after Allogeneic Stem Cell Transplantation

Acute graft-versus-host disease (aGvHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HSCT), occurring to some degree in over 50% of patients and being a direct cause of death in about 20% of patients. This complication occurs even despite a better understanding of donor selection and GvHD prophylaxis regimens. aGvHD is a complex event in which multiple contributing factors are involved. We performed RNA transcriptome analysis of 1408 genes in bone marrow samples obtained before and after transplantation using machine learning to predict the risk of aGvHD and post-transplant survival for a cohort of patients undergoing HSCT. Differential gene expression identified several signaling pathways in the bone marrow microenvironment that may be major regulators of the complex biology of GvHD, and identified targets of intervention to ameliorate the risk of aGvHD and improve patient survival.

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