Speaker Profile
Ph.D., COO/CSO, AMPEL BioSolutions
Biography
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 BioSolutions
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 2022 Silicon Valley
Sequencing technologies are continuously improving, making it easier to obtain more in-depth molecular information than ever before. Emerging single-cell multi-omics sequencing technologies allow the capture of multiple modalities from a cell, including its epigenome, transcriptome, epitranscriptome, and proteome. This allows research into the heterogeneity of many biological mechanisms, and insights into complex molecular mechanisms that underpin disease.
Sessions:
- 4th Generation Sequencing Technologies & Genome Mapping Systems
- Barrett Bready, Nabsys
- Alka Chaubey, Bionano Genomics
- Eli Glezer, Singular Genomics - Long-Read Sequencing Technologies
- Steve Turner, PacBio - Single Cell Genomics
- Michael Schnall-Levin, 10x Genomics - Spatial Transcriptomics
- Jason T. Gammack, Resolve Biosciences - Pathogen Identification
Session Chair: Charles Chiu, UCSF
- Philip Stevens, Noscendo - Metagenomics and Microbial Profiling
- Amrie Grammer, Ampel BioSolutions - ML/AI for Diagnosis & Prognosis
- Todd Dickinson, Arc Bio - Modern Technologies for Pathogen Identification + AI
Session Chair: Sivan Bercovici, Karius Dx - Novel SBS Methodology
- Josh Lauer, Ultima Genomics - Proteogenomics
- Nigel Beard, Encodia - Advances Proteomics - Stratifying Cardiovascular Risk to Decrease Cost of Care
Session Chair: Roy Smythe, SomaLogic
- Adrian Lee, UPMC
- Jamie Bauersmith, UPMC - Leveraging Immune System Diagnostics to Improve Disease Outcomes
Session Chair: Kathy Kamath, Serimmune, Inc
- Noah Nasser, Serimmune, Inc
- Sasha Tabachnikova, Yale - Evolving Alzheimer’s Disease Therapeutics with Neuro Diagnostic Therapies (PANEL)
Session Chair: Kevin Hrusovsky, Quanterix
- Charlotte Teunissen, Amsterdam UMC
- Henrik Zetterberg, University of Gothenburg
- Nicholas Ashton, University of Gothenburg - PMWC Showcase (NCI)
- Michael Cardone, Eutropics Pharmaceuticals
- Robert Meltzer, Fluent BioSciences
- Cynthia Taylor Lawley, Olink Proteomics
- Niro Ramachandran, Akoya Biosciences
- Asim Siddiqui, Seer
Session Abstract – PMWC 2022 Silicon Valley
The PMWC 2022 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.
