Dr. Amrie Grammer co-founded AMPEL to bring personalized precision medicine to patients with diseases involving the immune system and inflammation. AMPEL is a performing company with revenues from design/management Lupus clinical trials and patient stratification using it’s proprietary genomic platform, bioinformatic tools and ML/AI algorithms. In 2022, AMPEL will commercialize it’s first product, a CLIA-certified blood test for patients/physicians called LuGENE® that assesses disease state/flares and best drug option(s) based on evidence. AMPEL's technology covers >95% of all known genes and is disease agnostic so there is capacity to expand reporting of results into new disease indications without developing a new test. Amrie has over 20+ years experience in genomics and is a recognized Immunologist with >50 publications. She managed a highly productive NIH laboratory and received multiple NIH awards for her team’s work comparing genes expressed in patients compared with healthy individuals, including the prestigious Director’s Award.
AI and Data Sciences Showcase:
AMPEL BioSolutions is a precision medicine company commercializing a CLIA-certified gene-based LDT blood test for Lupus patients (LuGENE®) that assesses disease status, predicts flares & matches with drug options. Genomic platform, bioinformatic tools & ML/AI algorithms are disease agnostic.
Lupus Genomic Profiling with Machine Learning Drug Predictions
AMPEL BioSolutions is a precision medicine company commercializing a CLIA-certified gene-based LDT blood test for Lupus patients (LuGENE®) that assesses disease status, predicts flares & suggests drug option(s). Genomic platform, bioinformatic tools & ML/AI algorithms are disease agnostic.
The PMWC 2021 AI Company Showcase will provide a 15-minute time slot for selected AI 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.