Get the latest news and updates
The PMWC 2020 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.
Confirmed Presenting Companies:
Divya Chhabra is passionate about building great products that create a positive change in people’s lives. Currently, she’s working to revolutionize dialysis treatments with personalized dosing to make them more efficient and accurate. She previously worked as a product manager at athenahealth.
AI and Data Sciences: Dosis Inc.
Dosis, an AI-powered personalized dosing platform, is the developer of Strategic Anemia Advisor (SAA), a clinical decision support tool that personalizes erythropoietin-stimulating agent (ESA) dosing for patients suffering from chronic anemia.
Using AI to Personalize Anemia Management in Chronic Kidney Disease Patients
Divya will discuss how AI is powering the personalization of Erythropoietin-stimulating Agent (ESA) therapy for renal anemia that often goes hand-in-hand with dialysis treatment for the more than 15% of adults in the United States suffering from Chronic Kidney Disease (CKD). AI is being used within cloud-based, clinical decision support tools to assist healthcare providers to determine a patient’s personalized response to ESAs that are prescribed to treat anemia. Using AI, and specifically, control algorithms, which are based on years of peer-reviewed research at the University of Louisville, helps to calculate each patient’s unique place on the spectrum of dose-response and provide an optimal dose recommendation to keep that patient as close to their hemoglobin target as possible. In fact, the use of AI has enabled a steep reduction in patient outlier hemoglobins and an increase in the percentage of patients within a hemoglobin target range, while cutting the time spent on determining the new ESA dose to 30 to 45 seconds per patient.
Kaisa Helminen leads Aiforia Technologies, a medical software company in a rapid expansion phase. Their Aiforia® Cloud is transforming clinical pathology and medical research by bringing deep learning AI to assist and augment human experts in image analysis. As a result, patients will have faster, more accurate diagnosis and more personalized care. Kaisa has a strong background in the life science industry, where she has gained close to 20 years of experience in the global business. Previously she has worked for both midsize and large international life science companies, including Thermo Fisher Scientific, Sartorius and Finnzymes, in sales, marketing and business development positions. Kaisa holds a M.Sc. degree in biochemistry from the University of Helsinki.
AI and Data Sciences Showcase: Aiforia Technologies
Aiforia is a medical AI software company with a unique cloud-based solution to image-based diagnostics. We are transforming pathology and drug development by bringing deep learning AI to assist and augment human experts in image analysis.
Neural Networks In The Hands Of Medical Professionals
We’ll introduce Aiforia Cloud, a novel approach to AI-powered image-based diagnostics. With Aiforia, medical experts can rapidly create their own image analysis algorithms, without a data scientist or AI expertise. We will present several examples of applications from various domains.
Aaron Y. Lee MD MSCI is focused on the translation of novel computation techniques including deep learning for automated diagnosis and to uncover new pathophysiologic mechanisms in routine clinical data from large electronic health databases. His main areas of research include age-related macular degeneration, diabetic eye disease, and macular telangiectasia. He has published over 50 peer reviewed manuscripts and editorials. Dr. Lee is an assistant professor and vitreoretinal surgeon at University of Washington, Department of Ophthalmology. He has served on the American Academy of Ophthalmology Medical Information Technology Committee and the American Academy of Ophthalmology IRIS Analytics Task Force. Dr. Lee received his BA in Biochemistry from Harvard University. He then completed his MD and Masters of Science in Clinical Investigations from the Washington University of St Louis. After an internship at St. John’s hospital, he returned to Washington University to complete his ophthalmology residency. He then completed two fellowships: a medical retina fellowship at Moorfields Eye Hospital in London, and a vitreoretinal surgical fellowship at the University of British Columbia in Vancouver Canada.
AI and Data Sciences Showcase: University of Washington
The UW is one of the world’s preeminent public universities. Our impact on individuals, our region and the world is profound — whether we are launching young people into a boundless future or confronting the grand challenges of our time through undaunted research and scholarship.
Applications Of Artificial Intelligence With Ophthalmic Imaging
The dawn of the machine learning era has caused an explosion of deep learning models applied to almost every aspect of ophthalmic care. Despite significant real-world limitations, these technologies are poised to play a disruptive role in the delivery of eye-care worldwide.
Dr. Jeremy Orr has more than 20 years of clinical medical practice, population health, and healthcare IT experience. A practicing, board-certified family physician, Dr. Orr was named a “Top 100 Physician” during his time with Kaiser Permanente, and then went on to launch a medical practice that became part of Centura Health. While an Assistant Professor at the University of Colorado, he was selected as Teacher of the Year by residents. Prior to joining EarlySign, Jeremy served as the CMO of Boston-based clinical data analytics firm Humedica (later Optum Analytics) and as CMO of Los Angeles based clinical decision support company Stanson Health.
AI and Data Sciences Showcase: Medial EarlySign
Medial EarlySign is a leader in machine learning-based healthcare whose solutions help clients with early detection and prevention of high-burden diseases.
Algorithm To Action To Outcomes
In the race to leverage machine learning to improve health outcomes, the math is the easy part. Dr. Orr will recount the story of two powerful clinical prediction models from training to validation to implementation to human impact.
Jarret Glasscock is a geneticist and computational biologist who leads the team at Cofactor Genomics, a tools and diagnostics company leveraging the power of RNA to diagnose disease. Prior to founding Cofactor Genomics, Jarret was faculty in the Department of Genetics at Washington University and part of The Genome Institute. While at WashU, he was involved in the Human Genome Project, published the first Cancer Genome, led the Institute’s Computational Biology Group, and was part of the Institute’s Technology Development Group tasked with characterizing the first RNA-seq experiments on early instruments such as 454 and Illumina/Solexa(Serial #1). Jarret’s work to leverage signals in RNA to propel Precision Medicine Initiatives has been covered by Genetic Engineering News (GEN), Tech Crunch, and Wired Magazine. He is a member of the Personalized Medicine Coalition, International Society for Computational Biology, and is a Y Combinator Alum.
AI and Data Sciences Showcase: Cofactor Genomics
Cofactor Genomics uses Predictive Immune Modeling to capture the complexity of disease and build powerful multidimensional biomarkers. Cofactor has spent years pioneering the tools to build an RNA-based database of Health Expression Models, unlocking precision medicine and clinical diagnostics.
Leveraging All Data with Multidimensional RNA Models
Precision medicine in an era of big data requires reducing complexity to meaningful information. The field of Predictive Immune Modeling enables a patient’s immune profile to be used as a powerful diagnostic tool leveraging immune Health Expression Models.
Dr. Kiel oversees Genomenon's scientific direction and product development. In 2014, Mark founded the company and created the Mastermind Genomic Search Engine, which connects doctors with evidence in the literature to help diagnose patients with genetic diseases and cancer. Prior to starting Genomenon, Mark completed his residency in Clinical Pathology in 2014 at the University of Michigan. While at Michigan, he completed a fellowship in Molecular Diagnostics and devised the informatics framework for clinical next-generation sequencing in the Molecular Diagnostics Laboratory. During his doctoral studies, he made ground-breaking contributions to the study of hematopoietic stem cells, for which he was awarded the Weintraub International Graduate Student Award and the ProQuest Distinguished Dissertation Award. While a post-doctoral researcher, he made significant contributions to the field of Hematopathology, including genomic profiling of lymphoid malignancies, for which he was awarded the Benjamin Castleman Award.
AI and Data Science Showcase: Genomenon
Genomenon, home of the Mastermind Genomic Search Engine, connects patient DNA with the billions of dollars spent on research to help doctors diagnose and cure cancer patients and babies with rare diseases.
Dr. Amrie Grammer is a Translational and Computational Immunologist specializing in Autoimmune and Inflammatory Diseases, both human patients and pre-clinical mouse models. Amrie co-founded AMPEL in 2013 to bring precision medicine to patients, especially those with lupus and gout. With bioinformatic tools her team created, she designed and implemented a pipeline to predict “flares” and the “right drug for the right patient at the right time” using predictive analytics, machine learning and AI. Top drugs Amrie identified for repositioning have had positive clinical trials. Her early scientific training was in Chemistry (BS ’89), Pharmacology (MS’91) and Immunology (PhD’96). After her post-doc, Amrie was recruited to the NIH to establish the B Cell Biology Group in the Autoimmunity Branch of NIAMS during the human genome sequencing project. She received multiple NIH awards for her work comparing signaling pathways and genes expressed in patients vs healthy individuals, including the prestigious Director’s Award.
AI & Data Sciences Showcase: AMPEL BioSolutions
AMPEL BioSolutions is a technology company who has developed a clinical genomic test in the Immunology space to predict flares and the correct drug for a patient based on machine learning of gene expression (target markets: Pharma, Patient/Physician and Payor).
Machine Learning Predicts Lupus Disease Activity "Flares"
Currently used to select patients most likely to be responders in clinical trials, thereby improving outcomes. Future use will be a decision support biomarker test for physicians to monitor disease activity and most appropriate treatments based on a patient’s genes.