Session Abstract – PMWC 2021 Silicon Valley


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.


Confirmed Presenting Companies:

 Session Chair Profile

Ph.D., CEO, Insilico Medicine, Inc

Biography
Alex Zhavoronkov, PhD, is the founder and CEO of Insilico Medicine (insilico.com), a leader in next-generation artificial intelligence technologies for drug discovery, biomarker development, and aging research. Since 2015 he invented critical technologies in the field of generative adversarial networks (GANs) and reinforcement learning (RL) for generation of the novel molecular structures with the desired properties and generation of synthetic biological and patient data. He also pioneered the applications of deep learning technologies for prediction of human biological age using multiple data types, transfer learning from aging into disease, target identification, and signalling pathway modelling. Under his leadership Insilico raised over $50 million in multiple rounds from expert investors, opened R&D centres in 6 countries and regions, and partnered with multiple pharmaceutical, biotechnology, and academic institutions. Prior to founding Insilico, he worked in senior roles at ATI Technologies (acquired by AMD in 2006), NeuroG Neuroinformatics, Biogerontology Research Foundation. Since 2012 he published over 130 peer-reviewed research papers, and 2 books including “The Ageless Generation: How Biomedical Advances Will Transform the Global Economy” (Palgrave Macmillan, 2013). He serves on the editorial boards of Aging Research Reviews, Aging, Trends in Molecular Medicine, Frontiers in Genetics, and co-chairs the Annual Aging Research, Drug Discovery and AI Forum (7th annual in 2020) at Basel Life, one of Europe's largest industry events in drug discovery. He is the adjunct professor of artificial intelligence at the Buck Institute for Research on Aging.


 Speaker Profile

Partner, McKinsey and Company

Biography
Ziv Yaar is an Expert Partner and has been involved in Digital and Advanced Analytics for over 20 years and in the pharma for over 15 years. Ziv brings experience and expertise as a proven client service leader, experienced at managing large, complex studies with dozen of resources, solving a wide array of pharma problems. He also has a strong cross-channel marketing strategy and analytics background, as well as extensive technology background, which enable him to understand and work with technology teams and help business and marketing stakeholders understand the how technology can affect their business.


AI and Data Sciences Showcase:
McKinsey and Company

McKinsey and Company is a global management consulting firm.

Data Transformation
There is a lot of interest these days at the senior-most leadership of many Pharmaceutical companies in using machine learning and other advanced analytics methods to achieve strategic differentiation. A recent McKinsey analysis found, however that in order for a company to achieve this level, they would need to conduct ~1,000 advanced analytics use-cases per year. This is not tenable today because most Pharmaceutical companies’ take between 4-6 months to perform a typical (non-clinical trial) analytics use-case, instead of the 4-6 week cycle time that they would need in order to achieve advanced analytics at scale.

 Speaker Profile

COO, MMRF

Biography
Michael Andreini joined the MMRF as the Chief Operating Officer in 2019, and is responsible for overseeing day-to-day operations, strategic programs, and alliances across the foundation. Michael brings over 12 years of strategic consulting and operational experience in the life sciences industry. Prior to joining the MMRF, Michael was an Associate Principal at IQVIA in the consulting services organization where he led complex engagements for biopharma, medical device, and non-profit organizations across diverse solution areas including commercial assessments, portfolio analysis, R&D and launch strategy, and operational execution. Before joining IQVIA, Michael worked at Fuld & Company, a boutique consulting firm specializing in competitive intelligence and strategy, and prior to that, at Siemens Healthcare Diagnostics in the Global technical Operations group where he resolved technical issues for immunoassay reagents and systems. Michael earned a B.A. in chemistry with a minor concentration in economics from Colgate University.


AI and Data Sciences Showcase:
MMRF

A pioneer in precision medicine, the Multiple Myeloma Research Foundation (MMRF) seeks to find a cure for every multiple myeloma patient by relentlessly pursuing innovations that accelerate the development of precision treatments for cancer.

Innovation Of Patient-Centered Research Initiatives: MMRF CureCloud
The first-of-its-kind, innovative MMRF CureCloud research study features direct-to-patient enrollment, the first at-home CLIA-grade cfDNA sequencing test for myeloma, and real-world EHR data collection to deliver real-time insights back to patients and their physicians to inform clinical decision-making.

 Speaker Profile

Ph.D., Co-Founder and COO/Chief Scientific Officer, AMPEL BioSolutions

Biography
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

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.

 Speaker Profile

Ph.D., Founder & CEO, QUIBIM

Biography
Angel Alberich-Bayarri is a bioengineer, researcher and entrepreneur in medical image processing and the application of AI methods to radiology. He has experience in the lab-to-market translation of AI models covering unmet clinical needs in neurology, respiratory diseases, musculoskeletal and oncology scenarios. He is author of more than 60 publications in the field of imaging biomarkers, author of more than 15 book chapters and editor of 2 books. He is board member of several scientific societies and panels, such as the European Society of Medical Imaging Informatics (EUSOMII) and the European Imaging Biomarkers Alliance (EIBALL). In March 2020, he was one of the main promoters of the Imaging COVID-19 AI initiative, which currently hosts the biggest worldwide database of COVID-19 CT examinations and is leading the development of a highly accurate model for disease severity scoring and in-patients follow-up. He was named one of MIT Technology Review’s 35 most innovative people in the world under age 35, in 2015.


AI & Data Science Showcase:
QUIBIM

QUIBIM provides an AI platform focused on converting medical images into meaningful data. The company has a portfolio of accurate quantitative imaging solutions across neurology, lung, musculoskeletal and oncology disease areas.

AI and Medical Imaging for Innovation in COVID-19
The presentation will review the main challenges in the field of AI in medical imaging in the most relevant disease scenarios as well as the need for accelerating the lab-to-market transition of tools that can support COVID-19 patients management during the pandemic situation.

 Speaker Profile

MBA, CEO, BeanStock Ventures

Biography
Shawnnah Monterrey is the CEO and founder of BeanStock Ventures, with 20+ years’ experience in medical and life science software product development. BeanStock Ventures is an FDA accredited third party 510(k) review organization. Prior to founding BeanStock Ventures, she obtained a bachelor’s degree in computer science from the University of California, San Diego and an Executive MBA from San Diego State University, then went on to hold product development management positions across numerous global firms, including Illumina, Invetech, Medtronic and Carl Zeiss Meditec. During her time at Carl Zeiss Meditec, Shawnnah and her team successfully launched and obtained several 510(k) clearances for an AI based glaucoma diagnostics and monitoring application, using a neural network and support vector machine, in the early 2000s.


AI & Data Science Showcase:
BeanStock Ventures

BeanStock Ventures provides 20 years of regulatory and software development experience in various healthcare specific domains including but not limited to NGS, diagnostics, the point of care, critical care, laboratory, automation, workflows, and connectivity.

FDA Regulation, A Peek into AI Proposed Regulatory Framework
Artificial intelligence applications rely on diverse datasets to make informed decisions. As datasets grow, algorithms improve in sensitivity and specificity. The challenge remains, how to handle this from a regulatory perspective without hindering innovation and delaying products into the market?

 Speaker Profile

Ph.D., Chief Data Scientist and Co-Founder, OneThree Biotech

Biography
Cory Gilvary’s research has primarily focused on developing new machine learning techniques for increasing the efficiency and innovation of drug development and discovery. She takes the unique approach of combining distinct types of noisy, high-throughput data to maximize algorithmic performance, while also building interpretable models that allow for a deeper mechanistic insight to the mode of action of therapeutics. She has leveraged cutting edge AI concepts across diverse disease areas including, but not limited to, oncology, diabetes and Parksinson’s disease. Outside of her biological research, she spent time developing cutting edge machine learning models at one of the world’s leading quantitative hedge funds. Currently, Cory leads OneThree’s data science and computational biology efforts and much of her early research work formed the core OneThree platform. At the beginning of 2020, she spearheaded OneThree’s internal efforts to provide free toxicity screening to any researchers working on treatment for COVID-19.


AI & Data Science Showcase:
OneThree Biotech

OneThree Biotech is a VC backed startup working to change how new medicines are discovered using biology-driven AI. We are clinically validated and work with biotech and pharmaceutical companies to apply our mechanism focused AI to both pre-clinical and clinical pain points.

Interpretable AI for Early Stage Oncology Drug Discovery
OneThree has created a platform of mechanism focused algorithms to address key questions for the development of targeted oncology therapeutics. Here, we will discuss our work on predicting potential cancer inhibition targets on a patient level. Our interpretable AI, allows us to elucidate the underlying mechanism of our predicted targets, such as exploiting synthetic lethal relationships or downstream suppression of an oncogene. This mechanistic insight enables easier indication positioning and biomarker marker identification in future development.