Day One Plenary Sessions | Wednesday, June 13, 2018
Leverage Big Data for a Healthier World
  • Understand the implications of the data deluge for the world’s largest bio-pharmaceutical company
  • Learn about the drivers behind the data growth, the potential it may hold for our ability to improve health & well-being at every stage of life
  • Examine Pfizer’s partnerships with health systems and tech to deliver better care, improve outcomes, and ensure sustainable success
Josh Raysman, Head, AI Center for Excellence, PFIZER
Remain Innovative Through Disruptive Technology While Navigating an Unknown Regulatory Environment
  • Define an AI practice that balances patient privacy and shared data opportunities to capitalize on AI applications
  • Discuss a policy and user perspective of healthcare data utility and access
  • Ensure HIPAA compliance while still relying heavily on patient data for AI utilization
Martin Lupinetti, President, HEALTHSHARE EXCHANGE
Panel: Develop Internal Buy-In for AI Platforms through Identification Need, Actual Application, and Innovation Need
  • Discuss strategies to present digestible and cohesive information regarding an AI platform’s capabilities and services for internal review
  • Onboard AI systems through satisfactory organizational discipline
  • Develop implementation planning committees to oversee the AI integration
  • Impact of implanting AI in an organization and proposed success and ROI
Ryan Billings, Senior Director, Digital Innovation, AMAG PHARMACEUTICALS
Harry Clifford, DPhil, M.Sci., Chief Technology Officer, CAMBRIDGE CANCER GENOMICS
Maria Palombini, Director, Communities and Initiatives Development, Emerging Technology, IEEE STANDARD ASSOCIATION
David Stark, M.D., Medical Director, Institute for Next Generation Healthcare, MOUNT SINAI
Networking break
Day One Tracked Sessions | Wednesday, June 13, 2018
AI for Life Sciences
AI for Healthcare
Blockchain and Future Technologies
Chairperson’s Opening Remarks
Karim Damji, Senior Vice President of Product Marketing, SAAMA TECHNOLOGIES INC.
Chairperson’s Opening Remarks
James Fackler, M.D., Director, Pediatric Critical Care Medicine Fellowship; Associate Professor of Anesthiology and Critical Care Medicine, JOHNS HOPKINS MEDICINE
Chairperson’s Opening Remarks
Evon S. Holladay, Analytics Executive in Residence, UNIVERSITY OF DENVER
Keynote: Artificial Realities – Use Cases, Experiments and Learnings Applying Artificial Intelligence to Drug Development
  • Identify the range of use cases exploring AI to impact drug development
  • Learn the impact of experiments with AI in drug development underway at two large pharmaceutical companies
  • Discover new opportunities and priorities for AI in the months and years ahead
Rob DiCicco, Vice President, Clinical Innovation and Digital Platforms, GLAXOSMITHKLINE
Craig Lipset, Head, Clinical Innovation, PFIZER
Keynote Case Study: Sheba’s Digital Medicine Innovation Center
  • Examine the operations of the comprehensive, interdisciplinary, multimodality medical simulation center dedicated to performance assessment, patient safety and quality care
  • Accelerating health system innovation through digital health
  • Outline steps to create one comprehensive data center that combs through outpatient, critical care, inpatient and ER data
Eyal Zimlichman, M.D., Deputy Director, Chief Medical Officer, and Chief Innovation Officer, SHEBA — TEL HA SHOMER HOSPITAL
Keynote: Apply Disruptive Technology to Enhance Patient Experience From Clinical Trial to Healthcare Delivery
  • Understand that the true value of life science and healthcare is the data; the medicine is a mere byproduct
  • Recognize that institutions and systems cannot yet balance data sharing and data privacy
  • Capitalize on blockchain technologies to achieve digital inclusion of security and agency
Maria Palombini, Director, Communities and Initiatives Development, Emerging Technology, IEEE STANDARD ASSOCIATION
Build and Implement Strategic Data Platform for Drug Development With Artificial Intelligence
  • Create a platform of curated data that spans the drug life cycle
  • Utilize cutting-edge, high-volume data science technologies and AI algorithms to train and test accurate models
  • Applying AI to the entire drug life cycle, including discovery, development, and commercial strategies
Richard Wendell, Founder and CEO, TELLIC
Apply AI Systems and Wearable Technologies to Improve Surgical Success
  • Predict surgical outcomes for orthopedic patients in the early stages of care
  • Apply wearable technologies combined with AI algorithms to monitor and prevent adverse events/emergencies
  • Monitor patients who have left the hospital to ensure well-being and prevent readmissions
Ken Fernandez Prada, Senior R&D Engineer, Depuy-Synthes Joint Reconstruction, JOHNSON & JOHNSON
Best Practices in Decision Management to Ensure the Subject Matter Expert Is in Control, Not the Computer
  • Review a use case of integrated IoT, devices, and EMR
  • Prioritize AI systems that are able to explain decision-making processes
  • Demand technologies don’t merely spit out insight, but can provide a proof
Vipul Kashyap, Ph.D., Director, Clinical Information Systems, NORTHWELL HEALTH
Operationalize AI and Machine Learning From Theory into Practice
  • Understand influences that could expedite the adoption & application of AI in drug development
  • Discuss the regulatory acceptance for AI technology in across the industry and policies that could change the regulatory landscape for AI
  • Understand industry-wide challenges for the application of AI methods in the development across therapeutic areas
Learning Systems and Precision Medicine for Issues and Directions
  • Discuss the concept and motivation of a data analysis-driven learning system for use in healthcare
  • Consider how new and emerging technologies can be leveraged in learning systems in various ways
  • Provide insight into implementation issues associated with learning systems in healthcare
  • Discuss the broader implications of learning systems, including those involving regulatory oversight and testing
Nicholas J. Schork, Ph.D., Distinguished Professor of Quantitative Medicine,Translational Genomics Research Institute (TGen); Director of Human Biology, J. CRAIG VENTER INSTITUTE
Close the Gap Between Technological Innovations Like Blockchain and Commercial Realities
  • Pair business elements with innovative platforms to establish early-stage tech companies on a commercial level
  • Consider the value of a cohort program that breeds individuals with specific skill sets and ecosystem of collaboration to build infrastructure with profitable potential
  • Realize the role of multidisciplinary foundations to bring new healthcare innovations to fruition
Judith Sheft, Associate Vice President Technology Development, NEW JERSEY INSTITUTE OF TECHNOLOGY
AstraZeneca’s Open Innovation Approach: Pushing the Boundaries of Scientific Collaboration Through Crowdsourcing
  • Examine AZ’s multipronged approach to collaboration to foster novel discoveries and speed the development of new medicines for patients in need
  • Determine best practices for collaborating within industrial-academic partnerships
  • Outline translational bioinformatics approaches to gain insight into novel connections between drugs and indications for the repositioning discontinued compounds — a case study
Leslie Cousens, Associate Director, Translational Medicine and Emerging Innovations, ASTRAZENECA
Transform Healthcare Delivery Through AI
  • Review specific examples of utilizing AI to craft and parse the largest clinical database representing clinical information from 63 million patients collected over 16 years through electronic medical record systems
  • Explore OSU Center for Health Systems Innovation’s efforts to apply AI approaches to the transformation of healthcare delivery, emphasizing on rural healthcare
William D. Paiva, Ph.D., Executive Director, Center for Health Systems Innovation (CHSI), OKLAHOMA STATE UNIVERSITY
AI and Blockchain-Based Platforms Are Wonderful, but Not Easy to Implement
  • Understand key insights from a completed AI project involving a wide variety of data sources and multiple companies
  • Recognize why operational issues may stand in the way of your AI project being completed as fast as magazines make your managers believe
  • Identify how your data-driven, unbiased AI project can be derailed
Dany DeGrave, Senior Director Innovation Programs and External Networks, SANOFI
Networking break
Address Pharma’s Big Data Problem and Even Bigger Text Problem
  • Provide a broad perspective on different Natural Language Processing (NLP) problems in Pharma and how that compares with other industries
  • Review different Deep Learning techniques that can be used to solve Pharma NLP problems
  • Outline how Saama went about solving Adverse Drug Event (ADE) extraction problem
Malaikannan Sankarasubbu, VP of AI Research, SAAMA TECHNOLOGIES
Maintaining and Defending Your Health Brand Online
  • Manage data available online to properly represent your health system or physicians
  • Outline with limited resources how to maintain a system’s online health brand without sacrificing search ranking
  • Hear Norton Healthcare’s approach to providing consumers with the best data on search, ultimately increasing its search traffic
Christy Belden, Director of Digital Marketing, NORTON HEALTHCARE
AI, Data, and Design Thinking: The Trifecta for Personalized and Population Healthcare
  • Leveraging big and small data as a foundation for personalized to population healthcare
  • Learn about AI algorithms and Blockchain-based platforms that drive personalization
  • Consider how design thinking is important for translational research
Nitesh Chawla, Professor of Computer Science and Engineering, UNIVERSITY OF NOTRE DAME
Apply Digital Governance Best Practices to AI Business Integration
  • Discuss strategies to onboard AI oversight to digital governance responsibilities
  • Propose AI applications to monitor and highlight product information available to patients on unauthorized or controlled websites
  • Apply AI systems to automate information updates on web and social platforms that reflect internal changes
Virtual Assistants Supporting Independent Living for Elderly and Remote Patients
  • Leverage technologies and future innovations to benefit all patient populations
  • Understand that the elderly and impoverished are the most overlooked populations but could benefit the most from AI
Sanjay Shah, Senior Director Innovation, DIGNITY HEALTH
Day One Concludes
Day Two Tracked Sessions | Thursday, June 14, 2018
AI for Life Sciences
AI for Healthcare
Blockchain and Future Technologies
Improving Bio-Therapeutic Development Through AI Technologies
  • Curated data collection across development pipelines to enable predictive modeling and automated decision-making
  • Predictive models to incorporate both the complexity of biology and therapeutic development behavior
Keynote: Utilize Predictive Analytics to Save Lives
  • Perform analytics on free-text imaging reports to detect patients with dangerously large abdominal aortic aneurysms
  • Scan 200 million reports in less than one second through real-time natural language processing
  • Convene disparate information streams together to act on perishable, real-time physiological data
James Fackler, M.D., Director, Pediatric Critical Care Medicine Fellowship; Associate Professor of Anesthiology and Critical Care Medicine, JOHNS HOPKINS MEDICINE
Prophylactic AI: Using AI Systems to Prevent Chronic Disease
  • Manage utilization, not prices, to ensure AI systems prioritize health promotion, not episodic diseases
  • Understand consumers’ cognitive behavior to create a holistic digital footprint
  • Use blockchain-based models to address the needs of patients who have the ability but low motivation or limited resources
Evon S. Holladay, Analytics Executive in Residence, UNIVERSITY OF DENVER
Case Study Transform Solid State Drug Development With ML/AI Approaches
  • Effectively harnessing HPC cloud resources for drug discovery
  • How a combination of artificial intelligence, physics, and chemistry is accelerating drug discovery
  • How AI-powered crystal structure prediction can disrupt the pharmaceutical industry
  • Protecting data while leveraging shared, cloud-based HPC resources
  • How highly accurate computations can help companies save money, save time, and lower risk across all phases of drug development
  • Impact of strong partnerships with web servicing and cloud vendors
Yide Alan Jiang, M.D., Ph.D., Chief Strategy Officer, XTALP
Address Legal and Policy Issues Related to the Implementation of AI in Healthcare
  • Consider the legal responsibility of AI developers and users
  • Discuss the main public policy challenges raised by the integration of AI in healthcare
  • Examine AI, reimbursement schemes and integrated healthcare services to understand privacy, data protection and data ownership
Mélanie Bourassa Forcier, Ph.D., Associate Professor, Director, Law and Health Policy Programme, Director, Law and Life Sciences Programme, UNIVERSITÉ DE SHERBROOKE
Decoding the Human Immune System
  • Decoding the human immune system is the prerequisite for accelerating development of next generation vaccines and immunotherapies;
  • Convergence of technological advances from biomedical, AI and machine learning sciences enable decoding the human immune system
  • Cognitive simulation models offer the potential to guide experimental design for complex systems like the human immune system
Wayne C. Koff, Ph.D., President and CEO, HUMAN VACCINES PROJECT
Networking break
Re-Imaging Drug Discovery Through AI
  • Understand AI’s massive potential in drug discovery, but determine the obstacles from pure in-silico end-to-end drug discovery
  • Expand and accelerate traditional approaches to bring substantial improvements to the efficiency of discovery and development
  • Examine Recursion’s technical strategies to accelerate discovery through AI
  • Review AI internal successes in rare disease, immunology and immunooncology
  • Outline Recursion’s execution plan to leverage technology and massive proprietary data sets to build a map of human cellular biology
Ron Alfa, M.D., Ph.D., Vice President, Discovery and Product, RECURSION PHARMA
Partner With Health Systems to Track Medication Adherence and Reduce Readmissions
  • Initiate and manage stakeholder relationships, timelines, budgets and deliverables in AI pilot partnerships
  • Examine case study of improved medication adherence through consumer-facing digital innovation products
  • Coordinate internal alignment to bolster AI pilot successes
Zanub Malik, Project Management Specialist, MYLAN
The Learning Supply Chain: Integrating Blockchain and AI to Drive Immutability and Efficiency Across Networks
  • How life sciences and biopharma organizations are adopting and implementing disruptive technologies to manage product diversion, countering illicit drug supplies while conforming to the mandates of the Drug Supply Chain Security Act (DSCSA)
  • Spanning the “Source,” “Plan,” “Make,” and “Deliver” networks: Aspects of machine learning and how AI is being introduced to train the digital ecosystem that supports these core functions of manufacturing and distribution
AI Vendor Management Through Developing an Internal Governing Process of These Disruptive Technologies
  • Determine critical search criteria in selecting the right AI platform for your needs
  • Identify strategies to benchmark system’s successes and failures
  • Outline specific questions to ensure the vendor is aware of your mission, goals, approach to implementing AI
Jennifer Turcotte, Product Strategy and Management, Personalized Healthcare and Digital Health, GENENTECH
Case Study Learn How AI Is Impacting the Healthcare Environment at Sanford Health
  • Outline Sanford Health’s transformation to centralized data and analytics, separate from the IT infrastructure
  • Uncover Sanford’s steps to organizational success with a centralized team covering data from clinical to operational to HR and to the health plan
Justin Smith, Ph.D., Director of Data Analytics, SANFORD HEALTH
Considerations for Companies Debating Implementing Blockchain- Based Databases Into Their Operations
  • Review commercial applications for blockchain in the industry
  • Contrast the pros and cons of building an in-house system and management team versus contracting a vendor
  • Discuss supply chain integrity as the first pharma target for blockchain
Darshan Kulkarni, Pharm.D., M.S., Esq., Vice President, Regulatory Strategy and Policy, SYNCHROGENIX, A CERTARA COMPANY
Utilize AI Applications to Ensure Pharmacovigilance at Every Step of the Drug Development Process
  • Elevate pharmacovigilance operations through technological innovations and internal collaborations
  • Identify and limit side effects of marketed drugs through AI systems
  • Enhance PV performance and reporting by utilizing developing technologies
Ram Josyula, Master Black Belt Coach and AI Consultant, BRISTOL-MYERS SQUIBB
Utilize AI to Go Beyond Improving Disease Outcomes to Improve Health
  • Utilize AI platforms that improve the quality of care while developing new realms of care that unburden physicians, prevent illness, and predict outbreaks
  • Examine Mount Sinai’s Lab 100’s operations to understand its foundation for clinical direction and diagnosis
David Stark, M.D., Medical Director, Institute for Next Generation Healthcare, MOUNT SINAI
Ensure Clinical Augmentation to Maximize AI Capabilities
  • Achieve high-model performance and accuracy and reduce alert fatigue through organized human oversight and committees
  • Develop an approach to machine learning that allows the system to achieve a positive predictive value
Rishi Madhok, M.D., Chief Executive Officer and Co-Founder, BITMED
Artificial Intelligence’s Impact on Healthcare From Drug Discovery to Digital Health
  • Use AI to discover novel therapeutic targets and build a pharma pipeline
  • Ai-guided clinical development and patient stratification
  • Data-driven AI approaches in predictive analytics and population management
The Diffusion of Digital Health
  • Identify strategies for alliance management with technologies that understand the current medical needs and the future platforms of operations
  • Apply sense-making strategies to ensure data converts to information in the diffusion of healthcare
  • Outline potential downfalls of direct-to-consumer healthcare devices and how to avoid pitfalls
Stan Kachnowski, Ph.D., Chair, HITLAB
Market Outlook for Companies Debating Creating or Buying AI
  • Review commercial machine learning products applicable to the industry
  • Contrast the pros and cons of building an in-house system and management team versus contracting a vendor
Conference Concludes

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