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Defining AI Strategies to Advance Patient Centricity & Business Outcomes

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With times of crises often spurring innovation, the fight against COVID-19 accelerated the adoption of ML & AI-powered technologies in the race to discover and bring to market vaccines. For pharmaceutical organizations to build on this recent AI momentum, outdated innovation strategies and data models must be redefined. Now is the time for the industry to come together to share learnings and collaborate to achieve scalable AI for maximum gains. Uniting innovation, data, digital and IT leaders from across the entire pharmaceutical product pipeline, the use-case led program at DECODE: AI for Pharmaceuticals goes beyond the hype of AI to identify where the true value lies and what business outcomes are within reach, how to structure your data, and how to navigate your technology implementation and change management journey.


From the Organizers of Renowned Industry Events Spanning Tech & Life Science

Bio-IT World

Featured Speakers

Andrea De Souza
Senior Director, Eli Lilly & Company

Emma Huang, PhD
Director of Data Sciences External Innovation, California Innovation Center, J&J

Falsal Khan, PhD
Executive Director, Advanced Analytics and AI, AstraZeneca

Maliheh Poorfarhani
Director, Digital Health and R&D, Bayer


Chandi Kodthiwada
Head of Product Management, R&D IT, Takeda

Jacob Janey
Scientific Director, Bristol Myers Squibb

Reza Olfati-Saber, PhD

Reza Olfati-Saber, PhD
Global Head AI & Deep Analytics, Digital & Data Science R&D, Sanofi

Tatiana Sorokina

Tatiana Sorokina
Solutions Director, Data Science & Artificial Intelligence, DSAI Innovation Execution, Novartis Pharmaceuticals


Amelia Averitt, MPH, MA, PhD

Amelia Averitt, MPH, MA, PhD
Manager, Clinical Informatics, Regeneron Pharmaceuticals, Inc.

Brian Martin

Brian Martin
Head of AI, R&D Information Research, Research Fellow, AbbVie

Gregory V. Goldmacher, MD, PhD, MBA

Gregory V. Goldmacher, MD, PhD, MBA
Head of Clinical Imaging, Merck & Co.

Jie Cheng

Jie Cheng
Senior Director, Statistical and Quantitative Sciences, Takeda


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Why Attend?



Join Us to Hear:

Identify & Achieve AI Goals & Outcomes

AI for True Patient Centricity

Dissecting the Hype of AI

Short vs Long Term AI Planning

Organizational Change Management

Hiring Talent & Fostering Skills

Emerging AI Technologies to Be Aware

2021 Regulation, Data & Political Considerations

How to Become a Data-Driven Organization

Redefining your Data Strategy & Innovation Model

Overcoming Siloed Data & Integration Issues

Data Monetization & Commercialization Of AI

External Collaboration & Partnerships

Ethical AI Considerations

Tackling Data Biases of Biomedical Data

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