Unlearn is the developer of the first machine-learning technology that creates digital twins of patients in clinical trials to enable smaller, faster studies. Unlearn works with pharma sponsors, biotech companies, and academic institutions to optimize human clinical trials with TwinRCTs™
Genomenon’s AI-driven genomic engine leverages billions of genetic associations between diseases, phenotypes, and therapies found within the medical evidence. They deliver a comprehensive genomic landscape for every disease, including rare, neurodegenerative, and genetic diseases, as well as somatic and germline cancer.
Armed with a comprehensive base of molecular biomarkers and disease mechanisms, Genomenon’s customers expand their genetic knowledge of the disease drivers by a factor of 10-20X to accelerate target discovery, identify genetic biomarkers for better clinical trial stratification, and develop CDx for regulatory approval
I look forward to speaking in this forum to share latest thoughts on the evolving role of ML/AI in the life sciences, hear from some of our industry’s top thought leaders at the intersection of data-sciences and life-sciences, and gain new insights into the application and integration of AI across programs, projects, and pipelines. With the many venues available discussing the role of ML/AI in pharma and biotech, I have found the AI in Pharma: Clinical Trials Summit venue to be a practical forum at the intersection of methods and application that has been a refreshing and catalytic venue for ML/AI insight with real-world and relevant case studies and examples.
I am looking forward to speaking at the AI in Pharma: Clinical Trials because it provides me with an opportunity to present our novel data science methods geared towards accelerating drug development, improving patient/site participation, and reducing risks across the clinical portfolio. I’m really excited to meet with my peers and fellow data scientists from across the pharmaceutical industry to discuss the latest innovations in clinical data science, data management, and advanced analytics.
Deep dive into the biggest data, regulatory and organizational challenges hindering the widespread adoption of AI in Clinical Trials. This summit covers topics such as operational opportunities, leveraging AI for patient recruitment, using AI to personalize the clinical trial experience and predict therapeutic response.
AI in Pharma: Clinical Trials brings together senior leaders from across the pharmaceutical industry to showcase cutting edge developments. This summit provides an opportunity to get exclusive insights from experts from Pfizer, Janssen, Neumora, Roche, Genentech and more.
With AI in Pharma Summit now split into two dedicated days for Discovery and Clinical Trials, each day will deep-dive into the crucial, specific challenges for each stage of the drug development process. This co-located event provides a comprehensive offering, bringing the industry together under one roof for one or two days of learning.
John Reynders, PhD MBA, is the Chief Data Sciences Officer at Neumora Therapeutics, a biotech focused upon precision medicines for brain diseases. John is also the founder and CEO of Latent Strategies, LLC, an AI start-up applying data sciences and game theory to business strategy and education. John has over 25 years of leadership experience in life sciences, data-sciences, and technology in organizations spanning early-stage biotechs, multi-national pharmaceuticals, and a top U.S national research laboratory. John’s leadership roles have included VP, Data Sciences, Genomics, and Bioinformatics at Alexion, the founding CIO of Moderna Therapeutics, VP of R&D Information at AstraZeneca R&D, VP Integrative Neuroscience and Biomarkers at J&J, and Director of the Advanced Computing Laboratory at Los Alamos National Laboratory. Dr. Reynders received a Bachelors, in Mathematics from Rensselaer Polytechnic Institute, a PhD in Applied and Computational Mathematics from Princeton University, and a Masters in Business Administration from the Northwestern University Kellogg School of Management.
Ryan is the Global Head of Data Science Acceleration at Roche & Genentech where he leads a team of data scientists, data engineers and software developers to develop products and capabilities that enable scientific insight generation for the clinical trial portfolio. Ryan has worked for Roche for 19 years and has held multiple data science leadership roles before his current role including building and leading the personalized healthcare analytics team who generated novel insights from real world data sources including electronic medical records, omics datasets and images. Ryan also leads the Roche Advanced Analytics Network (RAAN) which is a community of over 1500 AI and machine learning enthusiasts from 40 Roche locations across the globe. Ryan’s background is in Statistics and Computing and he has a passion for advanced analytics, new technology and understanding & fostering team culture and engagement.
Ariel V. Dowling, PhD is a Senior Director and Head of the Sensing and Measurement group within the Data Sciences Institute at Takeda Pharmaceuticals. In this role, her group oversees the assessment, validation, and deployment of digital devices and endpoints across the organization. She was previously a Senior Clinical Data Scientist at Biogen Inc where she managed the wearable sensors deployed in clinical trials for Parkinson’s Disease. Ariel was also the algorithm team lead at MC10 Inc and worked at BioSensics LLC. Ariel holds an MS and PhD in Mechanical Engineering from Stanford University and an AB and BE in Mechanical Engineering from Dartmouth College. She currently serves on the Strategic Advisory Board of the Digital Medicine (DiMe) Society.
Amir Emadzadeh is a Director of data science at Gilead sciences, and an adjunct Professor at California Science and Technology University (CSTU). He has more than 10 years of work experience at top Silicon valley companies, including Qualcomm, Nvidia, and Google (Waymo). He holds a PhD in Electrical Engineering from University of California, Los Angeles (UCLA). His current focus is on improving clinical operations using data science. He is working on many exciting ML/AI/Modeling problems including extracting information from Pharmaceutical texts using NLP, image classification, clinical trial site selection, enrollment forecast, and risk-based monitoring.
Mohsen Hejrati is a computer scientist focused on biotechnology and healthcare. Currently, he is a director of AI & Cloud Engineering at Genentech and co-founder of Galliot (technology consulting). In the past, Mohsen worked as a robotics scientist for self-driving cars at Google[X], and he also founded Maktabkhooneh, the largest Farsi MOOC (served over 18 million students so far, and as of right now, 7 million active students each year), and launched several other startups. Mohsen completed his Ph.D. in Machine Learning and Computer Vision at the University of California, Irvine.
Qinghua Song is the Senior Director and Head of Data & Statistical Science, in Kite Pharma (A Gilead Company). He has nearly 20 years of data and statistical research experiences and comprehensive industry experiences across various stages of drug discovery and development (from research, preclinical, translational science to all phases of clinical trials). He has worked in Merck, Genentech and Gilead Science. He is the author/co-authors of more than 20 peer-reviewed, high-profile indexed publications (including Nature, PNAS, Science of Translational Medicine) and more than 50 presentation/posters in scientific and statistical conferences. He received his Ph.D. (2005) and M.S. (2002) in Biostatistics from University of Wisconsin-Madison.
Alex Aronov is Executive Director and Head of Data Science at Vertex Pharmaceuticals, a function he co-founded in 2017 to address data-centric problems across the entire business through application of advanced analytics and machine learning.
Previously, Alex led the Discovery Informatics team at Vertex, with responsibility for HTS content and enrichment, the global chemogenomics initiative, as well as the company’s toxicogenomics efforts. He started his career as a computer-aided drug design scientist and was involved in projects in oncology, inflammation, rare diseases, and antivirals.
Alex serves on the Drug Discovery for the Nervous System committee at the Center for Scientific Review/NIH and is a board member for MIT delta v entrepreneurship bootcamp at the MIT Martin Trust Center. He is an author of over 30 peer-reviewed manuscripts and an inventor on over 40 international patent applications. He holds a PhD in Chemistry from the University of Washington and an MBA from MIT Sloan School of Management, and completed postdoctoral training at the University of California, San Francisco School of Pharmacy.
Steve is a technology and business leader with 20+ years of experience in clinical research, health analytics, consulting, and software development. Steve has been with TriNetX since inception leading the development of our technology platform. Prior to TriNetX, Steve built and led engineering teams at Perceptive Informatics and PAREXEL. Before that, Steve was a technology consultant for several Fortune 1000 and startup companies and co-founder of an internet infrastructure company. Steve has a BS in Engineering from Cornell University and an MBA from Babson College
Luis is a scientist at heart with interest in business and innovation. Before joining Unlearn, Luis worked in clinical development at Biogen focusing on study design and execution of clinical trials and as medical writer at Medpace focusing on developing a variety of regulatory documents in close collaboration with regulatory affairs folks. Prior to that, Luis conducted neuroscience research on neurodevelopmental disorders such as Fragile X Syndrome and Down Syndrome at Children’s Hospital in Washington DC and at Boston University. He has co-authored several peer-reviewed papers and served as peer-reviewer for a number of scientific journals. He holds a PhD from University of Malaga (Spain) and an MBA from IE Business School (Spain).
Bringing together senior-level executives from across the industry, the AI in Pharma: Clinical Trials Summit promises an unrivalled networking and learning opportunity for everyone working in this space.
AI in Pharma: Clinical Trials provides a rare opportunity to showcase your offering to a dedicated, world-class audience. Spaces are limited this year, please contact our commercial manager, Tom (firstname.lastname@example.org) to discuss opportunities for involvement.
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