Biography
Petrina Kamya, Ph.D., is the Global Business Development Director for Insilico Medicine’s end-to-end AI-driven drug discovery platform, Pharma. AI. Before joining Insilico, Dr. Kamya was at Chemical Computing Group (CCG) and Certara. At CCG, she led the sales and business development of molecular modeling software for pharma and biotech companies and academia. At Certara, she consulted with pharma companies on Market Access strategy. During the pandemic, investment banks and management consulting firms turned to Dr. Kamya to provide due diligence on AI-driven drug discovery platform companies. She became very familiar with many of the key players in the space. She saw the potential these companies, including InSilico Medicine, could have in the optimization of the drug discovery and development process. She joined the InSilico Medicine team in August 2020, where she works closely with drug discovery stakeholders interested in implementing AI-driven computer-aided techniques into their discovery pipelines.

Biography
Ziv Yaar has worked on the topic of Digital & Advanced Analytics for 23 years, across a variety of different industries and in pharma for over 15 years. Ziv has worked across many different industries on the topic of scaling advanced analytics, the key topics that business leaders and managers need to know, how to work with technology and data science organizations, organizational processes design of analytics, best-practices in digital & analytics transformations, and strategy. He has served the top 20 global pharma companies in a variety of different studies over the past 10 years both at the country and global level.

AI and Data Sciences Showcase:
McKinsey and Company
McKinsey and Company is a global management consulting firm.

Data Transformation
McKinsey found that Pharmas need to deliver ~1,000 AI use-cases per year to achieve scale. Most take 4-6 months per use-case. We will review our findings on what leading pharmacos are doing to get that down to 4-6 weeks.

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 is an FDA accredited 3rd party review and software product development organization in the life science, digital health and medical device industry.

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?

Biography
Steve is a serial technology entrepreneur with over 25 years’ experience developing and commercializing ground-breaking data science and informatics in the healthcare, life sciences and agri-food sectors. Never afraid to innovate, Steve has an established track record in building world-class companies, teams and products working at senior levels in the UK, EU and US for Fortune 500 and start-up companies. He is a former Global Director of Research Informatics for Astra A/B and has consulted with drug discovery and safety teams in over 20 biopharma companies.

AI & Data Science Showcase:
PrecisionLife
PrecisionLife is changing the way the world looks at predicting, preventing, and treating chronic diseases. Our unique AI and combinatorial analysis platforms generate more insights from patient data than anyone else on the planet to understand disease biology better and stratify patients at unprecedented resolution.

Precision Medicine in Chronic Diseases: Better Outcomes, Faster
Analysis of large patient datasets using unique combinatorial analytics is enabling the stratification of complex diseases into distinct patient subgroups that have different causes and influences. This offers huge promise for innovation in drug discovery and the delivery of personalized care to patients.

Biography
Maddison is co-founder and CEO of Deepcell. She invented Deepcell’s AI-based single-cell analysis and sorting technology with her postdoctoral advisor Euan Ashley and Mahyar Salek, and spun the company out of Stanford University in 2017. She has a multidisciplinary background with experience in electrical engineering, computer science, and bioengineering. Maddison holds a bachelor’s degree in electrical engineering from Sharif University of Technology, as well as a master’s degree in computer science and a PhD in bioengineering from the University of California, Los Angeles. She has published several papers in top-tier journals and has co-invented multiple patented technologies.

AI & Data Science Showcase:
Deepcell
Deepcell offers an AI-powered imaging and microfluidics platform that identifies and isolates viable cells based on morphological distinctions for use in translational research, diagnostic testing, and therapeutics.

Deep Learning Enables Label-free, Real-time Cell Characterization and Isolation
We present a novel technology for real-time identification and sorting of unlabeled single cells in flow using high-resolution imaging and a Convolutional Neural Network (CNN) across multiple cell types including immune cells, malignant cells, among others.

Biography
Dr. Chakravarty leads external research collaborations and pursues opportunities and defines scientific applications of the BIOiSIM platform. He works specifically in the areas of preclinical data translatability, relevant endpoints, and exhaustive review of preclinical models, leveraging our AI/ML platform for the acceleration of the drug development process for potential shortening of the timeline to IND and NDA. His research and development experience encompasses metabolic disease, physiology, in vivo pharmacology, and translational science. He has been in the drug discovery space for 15+ years with one of his antisense compounds completing Phase II clinical trials recently. Prior to VeriSIM Life, Chakravarty led teams at Pfizer, Roche, and NASA. He holds a Ph.D. in Nutrition and Biochemistry from Case Western Reserve University. He has published 18+ peer-reviewed scientific articles, delivered talks at several conferences, and received numerous awards for his contributions.

AI & Data Science Showcase:
VeriSIM Life
VeriSIM Life created a platform that enables AI-driven bio-simulations to de-risk drug R&D decisions by predicting the value before human trials.

AI-driven Accelerated Therapeutics Development for COVID-19
We use in silico modeling using BIOiSIM, an AI-integrated mechanistic modeling platform by utilizing known preclinical in vitro and in vivo datasets to accurately simulate systemic therapy disposition and site-of-action penetration of the investigational compounds implicated in COVID 19 pathogenesis.

Biography
Ofer Mendelevitch has led technical development at Syntegra since its inception, where he has pioneered the use of generative language models to create synthetic healthcare data. Prior to joining Syntegra, Ofer served as Vice President of Data Science at Helix, a population genomics company. He has extensive experience leading complex state-of-the-art machine learning software projects across industries, having previously led data science and engineering teams at several companies, including LendUp, Hortonworks and Yahoo!. Ofer has published several papers and is the author of the book, “Practical Data Science with Hadoop and Spark.”

AI & Data Science Showcase:
Syntegra
Syntegra is the first healthcare company to leverage the breakthrough of machine learning language models (similar to GPT-3) to create patient-level, synthetic healthcare data that maintains full statistical fidelity and patient privacy, enabling increased data use and value across healthcare.

Innovative Machine Learning Models to Democratize Healthcare Data
AI-enabled synthetic data offers a unique solution to the long-standing challenges inhibiting access to healthcare data. We will discuss how modern language models are used by the Syntegra engine to generate synthetic healthcare data with high fidelity and guaranteed privacy.

Biography
Timo Kanninen is CSO and co-founder of BC Platforms. He is the visionary behind BC Platforms’ data management systems. He has long-term experience in software development, genetic epidemiology, statistical genetics, and clinical statistics. Mr. Kanninen has also worked with hospital and occupational health IT systems. Mr. Kanninen studied information technology in production and statistics. He is a co-author on 16 scientific articles published in high-level journals.

AI & Data Science Showcase:
BC Platforms
BC Platforms is a global leader in providing a powerful data and technology platform and data science services for personalised medicine and drug development, accelerating the translation of insights into clinical practice.

Developing and Validating AI/ML Models for Personalised Medicine
Use of clinical and genome data based AI/ML models for Personalised Medicine has the potential to revolutionise healthcare. To ensure that these models work in different environments and populations, diverse Federated Data Partner Network can be used for model development and validation.

Biography
Dr. Wood has 25 years’ experience championing innovative clinical solutions into routine clinical use. She was recognized as one of the top 50 CEOs by Healthcare Technology Report; she also received the Joe Rosenfeld Award for outstanding leadership. In addition to serving as CEO of VIDA, she is currently a board member for iCAD, serves on the Board of Governors at the University of Maryland, and is past Chair of the Board of Visitors of the Graduate School at Duke University. Dr. Wood received her Ph.D. from Johns Hopkins Medical Institutions, School of Hygiene and Public Health. Her Ph.D. work combined quantifying three-dimensional lung structure with changes in lung function using high-resolution CT imaging. She also holds a Master of Science degree in Biomedical Engineering from Duke University, and a Bachelor of Science in Engineering from the University of Maryland, College Park.

AI & Data Science Showcase:
VIDA
VIDA delivers precision lung intelligence to accelerate the therapy pipeline. Our AI-powered analysis is quantitative and actionable, making a breakthrough in the staggering time and cost of respiratory trials.

AI-Powered Lung Intelligence to Drive Clinical Trial Efficiencies
Precise imaging biomarkers of lung diseases are accelerating the therapy pipeline, resulting in substantial ROI for pharma vendors. See how VIDA’s 50+ validated quantitative biomarkers are changing the game for respiratory trials.

Biography
William K. Oh, M.D. is Chief Medical Science Officer at Sema4, a patient-centered health intelligence company focused on precision medicine. He is also an internationally recognized medical oncologist with over 25 years of clinical and translational research experience and leadership roles at major NCI-designated cancer centers. He continues to see cancer patients in his capacity as Clinical Professor of Medicine at Icahn School of Medicine at Mount Sinai. William has authored more than 330 articles, reviews, books and book chapters related to genitourinary cancers. He has conducted multiple clinical cancer trials and has served in key invited roles for the American Society of Clinical Oncology, the American Cancer Society, and the American Urological Association.

AI & Data Science Showcase:
Sema4
Sema4 is a Patient-Centered Health Intelligence Company Leveraging AI, Genomics and Other Deep Data.

REPRESENT: Providing Prec. Oncology Access to All
Sema4 launched the REPRESENT study in community oncology practices caring for patients with advanced cancer in diverse, underserved populations. REPRESENT will perform comprehensive genomic profiling, hereditary cancer testing and clinical data including SDOH and correlate outcomes to these findings.

Biography
Jason is an accomplished start-up founder and executive with experience developing and commercializing disruptive products to solve healthcare’s most challenging problems. He is currently co-founder, board member and CEO of Endpoint Health, a Precision First therapeutics company dedicated to addressing urgent needs in immune-driven critical and chronic illnesses by delivering therapies that are personalized to each individual patient’s biology. Prior to Endpoint Health, co-founded GeneWEAVE, a diagnostics company that developed novel solutions to improve diagnosis and therapy choice in drug-resistant infections. Started in 2010, GeneWEAVE raised $25M in venture financing and was acquired by Roche in 2015. Jason received an MBA from Cornell University and currently lives in San Jose, CA with his wife and daughters.

AI & Data Science Showcase:
Endpoint Health
Endpoint Health is a precision-first therapeutics company dedicated to addressing urgent needs in immune-driven illnesses by developing therapies that are personalized to each patient’s biology.

Rewriting the Rules in Precision-First BioPharma
Learn how Endpoint Health is using it's Precision-First AI platform to develop life-changing immunology therapies personalized to each patient’s biology. Combining therapeutics, diagnostics and AI, the Company is unlocking value for patients, doctors, and healthcare systems.

Biography
Dr. Krzysztof Rataj works at the intersection of medicinal chemistry, biology, imaging and artificial intelligence in the field of drug discovery. He obtained a PhD in Biophysics from Jagiellonian University, and worked on numerous projects in collaboration with scientific teams from Hungary, Denmark and Norway. His team explores the application of artificial intelligence approaches to various aspects of drug design and precision medicine, such as transformers for property prediction and compound optimization, natural language processing methods in protein and nucleic acid research, and computer vision in high content screening and histopathology. Their current endeavor is the marriage of chemical structure and phenotypic screening images in order to create a comprehensive approach to high content screening.

AI & Data Science Showcase:
Ardigen
Ardigen is harnessing advanced AI methods for novel precision medicine. The company’s in-house datasets, together with advanced AI platforms, empower the development of effective therapies.

Enhancing Phenotypic Drug Discovery with AI-based Methods
The resurgence of phenotypic screening as a viable method of early drug discovery opens up a new field for application of AI-based methods. We would like to explore the concept of merging high content image data with chemical compound data to provide new quality in HCS pipelines.

Biography
Hongxin Zhang is the lead software engineer for OncoKB, Memorial Sloan Kettering Cancer Center's (MSK's) precision oncology knowledge base. Hongxin is responsible for the design, implementation, and management of all OncoKB software products. A member of OncoKB since its inception, Hongxin has leveraged his expertise in technology development and bioinformatics to bring the best clinical care to patients.

AI & Data Science Showcase:
Memorial Sloan Kettering Cancer Center
Memorial Sloan Kettering Cancer Center(MSK) in New York City, the world’s oldest and largest private cancer center and one of 51 NCI-designated Comprehensive Cancer Centers, has 135 years of experience dedicated to exceptional patient care, innovative research, and outstanding educational programs.

OncoKB: Memorial Sloan Kettering Cancer Center’s Precision Oncology Knowledge Base
OncoKB, MSK’s precision oncology knowledgebase, contains expert-curated information about the biological and clinical relevance of cancer mutations. It is used to annotate approximately 12000 MSK patient sequencing reports annually. OncoKB is the first somatic human cancer variant database to be partially recognized by the FDA. It is available as a licensed product for research, hospital, or commercial use.

Biography
Dr. Thomas Westerling-Bui received his PhD in cancer biology, focusing on the cell cycle and transcription, from the University of Helsinki Medical School in Finland. He completed a post-doctoral EMBO fellowship at the Dana Farber Cancer Institute in Boston, researching the genomics of breast and prostate cancer. Thomas joined Aiforia to advance the new potential of cancer biology, pathology, big data, and artificial intelligence.

AI and Data Sciences Showcase:
Aiforia
Aiforia equips pathologists and scientists with powerful deep learning artificial intelligence for translating images into discoveries, decisions, and diagnoses. The cloud based Aiforia software aims to escalate the efficiency and precision of preclinical and clinical medical image analysis from oncology to neuroscience and more.

Bringing Precision to Diagnostics with Deep Learning
Deep learning artificial intelligence enables increased speed, accuracy and consistency in medical image analysis. Aiforia's automated, AI-driven solutions supports pathologists in diagnosing some of the most prevalent cancers like breast and lung with greater efficiency and precision; paving the path for personalized therapy.

Biography
Ryan has always stayed at the forefront of technology throughout his 15+ year career in genomics. Focused on uncovering the genetic basis of cardiovascular disease, his work began at UCSD utilizing various gene expression, genotyping, and sequencing methodologies to develop novel small molecule therapeutics for essential hypertension. After leaving academia for the biotech industry, Ryan switched to developing NGS-based molecular diagnostics for hereditary cancer through a collaboration with IBM, using their Watson Artificial Intelligence system, to develop a personalized medicine app for patients. More recently at NanoString, Ryan harnessed his expertise in spatial transcriptomic assays and data analysis pipelines to support the Pharma, Biotech, and the Academic community in southern California with their drug development, clinical trial, and biomarker studies. Ryan is now at the forefront of cloud computing and is excited to help researchers across the globe discover novel insights in their data with ROSALIND.

AI and Data Sciences Showcase:
ROSALIND
ROSALIND is the leading collaborative research platform for knowledge management and multi-omic data analysis. As a secure unified data hub for sequencing and multiplex technologies, ROSALIND combines deep interpretation and interactive visualization for spatial, single-cell, RNA, NanoString, and clinical data.

Advancing Precision Medicine through Spatial and Multi-Omic Data Analysis
Learn how the ROSALIND collaborative analysis platform brings together biomedical, multi-vendor, multi-omic data with leading-edge machine learning.

Biography
Ken leads the AWS Academic Medicine Vertical which includes a team of Principal Trusted Advisors in Digital Health, Hospital Modernization, Precision Medicine, Clinical Care and Informatics, and HealthTech sub-verticals, and a team of field based and customer facing Healthcare Executive Advisors. He has over 30 years of healthcare experience, including founding and taking public a cell and gene therapy company. Prior experience includes being a Chief Clinical Officer, President and CEO for 10 years prior to joining AWS. Ken has a strong background in building and commercializing regulated products in the device, combination product, clinical software, and therapeutic biologics space.

AI and Data Science Showcase:
Amazon
AWS for Health is used by thousands of healthcare customers globally. It provides proven and easily accessible capabilities that help organizations increase the pace of innovation, unlock the potential of health data, and develop more personalized approaches to therapeutic development and care.

Digital Health Data Strategy – The First Step in Precision Medicine
Linking big data at the patient level is essential to enable physicians and researchers to truly test their precision medicine hypothesis. However, different types of data have various value, and it is important for institutions to prepare and implement an upfront data plan that powers research. In this talk, we will present various technology approaches to link and validate existing PHI data.

Biography
Billy graduated from Ecole Polytechnique, AgroParisTech and holds a multiple-awards-winning PhD in Decision Mathematics from Paris-Dauphine University. Over the past 20 years, Billy has developed quantitative methodologies to inform and support strategic decision making in healthcare. He created and led data-driven decision support teams in major public and private organisations. He served as statistical or modeling expert for public Health Authorities (e.g. EFSA, ANSES, WHO, Gates Foundation) and supported 100+ regulatory or reimbursement dossier submissions worldwide. Billy authored 100+ publications, and led hundreds of data modeling or machine learning projects. He is now CEO of Quinten Health, the Real-World Disease Modeling company.

AI and Data Science Showcase:
Quinten Health
As a European leader in artificial intelligence and machine learning, Quinten Health masters interpretable real-world data science, together with predictive disease modeling and cohort simulations. Quinten Health accelerates, de-risks and optimizes data-driven and value-based decision making for health agencies, care providers and pharma industry.

AI-powered Disease Modeling in Real-world for Optimal Decisions
The purpose of this talk is to propose a regulatory-grade, data-integrative and disease-centric approach to accelerate and de-risk trials while maximizing the real-world value of the products in development. We use reference disease modeling plaftorms enabling for virtual cohort simulations.

Biography
Ruby Hsu earned her BA from Harvard University and her PhD in Neurobiology from Columbia University, before completing postdoctoral studies at the University of California San Francisco. She joined Advanced Cell Diagnostics (now a Bio-Techne company) as an early employee and served as the commercial and operational leader of the CRO business prior to becoming Director of Business Development. She is now Director of Biopharma Partnerships at PathAI, a leader in the development and application of artificial intelligence for computational pathology.

AI and Data Sciences Showcase:
PathAI
At PathAI, we’re dedicated to improving patient outcomes with reliable AI-Powered technology and meaningful collaboration with biopharma, laboratories, and clinicians — aiming to provide patients with access to accurate diagnoses and effective treatments.

AI Powered Pathology in Precision Medicine
PathAI is developing AI-powered digital pathology algorithms for translational and clinical development.

Biography
Sarah Jenna is the co-founder and CEO of My Intelligent Machines (MIMs) and was previously an associate professor specialized in genomics and genetics at UQÀM. Sarah received her Ph.D. in Cell and Structural Biology, from Aix-Marseille University in France. She completed her postdoctoral training in cell signalling at McGill University and was Platform Manager of the Montréal Proteomic Network. In 2006, her dual expertise in cellular and genomic signalling led her to be awarded a NSERC (Natural Sciences and Engineering Research Council of Canada) Junior Canada Research Chair in Integrative Genomics and Cell Signaling at UQÀM. At the helm of MIMs, she translates her 20 years of experience and expertise to provide clients with cutting-edge integrative genomics strategies & systems biology while paying particular attention to the specific needs of life scientists working in BioPharma, and research institutes. She was part of the Top 10 Most Influential Women Leaders in 2021 by Exeleon Magazine.

AI and Data Science Showcase:
MIMs
Founded in 2016, Montreal-based My Intelligent Machines (MIMs) is a leader in artificial intelligence & systems biology. MIMs provides Biopharma companies with easy-to-implement augmented intelligence systems, allowing for accurate biological simulations at early R&D stages, to assist life scientists in the development of targeted and personalized therapies.

Use of Augmented Intelligence for Target and Biomarker Discovery
At MIMs, we have developed a unique augmented intelligence system that enables life scientists to capitalize on machine-based computer modelling, distributed computing & federated learning while leveraging their own expertise in life sciences, to identify targets with more clinical potential than classical bioinformatic approaches.

Biography
Shyam has 15+ years of experience in data management and has a strong background in clinical data analysis. Shyam heads up the data science department for the Medical Imaging business segment of Clario. The department oversees standardization of medical imaging data; and creating analysis and models on clinical, operational, and financial data. Prior to this role, Shyam was the head of the Clinical Data Management team at Clario. His experience includes working for Janssen Alzheimer Immunotherapy and Medtronic. Shyam has a Master’s in Data Science and Engineering from UCSD.

AI & Data Science Showcase:
Clario
Clario delivers the leading endpoint technology solutions for clinical trials. Through experience gained from over 19,000 clinical trials delivered including support of 870 regulatory approvals, Clario fuses scientific expertise and global scale into the broadest endpoint technology platform to enable our clinical trial partners.

Medical Imaging Data Standards, Automation and Analysis
Medical Imaging is used to generate the primary, secondary, or exploratory study end points which help determine the safety and efficacy of the treatment in clinical trials. We will present an innovative solution to standardize, automate and analyze this data.

Biography
Rafael leads Genialis company’s effort to model patient biology to realize the promise of precision medicine and therapeutic discovery. He spent nearly 20 years in biomedical research prior to Genialis, publishing on the evolution of innate immune systems, bioengineering of microbes, and genetics of development. He has also nurtured a specialty in developing software for high-throughput molecular design and analyses, co-inventing the j5 DNA assembly design automation tool (which has since been commercialized by TeselaGen Biotechnology). Rafael attended Dartmouth College and then Yale University, where he was an NSF Graduate Research Fellow. He went on to postdoctoral training in Jay Keasling’s synthetic biology group at Lawrence Berkeley National Laboratory, Joint BioEnergy Institute (JBEI), followed by a National Library of Medicine Keck fellowship in Biomedical Informatics at Baylor College of Medicine. In his free time, Rafael enjoys cooking and rock climbing, and raising heirloom tomatoes and two precocious children.

AI and Data Science Showcase:
Genialis, Inc.
Genialis is a computational precision medicines company unravelling complex biology to find new ways to address disease. ResponderID™, Genialis’ clinical biomarker discovery platform, defines, models, and validates actionable biomarkers and optimally positions novel drugs to accelerate translational research and clinical development.

Machine-Learning for Clinical Biomarker Discovery
The research space churns out biomarkers while the clinical space struggles to deliver them for patient reporting. I will discuss biomarker development challenges and describe ML-enabled and ML-enabling solutions Genialis uncovered on the road to validating a clinical assay.

Biography
Serving as SVP of Commercial and Global Alliances at nference, Nic Wilson is an experienced product, technology, and sales leader with a demonstrated history of working in the consumer electronics and SaaS industry. Prior to joining nference, Mr. Wilson served as the VP of Customer Success at Xperi Corporation and Senior Director of Global Customer Success at TiVo. He holds a Bachelor of Arts (B.A.) focused in Computer Science from Lewis and Clark College.

AI and Data Sciences Showcase:
nference
nference partners with medical centers to turn decades of rich and predominantly unstructured data captured in electronic medical records (EMR) into powerful software solutions that enable scientists to discover and develop the next-generation of personalized diagnostics and treatments for patients worldwide.

Powering Quantum Leaps in Human Health
The world’s collection of human health data remains largely unstructured and therefore unusable. At nference, we’re leveraging state-of-the-art technology coupled with deep biomedical expertise to transform semi-structured data and unstructured data, resulting in the largest labeled dataset in healthcare.

Biography
Scott recently joined CDD to help refine and grow its new BioHarmony data services business. Scott has over 30 years of experience in the pharmaceutical research industry. His career has focused on the development and commercialization of informatics tools and services that improve the drug discovery & development process. Scott has served in multiple senior leadership roles including VP, GM at Tripos, Inc. a Computer Aided Molecular Design company, Co-Founder & CEO of ChemNavigator.com an online chemistry services company which was acquired by Sigma-Aldrich Inc., and Commercial Director of Elsevier Life Sciences Professional Services.

AI and Data Sciences Showcase:
Collaborative Drug Discovery
CDD advances science through better data management. It’s CDD Vault® product, is a hosted informatics solution that allows researchers to organize data and experiments and securely collaborate in real time. CDD also offers BioHarmony™ Drug Data Store and Annotator an ML assisted bioassay annotation platform.

ML Bioassay Annotation and FAIR Drug Data
FAIR Drug data and new ML technology for the automated curation and annotation of bioassay protocols.