Dr. Grammer is an internationally recognized scientist and successful entrepreneur, having founded and managed AMPEL successfully for over 5 years. Dr. Grammer was elected to the class of 2021 for SIBF (Society of International Business Fellows), an organization of 1,400 individuals in 45 countries worldwide. She was also awarded a Virginia SBIG grant for AMPEL's first investment round. She is a second term board member of Virginia Bio.Before co-founding AMPEL in 2013, Dr. Grammer spent over 20+ years in genomics and managed more than 15 National Institute of Health (NIH) scientific teams and a highly productive NIH laboratory. Dr. Grammer received multiple awards for her team's work comparing genes expressed in patients compared with healthy individuals, including the prestigious NIH Director's Award as well as mentoring awards from the American Association of Immunologists. She has published over 75 articles on her scientific research.
AI and Data Sciences Showcase:
AMPEL is a precision medicine company with a development pipeline of CLIA-certified gene expression tests for blood or tissue samples that determine disease status, identify molecular pathway and predict best drugs. Genomic platform, bioinformatics, RNA analytics and ML/AI algorithms covered by patents & are disease agnostic.
LuGENE Px for Lupus
AMPEL’s LuGENE® Px blood test evaluates Lupus disease status, identifies molecular pathways and predicts drug options. Filed patents protect AMPEL’s genomic platform, bioinformatics, RNA analytics and machine learning algorithms as well as disease specific applications in oncology, autoimmunity and infectious disease.
Session Abstract – PMWC 2023 Silicon Valley
The PMWC 2023 AI & Data Sciences company Showcase will provide a 15-minute time slot for selected companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.