• IMPLEMENTATIONS OF AI IN HEALTHCARE SUMMIT

  • Times in EDT

  • 10:00

    WELCOME & OPENING REMARKS

  • CHALLENGES & TRANSFORMATION

  • 10:05
    Kilian Koepsell

    From Idea to Research to Implementation: Making a Real Difference

    Kilian Koepsell - Co-Founder & CTO - Caption Health

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    From Idea to Research to Implementation: Making a Real Difference

    Kilian has spoken previously about Caption Health’s approach to address echocardiogram variability with AI. The company has since earned FDA breakthrough device designation and 510(k) clearance for its AI-guided ultrasound system, Caption AI, and announced its first customer, Northwestern Medicine. Not every company with an AI and healthcare idea can say the same. Kilian will illustrate what’s necessary to move beyond the theoretical and create useful technology for medical professionals, improving patient care. He will also discuss the medical settings that can benefit from A (and the challenges), and his take on how AI can democratize care.

    Caption Health CTO and Co-Founder Kilian Koepsell leads the company’s efforts to use the latest in artificial intelligence and deep learning to bring the diagnostic power of ultrasound to more healthcare providers, democratizing access to healthcare and improving patient outcomes.

    Prior to co-founding Caption Health, he worked on developing computer vision algorithms matched to the human visual processing system at the Redwood Neuroscience Institute and UC Berkeley — research he brought to Caption Health’s ultrasound guidance software. He also co-founded White Matter Technologies and was a founding team member at IQ Engines, which was acquired by Yahoo! for its Flickr group. He holds a PhD in physics from the University of Hamburg, as well as two master's degrees in mathematics and physics from the same university.

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  • AI IN HEALTHCARE: TOOLS & TECHNIQUES

  • 10:30
    Camille Marini

    How Federated Learning Puts Patient Privacy First in Healthcare

    Camille Marini - CTO - Owkin

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    Roundtable: Accelerating Drug Discovery by Competitive Cooperation

    Historically, pharmaceutical companies have kept their machine learning models and data strictly confidential. The EU/EFPIA IMI2 Joint Undertaking funded “MELLODDY” (Machine Learning Ledger Orchestration for Drug Discovery, Grant n° 831472) initiative, a 3 year 18.4M EUR effort, brings together 10 leading pharma companies and 7 tech partners to build a new collaborative ML platform that boosts drug discovery model development without compromising security and privacy (including commercial confidentiality of data and models). This new and unprecedented co-opetitive consortium connects over 10 million small molecules and 1 billion molecular assays into the world’s largest chemoinformatics database. Enabled by federated learning, participating pharma companies can benefit from the joint representation of their combined data while keeping the mapping onto their assays strictly confidential. Enabling Federated Learning for the MELLODDY project, Owkin Connect helped to secure the first Federated Learning model for drug discovery to perform at scale. This federate learning platform has been audited to ensure the highest level of confidentiality and has been deployed in the 10 participating pharmaceutical companies.

    3 Key Takeaways:

    *In June 2019, 10 major pharmaceutical companies — Amgen, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, GSK, Institut De Recherches Servier, Janssen, Merck, and Novartis — inked an agreement to build a shared platform called MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery). In partnership with Owkin, NVIDIA, and others, the group sought to leverage techniques like federated learning to collectively train AI on datasets without having to share any proprietary data.

    *Although R&D competition remains as fierce as ever, many pharmaceutical companies engage in various types of cooperation and partnership ventures to help drive innovation. The goal of coopetition — when companies cooperate on certain projects while maintaining a competitive stance — is to make drug development more efficient and effective.

    *In September 2020, the MELLODDY Project met its year one objective with the successful deployment and running of the world’s first secure platform for multi-task federated learning in drug discovery among 10 Pharma companies.

    As Chief Technology Officer of Owkin, Camille currently leads the development of a collaborative machine learning platform designed for data scientists and medical experts. Prior to joining Owkin, Camille was an academic researcher and worked in startups focused on reproducible and traceable AI. She graduated from Mines ParisTech and completed her Ph.D. in applied data science at the Université Pierre et Marie Curie.

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  • 10:55
    Enrico Santus

    NLP for Adverse Event Detection: a Case Study on COVID-19 Vaccines

    Enrico Santus - Senior Data Scientist - Bayer

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    Natural Language Processing for Adverse Event Detection: a Case Study on COVID-19 Vaccines

    Adverse events are among the main causes of hospitalization and death in the world. Pharmacovigilance plays therefore a crucial role in monitoring the drugs released in the market to minimize harm to the patients. In this talk, I will present our Adverse Event Detection system, which was ranked at the top of the Social Media Mining for Health (SMM4H) shared task leaderboard and won the IBM best short paper at the Workshop on Pharma and Healthcare Intelligence (W3PHIAI).

    3 Key Takeaways:

    *Adverse events are the cause of 5% to 8% of hospitalization.

    *The FDA Adverse Event Reporting System has received over 16 million reports until 2018, 9 millions of which are classified as severe and 1.5 of which are related to the death of the patient

    *Because the number of reports increased by 400% between 2007 and 2017, it is necessary to automate their processing and Natural Language Processing offers a way to do so.

    Enrico Santus is a senior data scientist at Bayer. After his PhD at the Hong Kong Polytechnic University, Enrico joined the group of Regina Barzilay at CSAIL, MIT. His academic career includes affiliations with the King's College of London, the University of Pisa, the University of Stuttgart, the Nara Institute of Technology and Harvard. His work touches topics such as NLP in Oncology, Cardiology and Palliative Care. Enrico has also worked on Epidemiology, Fake News Detection, Sentiment Analysis and Lexical Semantics. As of today, Enrico has published over 50 papers, with over 637 citations. He collaborated to the creation of The Prayer (artist: Diemut Strebe), a mouth-shaped robot that pronounces original prayers, generated with Artificial Intelligence, exposed at the Centre Pompidou, in Paris. He was also involved in the creation of Safe Paths, the MIT tracing app.

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  • 11:20

    COFFEE BREAK: 1:1 Speed Networking Session

  • HEALTHCARE SOLUTIONS

  • 11:35

    Sensemaking for Life Sciences in the Age of Big Data

  • David Shaprio

    Speaker:

    David Shaprio - VP of Product - H1

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    Sensemaking for Life Sciences in the Age of Big Data

    The sources of information necessary for healthcare and life sciences professionals to deliver value continue to expand and grow deeper. At the same time, the insights needed grow ever more precise. How will life sciences professionals find the information they need? One of the key challenges is identifying the right healthcare professional or key opinion leader for a given topic, therapeutic area or indication. Ultimately, healthcare is about connections between people, so how do we find the right people? Through the thoughtful application of AI tools in combination with human subject matter experts, we can unlock the hidden knowledge in big data and make the human connections that lead to innovation and improved health and patient outcomes.

    Dave Shapiro is the VP of Product at H1, a start-up focused on creating a healthier future by delivering a platform that connects stakeholders across the healthcare ecosystem. Dave has spent his career building software products as both an engineer and product manager. Dave graduated from the University of Pennsylvania with a degree in Computer Science. He has built enterprise applications to power financial institutions and architected search solutions for media companies. His focus on big data driven products started in fintech and market data and he honed his user experience focus at one of the leading food delivery platforms. Most recently Dave has led product at startups making an impact in healthcare through the use of data to drive better outcomes for stakeholders throughout the system.

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  • Julie Stern

    Speaker:

    Julie Stern - SVP Of Engineering - H1

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    Sensemaking for Life Sciences in the Age of Big Data

    The sources of information necessary for healthcare and life sciences professionals to deliver value continue to expand and grow deeper. At the same time, the insights needed grow ever more precise. How will life sciences professionals find the information they need? One of the key challenges is identifying the right healthcare professional or key opinion leader for a given topic, therapeutic area or indication. Ultimately, healthcare is about connections between people, so how do we find the right people? Through the thoughtful application of AI tools in combination with human subject matter experts, we can unlock the hidden knowledge in big data and make the human connections that lead to innovation and improved health and patient outcomes.

    Julie Stern is the SVP of Engineering at H1, a start-up focused on creating a healthier future by delivering a platform that connects stakeholders across the healthcare ecosystem. Julie graduated from Carnegie Mellon University with a degree in Mathematics and Computer Science. For the last 16 years, Julie has focused on leveraging the power of NLP and Machine Learning to make Healthcare data actionable. In products ranging from revenue cycle management, patient engagement, predicting health events, improving health outcomes, and applying guideline directed medical therapies, Julie has focused on leveraging the power of health data to improve lives.

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  • 12:00
    Laura Kemppainen

    The Patient-Centric Approach to Implementing AI in Healthcare

    Laura Kemppainen - Digital Innovation Lead - Roche

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    The Patient-Centric Approach to Implementing AI in Healthcare

    In this presentation, you will hear what are some of the opportunities of AI in improving the quality of life of patients and creating value for the network. This presentation will inspire you to think beyond the technology, deep dive into the question WHY, and start thinking about how to implement AI in healthcare with a patient- and human-centric approach. Like with any new innovations, as a foundation, collaboration, trust and privacy are the key.

    3 Key Takeaways:

    *Understanding the stakeholder and patient need should be the foundation of digital innovations and leveraging AI

    *Collaboration and co-creation in the network is crucial in order to unleash the value of AI

    *It is not about the technology, it is about the impact, trust and privacy

    Laura is the Digital Innovation lead at Roche, her passion is to create digital innovations and business models that transform healthcare. She is also finalising a PhD with a topic: Future individual-centric and data-driven platforms in digital health. Her other research topics include AI in healthcare and platform business models.

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  • 12:25
    Christophe Aubry

    Hybrid AI Approach to Knowledge Discovery

    Christophe Aubry - Head of Sector Strategy, Healthcare - Expert.AI

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    Hybrid AI Approach to Knowledge Discovery

    Global biomedical content represents critical data for healthcare organizations, which cannot be easily handled by business applications because it is unstructured and varies across different data sources. With speed and accuracy necessities in the medical field, organizations must find a way to overcome this barrier to understanding language. A hybrid approach to AI, combining the strengths of both natural language understanding and machine learning, provides an ideal solution that mimics the human-like comprehension of biomedical content such as clinical trials, real-world data, medical reports, literature, and social media. This capability can help to accelerate drug discovery and development, innovate faster and increase access to healthcare.

    Key Takeaways:

    • How Hybrid AI can accurately transform clinical trials data, real world data and scientific literature into knowledge and insight.

    • How Hybrid AI can overcome the need of exhaustive training data sets required for pure machine learning based approach

    • How Hybrid AI can be explainable by design and overcome the black box phenomenon associated with machine learning

    Christophe Aubry leads business activities in specialized markets for expert.ai, the leading provider of AI-based Natural Language Understanding solutions. As a strategic technology leader focused on delivering solutions that solve customer pain points, Christophe has dedicated the last 20 years of his career to creating business value for clients worldwide. He helped his company establish its presence in North America, earning and consolidating the trust of major clients in Media, Publishing, Life Sciences, or Government sectors. Christophe started his career as a Product Manager at IBM in the early stages of data and text mining. As a co-founder and Vice President Professional Services at TEMIS for more than 10 years, he molded talents to help them reach their highest potential while supervising customer deployments in all geographies and leading strategic service activities. His favorite quote is “A company’s employees are its greatest assets and your people are your product”. Christophe has a deep understanding and passion for A.I. technologies. He holds a Master’s Degree in Applied Mathematics and Computer Sciences.

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  • 12:50

    ROUNDTABLE DISCUSSIONS

  • Mathieu Galtier

    ROUNDTABLE: Accelerating Drug Discovery by Competitive Cooperation

    Mathieu Galtier - Chief Product Officer - Owkin

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    How Federated Learning Puts Patient Privacy First in Healthcare

    Accessing the volume and diversity of data required for robust and precise machine learning is currently one of the biggest limiting factors to the use of artificial intelligence in healthcare. Health data is private, sensitive, often confidential, and can only be processed in compliance with strict institutional, national and federal regulations. This presentation explores how federated learning technology can be used to overcome this challenge and allow developers to access healthcare data for use in machine learning algorithms with full regulatory compliance. Owkin brings this new learning paradigm to all healthcare stakeholders, unlocking the potential for safer, better and more effective medical research with its federated learning platform Owkin Connect.

    3 Key Takeaways:

    *Federated Learning is a new learning paradigm that will help artificial intelligence reach its full potential and, ultimately, make the transition from research to clinical practice. It is a powerful solution for the future of digital health.

    *Owkin Connect is a federated learning platform that unlocks AI, breaks data silos, and protects data privacy across healthcare applications. Its distributed architecture and federated learning capabilities allow data scientists to securely connect to decentralised, multi-party datasets and train AI models without having to pool data

    *Adoption of federated learning across hospitals and pharma companies is expected to lead to models trained on datasets of unprecedented size and diversity and as such have a catalytic impact on precision medicine.

    Mathieu is the Chief Product Officer at Owkin where he leads the design of Owkin product: a collaboration platform between medical researchers and data scientists powered by federated learning. Mathieu graduated from ENS and Mines ParisTech and completed his PhD in Machine Learning applied to Neuroscience at Oxford and Inria. He started his career at Dreem, a neurotech startup, where he directed research and algorithms and led the Morpheo project. He is devoted to deploying AI in a responsible way. He now leads Owkin’s Product team.

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  • Christophe Aubry

    ROUNDTABLE: Hybrid AI and Beyond in Healthcare: Demo & Discussion

    Christophe Aubry - Head of Sector Strategy, Healthcare - Expert.AI

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    Hybrid AI Approach to Knowledge Discovery

    Global biomedical content represents critical data for healthcare organizations, which cannot be easily handled by business applications because it is unstructured and varies across different data sources. With speed and accuracy necessities in the medical field, organizations must find a way to overcome this barrier to understanding language. A hybrid approach to AI, combining the strengths of both natural language understanding and machine learning, provides an ideal solution that mimics the human-like comprehension of biomedical content such as clinical trials, real-world data, medical reports, literature, and social media. This capability can help to accelerate drug discovery and development, innovate faster and increase access to healthcare.

    Key Takeaways:

    • How Hybrid AI can accurately transform clinical trials data, real world data and scientific literature into knowledge and insight.

    • How Hybrid AI can overcome the need of exhaustive training data sets required for pure machine learning based approach

    • How Hybrid AI can be explainable by design and overcome the black box phenomenon associated with machine learning

    Christophe Aubry leads business activities in specialized markets for expert.ai, the leading provider of AI-based Natural Language Understanding solutions. As a strategic technology leader focused on delivering solutions that solve customer pain points, Christophe has dedicated the last 20 years of his career to creating business value for clients worldwide. He helped his company establish its presence in North America, earning and consolidating the trust of major clients in Media, Publishing, Life Sciences, or Government sectors. Christophe started his career as a Product Manager at IBM in the early stages of data and text mining. As a co-founder and Vice President Professional Services at TEMIS for more than 10 years, he molded talents to help them reach their highest potential while supervising customer deployments in all geographies and leading strategic service activities. His favorite quote is “A company’s employees are its greatest assets and your people are your product”. Christophe has a deep understanding and passion for A.I. technologies. He holds a Master’s Degree in Applied Mathematics and Computer Sciences.

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  • 13:15

    COFFEE BREAK: Explore the Expo Area

  • 13:30
    Hye Sun Na

    A Revolution in Healthcare AI: From Bespoke to Industrial Scale

    Hye Sun Na - Director of Product Management, AI - GE Healthcare

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    A Revolution in Healthcare AI: From Bespoke to Industrial Scale

    Hye Sun’s presentation explains what makes up a comprehensive precision healthcare system. The adoption of AI in healthcare also needs to include seamless workflow integration; AI solutions should not only achieve clinicians’ goals, but it all needs to work together. In this presentation, Hye Sun will use her valuable experience at GE Healthcare to show how AI can create a revolution towards precision health, focusing on productivity, capacity, and patient outcomes.

    3 Key Takeaways: *How AI is adding value to healthcare through examples of apps that help you improve quality of care and efficiency.

    *How you can integrate many algorithms into your workflow, without crushing your purchasing team and IT team

    *The expectations of what obstacles you’ll face when adopting AI technology

    Hye Sun Na is an AI product manager at GE Healthcare driving the development of a platform for creating deep learning models. She works closely with device product teams to define the AI strategy and integrate deep learning into GEHC’s portfolio of imaging and clinical monitoring systems. Prior to joining the AI team, Hye Sun was a senior engineer on the CT physics team, leading feature development for GE’s Revolution CT system. She has over 10 years of engineering experience in diagnostic imaging including X-ray, MR, and CT. Hye Sun holds a Biomedical Engineering degree from the University of Texas at Austin and is a member of the American Association of Physicists in Medicine.

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  • 13:55

    PANEL: Harness the Full Value of Your Data

  • Michael Frank

    Moderator

    Michael Frank - Senior Director in the Breakthrough Change - Pfizer

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    Michael is a Senior Director in the Breakthrough Change group, an innovation and transformation center at Pfizer HQ. His mission is to advance the company’s ambition to provide “Breakthroughs that change patients’ lives. His focus is on delivering first-in-class science and winning the digital race, which includes 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 CombinatoRx.

    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.

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  • Claudia Pagliari

    Panellist

    Claudia Pagliari - Director of Global eHealth Programme - University of Edinburgh

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    Claudia Pagliari is a senior researcher and educator based in the Usher Institute, where she is active across the Centre for Population Health Sciences, the Centre for Medical Informatics, the Edinburgh Global Health Academy and the Institute for Science, Technology and Innovation. Claudia directs the Interdisciplinary Research Group in eHealth. While mainly focused on digital health, her research crosses topics, methods and theories from diverse areas, including health technology assessment, science and technology studies, biomedical ethics, management science, data science and policy studies. For example, her recent empirical studies and expert reviews have looked at mobile apps for contact tracing, participatory disease surveillance and medication advice; empathic robots for mental health support; the use of digital innovations at the end-of-life, big data infrastructures, workforce analytics, online health networking, social media misinformation, and the ethics of data mining from conventional and alternative platfoms. Cross-cutting interests include the ethics and good-governance of digital innovations and programmes, in both lower and higher income countries.

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  • Rama Ravindranathan

    Panellist

    Rama Ravindranathan - Senior Director of Technology Strategy - UnitedHealth Group

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    Rama Ravindranathan is an innovator and technologist who solves complex healthcare business problems. Rama focuses on building the product engineering discipline to build the solutions. She works with her business clients to understand their complex issues and creates technology strategy, roadmap to solve those problems in a simplistic way using Agile methodology. She is an innovation champion, who is responsible for promoting innovation through creative problem solving. She coaches’ innovators through the Start-up Accelerator program. Her professional experience includes working as a CRM implementation consultant in addition to extensive programming and development experience. Rama has extensive experience in data management and business intelligence. With this experience she helped build several executive dashboards & data visualizations. Rama has Bachelors in Computer Science and she is PMP certified from Project Management Institute. Rama was a certified Siebel Analytics consultant and implemented Siebel Analytics and Siebel marketing solutions. Rama is the innovation award recipient of UHG, where her innovative ideas were chosen as finalists among 1000 other ideas that were submitted to solve complex healthcare problems.

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  • Han Chang

    Panellist

    Han Chang - Director, Head of Late Stage Oncology - Bristol-Myers Squibb

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    Han Chang is the Director of Head of Late Stage Oncology, Translational Bioinformatics at Bristol-Myers Squibb where he is leading a team of analysts applying cutting-edge bioinformatics, statistics, and machine learning methods. He is working with clinical and large-scale data sets from BMS’s industry-leading late-stage oncology pipeline; influencing development strategies and advancing the BMS late clinical oncology pipeline.

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  • 14:30

    1:1 Speed Networking

  • 15:00

    END OF SUMMIT

  • PLEASE SEE DAY 2 OF THE AI IN HEALTHCARE & PHARMA VIRTUAL SUMMIT SCHEDULE

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