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Innovations, Implementations, and Strategies to Advance Patient-Centricity and Business Outcomes

Cutting-edge technologies have long played a key role in developing and delivering safe, reliable drugs to market, and yet the adoption of advanced analytics tools such as AI & ML, has been relatively slow in pharma compared to other sectors. For AI to make a true and scalable impact enabling patient centricity and desired business outcomes across drug discovery through commercial applications, outdated innovation models and data strategies must be redefined. This dedicated event brings together pharmaceutical executives to help further drive innovation across data and technology and navigate the implementation of ML & AI and to delve into the subsequent business outcomes. Combining strategic discussions on redefining your AI strategy, the value of AI, ethics and trust, risk mitigation, data quality and implementation success stories, this forum facilitates discussions and partnerships to continue the current AI momentum.




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

Bio-IT World

Why Attend?

DISSECT the Hypde of AI and Translate for your Needs
HEAR AI Use Cases an Real-World Evidence from your Peers
GAIN Tools to Become a Data-Driven and Patient-Centric Organization
TRANSITION AI from Ideation to Project to Scale for True Value
IMPROVE Efficiencies and Commercialize AI
SECURE Talent and Optimal Organizational Structures and Mindsets


Join Us to Hear:


Defining/Redefining Your Strategy in the Post Pandemic Era

The Value and Impact of AI

Organizational Change Management Considerations

Policy, Standards, and Regulatory Frameworks

Ethics and Trust

Risk Mitigation and Building Resilience with AI

Emerging AI trends and the Evolving Investment Landscape

Democratizing AI

AI in Pharma Adoption Lessons Learned

Comparing a Build vs. Buy Strategy

Use Cases for AI to Drive Business and Patient Outcomes

Data Skillsets and Hiring Best Practices

Overcoming Data Bias and Establishing Data Equity

Use of AI in Personalized Medicine and Digital Health Partnering and Collaboration Best Practices