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Kyle Holen
Head, Development Design Center
AbbVie

A leader in the field of advanced analytics and data, Kyle helped create and now heads, AbbVie’s Development Design Center where he works with teams all over the world to ensure innovation, health technologies, and data tools are incorporated into AbbVie’s clinical trials. Whether it’s using real-world evidence and machine learning or incorporating wearables, sensors, and other devices into clinical trials, Kyle’s goal is to bring new and better treatments to more patients, faster. Before coming to AbbVie, Kyle was a physician who treated cancer patients and saw first-hand patients battle some of the most devastating diseases.

Day One

Wednesday 18th September 2019

9:10 am | Unlocking the Potential of Machine Learning (ML) in Clinical Development

Leonardo Rodrigues
Vice President, AI & Machine Learning
Berg

Leonardo Rodrigues, Ph.D., is the Vice President of Artificial Intelligence and Machine Learning, where leads the continuous development of BERG analytics-platforms, the analysis of projects across the entire clinical development pipeline, and the research and development of innovative analytics technologies. With more than 15 years of academic and industry experience, he has a solid background in computer science, biology and systems engineering. By advocating that data analytics might focus on minimal data-manipulation and maximum result-actionability, which is achieved by allowing the data to define the analysis parameters and properly balancing innovation/tradition throughout the analysis process, Dr. Rodrigues has established at BERG one of the most efficient and innovative data analysis teams of the industry. He holds a B.Tech. in Data Processing, a B.S. in Molecular Sciences with a major in Bioinformatics, and a Ph.D. in Biochemistry. He concluded his postdoctoral work at the Whitehead Institute-MIT.

Day One

Wednesday 18th September 2019

12:10 pm | Using Probability-Based AI to Augment Clinical Development

Dipen Sangurdekar
Director of Data Science
Bluebird Bio

Dipen Sangurdekar is the director of bioinformatics, data sciences at bluebird bio. He leads data integration and analysis efforts from clinical, molecular and manufacturing data for oncology and severe genetic disorders. Prior to joining bluebird bio, he was Associate Director of biomedical informatics at Biogen, where he led analytics projects for finding genomic biomarkers from multiple sclerosis clinical trial and registry data and on validation of serum neurofilament biomarker for MS disease prognosis. He has a Ph.D. in Chemical Engineering from University of Minnesota and previously worked at GE Research in Niskayuna, NY and Sanofi in Cambridge, MA.    

Day Two

Thursday 19th September 2019

9:10 am | Data Integration & Machine Learning for Gene Therapy Translational Research

George Lee
Digital Pathology Informatics Lead and Data Scientist
Bristol-Myers Squibb

George Lee received his PhD in Biomedical Engineering at Rutgers University and has over 10 years of expertise in the areas of digital pathology, machine learning, and clinical oncology.  He has authored over 30 peer-reviewed manuscripts and abstracts and holds several patents for image-based companion diagnostics.  Currently, at Bristol-Myers Squibb, he is partnering with image analysis vendors to develop and validate pathology image-based pipelines to provide mechanistic and clinically relevant insights into immunotherapy response. Previous to working at BMS, he served as a Research Assistant Professor in the Biomedical Engineering Department at Case Western Reserve University developing machine learning and image-analysis methodologies for modeling the progression of prostate cancer.

Day One

Wednesday 18th September 2019

11:40 am | Use of AI in Computational Pathology for Patient Stratification

Omar Aimer
Pharmacovigilance and Drug Safety Specialist
Brunel-Sanofi

Previously Pharmacovigilance specialist at ANSM Regional Centers Network in Paris, then in Pharmaceutical Industry in Canada. Speaker in several PV events in North America and Europe on AI implementation and impact in PV.

Day Two

Thursday 19th September 2019

2:40 pm | Using Artificial Intelligence to Optimize PV workload

Basker Gummadi
Director Technology and Innovation
Celgene

Basker Gummadi is the IEEE Lead for Digitalization of Clinical Trials leads a community focused on bringing together stakeholders in the pharma industry and academia to identify business cases for clinical trials using blockchain, artificial intelligence, robotic process automation, and big data. He currently works at Celgene as Director  Technology and  Innovations, and prior to Celgene he was at Bayer leading Digital Innovation, and greatly contributed towards Bayer’s foray into blockchain focused on designing clinical trials to be more patient centric. Prior to joining Bayer, Basker held various positions in the pharmaceutical industry, including Business Solution Manager at Hoffman-La-Roche, Assistant Director at Schering Plough. He enjoys volunteering in the community and coaching  anyone who is interested on topics related to disruptive innovation, and technology breakthroughs

Day One

Wednesday 18th September 2019

2:40 pm | Combining Blockchain, Machine learning & Process Automation to Optimize the Future of Clinical Development

Ameya Phadke
Digital Health & Technology Transactions Lead
Chiesi Pharmaceuticals

Ameya currently leads Chiesi’s corporate development & partnering activities related to technology & digital health. In this role, he helps drive the company’s technology strategy via identification of business needs, the scouting & sourcing of technology partners to fill those needs and finally- leading the transactions to realize those partnerships. Prior to Chiesi, Ameya spent a number of years in progressively increasing roles spanning R&D, strategy & market intelligence at both, Fortune 500 medtech companies and early-stage informatics companies, working on topics ranging from genomics to digital health. Ameya holds a Ph.D. in Bioengineering from the University of California- San Diego and a B.S.E. in Bioengineering from the University of Pennsylvania.

Day One

Wednesday 18th September 2019

2:10 pm | Panel Discussion: How Do You Build a Business Case Behind an AI Platform?

Ed Addison
CEO
Cloud Pharmaceuticals

Ed Addison, is Chairman and CEO of Cloud Pharmaceuticals, an established leader in Artificial Intelligence based drug design and development located in Research Triangle Park. Ed is also advisor to Drug Logic, an AI-based drug safety venture, to Parallel Profile, a pharmacogenomics testing company, and he serves on several other boards. His expertise is in deploying exponential technologies in health care, life sciences, artificial intelligence enabled ventures, and information technology. With a technical background in Artificial Intelligence and a strong business development and capital raising background, Ed is an established serial entrepreneur of disruptive ventures. Ed started 7 companies, funded 5 of them and exited 3. He has twice been named "Entrepreneur of the Year". He has advised 7 venture capital funds and over 20 early stage ventures

Day One

Wednesday 18th September 2019

9:40 am | Using AI & Data Science to Rapidly Discover Precision Medicines by Analyzing Failed Phase 3 Trial Data

Israel Gutierrez
Vice President, Pharmacovigilance & Drug Safety
Geron

Israel is an accomplished Global Executive with 23+ years of experience building multi-therapeutic area medical affairs, clinical development, drug safety.  He is presently the VP of Pharmacovigilance and Drug Safety in the rapidly expanding Geron Inc in the USA.  Over the last 5 years he has worked with multiple companies in many layers of executive management in the areas of Drug development, Risk Management, Artificial Intelligence implementation and PV Strategy. He has provided leadership of multifunctional groups across many companies including Geron Inc, EMD Serono, Neurocrine LLC, Watosa Therapeutics, PRA Health Sciences, Vicapsys, Pharmacyclics, Abbvie, Exelixis,  Genentech, Roche Ltd, Celgene, Pharmion Corp, etc.. He has completed Artificial Intelligence business strategy implementation curricula at the Massachusetts institute of Technology (MIT), High Performance Leadership management at  Univ Of Chicago, Clinical Trial Administration in University of California San Diego (UCSD) and  is a physician and surgeon from Universidad Autonoma de Guadalajara, Science Fellow in Cardiology and Endocrinology from University of Southern California (USC).   Due to his many contributions to society he was bestowed a Fellow of the Royal Society of Public Health in London, and a Fellow of the Royal Society of Medicine

Day Two

Thursday 19th September 2019

1:40 pm | Exploring the Emerging Pharmacovigilance Applications of AI & Machine Learning

Jennifer Gentile
Senior Vice President, US Clinical Operations
Ieso Digital Health

 

Day Two

Thursday 19th September 2019

12:10 pm | The Road to Digital Therapeutics: Using AI to Improve Patient Engagement to Advance Mental Healthcare

Rasmus Hogreffe
Head of Virtual Clinical Trials
Leo Innovation Lab

Rasmus Hogreffe joined the Leo Innovation Lab in January 2019 and is currently the Team Manager of the Virtual Clinical Trial project, with the main goal of improving treatment for patients, by making trials better and faster than ever before, using digital and remote innovations. He holds a Master in Medical Science (MSc. Medicine) from Aalborg University, Denmark and has, since 2010, been working in the healthcare industry in various positions within clinical research & development. Rasmus has extensive experience in the pharmaceuticals industry both within marketing, medical market access, HEOR, project management, sites-optimization, and study-start up. Rasmus has been involved in more than 40 clinical trials, giving him a broad knowledge regarding every aspect of clinical research.  

Day Two

Thursday 19th September 2019

11:10 am | Case Study: How AI Is Being Harnessed in Designing Decentralised Trials

Qasim Bukhari
Postdoctoral Research Associate
Massachusetts Institute of Technology

Dr. Qasim Bukhari is a computational neuroscientist at McGovern Institute for Brain Research at Massachusetts Institute of Technology (MIT), in the lab of Prof. John Gabrieli. He is an expert in applying machine learning tools to develop personalized medicine tools in psychiatry. He holds a PhD in computational neuroscience from Swiss Federal Institute of Technology Zurich (ETH Zurich). He has worked with world leading neuroscientists including Terry Sejnowski, John Gabrieli, Markus Rudin, Klaas Enno Stephan, David Borsook and Lino Becerra. His unique contribution to research is integration of sophisticated engineering tools to ask translational and basic neuroscience questions by combining expertise in neuroscience and engineering. He has worked with pre-clinical, clinical and basic psychological brain data from fMRI, MRI and DTI to study the relationship between different conditions, identify differences in brain connectivity and investigate the neuroscience basis of those differences.

Day One

Wednesday 18th September 2019

11:10 am | Using ML to Develop Personalized Medicine for Psychiatric Patients

Mark Michalski
Executive Director
MGH & BWH Center for Clinical Data Science

Mark H. Michalski, MD is the Executive Director of the MGH & BWH Center for Clinical Data Science, which is focused on the application and translation of novel machine learning techniques into clinical practice. Previous to this role, Dr. Michalski held leadership and operational roles at early-stage companies in the medical software and device domain, including Butterfly Network and Hyperfine Research.  Dr. Michalski held additional strategic roles in healthcare-focused efforts at Google and Genentech.  Dr. Michalski completed his radiology residency training as a Holman Fellow at Yale-New Haven Hospital. He graduated with a degree in Cybernetics from the University of California at Los Angeles with multiple honors and received his medical degree from Stanford University.

Day Two

Thursday 19th September 2019

10:10 am | Translating Machine Learning Solutions in the Clinical Practice

Peter V. Henstock
AI strategy & Machine Learning Technical Lead
Pfizer

Peter Henstock is working to transform Pfizer using AI and Machine Learning. He is the Machine Learning and Technical Lead in Pfizer’s Digital group based in Massachusetts. He holds a Ph.D. in Artificial Intelligence from Purdue University and Master’s degrees in Biology, Software Engineering, Statistics, Applied Linguistics, and Image Processing. Before joining Pfizer, Peter worked at MIT Lincoln Laboratory in image processing and computational linguistics. He also teaches graduate level Machine Learning & Data Mining and Software Engineering at Harvard University.

Day One

Wednesday 18th September 2019

1:40 pm | Infrastructures, People Structures, & Problem Structures: Managing the Shift to AI

Gregoire Versmee
Senior Manager, Medical Informatics
Pfizer

Dr. Versmee is an Emergency Physician who received his MD from the University of Poitiers, France. He worked for 5 years as a clinician in an Emergency Department at the University Hospital of Bordeaux France. He led the clinical and epidemiologic research in parallel to his clinical activities. His research interest was in neurological (stroke, TBI, seizure) and cardiovascular disorders (EKG interpretation and atrial fibrillation). He moved to Boston in 2016 and obtained a Master of Public Health's degree in Health Management from Harvard T.H. Chan School of Public Health. He then joined the Department of Biomedical Informatics at Harvard Medical School, working on NIH Data Commons project, aiming to create an infrastructure to store and compute biomedical big data (clinical, genomic and imaging). Since February 2019, Dr. Gregoire Versmee joined the Digital Medicine & Translational Imaging group at Pfizer, located in Cambridge MA. This group is dedicated to develop new digital biomarker using wearable devices

Day Two

Thursday 19th September 2019

11:40 am | Implementing Digital & Wearables Devices in Clinical Trials: A Collaborative Process

Michael Frank
Director, R&D Strategy, World Wide Research and Development
Pfizer

Michael is a Director, R&D, Strategy and Consulting, in Pfizer’s Chief Business Office.  His group’s mission is to advance strategy and innovation in pharmaceutical development across all therapeutic areas.  His current focus is expanding the role of Artificial Intelligence in both business and drug discovery to increase productivity and identify new therapies to help patients. Prior to Pfizer, Michael was a consultant at Strategy& (a PWC company) and PA Consulting.  He was also VP of technology at Phosplatin Therapeutics, a NYC biotech startup, and Director of BD and Commercial Operations at Forma Therapeutics (formerly CombinatoRx Singapore). Michael lives in Brooklyn, and in his spare time enjoys helping entrepreneurs get their ideas to market; with several successful launches, from KickStarter to biotech IPOs. His own inventions include a kitchen gadget for SkyMall, a dual language eReader App, and several medical diagnostics and products. He has an MBA from Columbia Business School, and MS in Biomedical Engineering from Boston University, and a BA in Biology from University of Michigan.

Day One

Wednesday 18th September 2019

2:10 pm | Panel Discussion: How Do You Build a Business Case Behind an AI Platform?

Hari Singhal
Lead Data Scientist
Roche

Dr. Singhal has experience in leading projects that apply big data, machine learning and artificial intelligence techniques for understanding molecular mechanisms that promote cancer and to deploy the generated knowledge for improvement of cancer care. More recently Dr. Singhal has been researching the immunotherapeutic basis of blocking PDL1 for treating patients with advanced solid tumors of lung, renal and urothelial tissues at Roche. Previously, Hari was a cancer genomics scientist at Harvard Medical School. He completed his PhD in oncology at University of Chicago and Masters in biomedical engineering from Johns Hopkins University.

Day Two

Thursday 19th September 2019

8:40 am | Harnessing Machine Learning & Artificial Intelligence for Biomedical Research

X’avia Chan
Clinical Research Associate
Stanford University

X’avia has been in the management of scientific research and clinical trials for 10+ years. As a clinical trial professional, she has helped the stakeholders in the start-up, execute and close-out cycle of multiple clinical trials, and ensured that they were all within budget, on time with full compliance with the federal regulations and policies. In this fast-paced and dynamic health-care business, she has overseen 15+ clinical studies spanning from cardiovascular disease, diabetes, and oncology, published 11 peer-reviewed manuscripts, delivered 21 international/national presentations, prepared grant proposals/white papers/executive summary reports to internal/external stakeholders, and helped bringing in US$11,000,000 intramural revenue, so to substantiate further growth of the organizations

Day Two

Thursday 19th September 2019

2:10 pm | Is it Possible to have AI-ML Circumvent the Bottlenecks in Clinical Trial Management?

Bin Li
Director of Computational Biology
Takeda

Dr. Bin Li leads a translational bioinformatics team at Takeda’s global computational biology organization. His team provides computational supports on both forward and reverse translational research, on multiple therapeutic areas including oncology, GI, neuroscience, and rare diseases. They develop methods, build predictive models, and do data-driven exploratory analyses for biomarker and patient stratification needs. His team is also responsible on method evaluation and pipeline building for various NGS platforms, including WES, RNA-seq, and targeted NGS panels.

Day Two

Thursday 19th September 2019

9:40 am | How Machine Learning Derived Drug-Sensitivity Models Can Help Clinical Proof-Of-Concept Studies