2nd Annual Pharma AI Summit

Key facts

Date: 8 — 9 April, 2021

Place: Virtual Summit

Conference Overview

Artificial Intelligence promises vast opportunities for economic and societal benefits in the pharmaceutical industry, lifesciences and healthcare including care delivery with digital health. As data applications supported by AI become more advanced, the whole healthcare value chain has been affected. New forms of drug discoveries and pharma workforces are going to evolve. At the same time, the collection of real-world evidence using AI platforms will alter the role of patients. Among these new technologies, it is important to follow up the developments and discoveries effecting pharmaceutical industry.

This conference provides a comprehensive view of the role that Artificial Intelligence plays, the key challenges and opportunities, as well as the strategic perspective on industry change. In times of disruptive innovation, success is based on a company’s ability to adapt, innovate and collaborate. This event therefore serves as a platform that fosters industry relationships, providing the opportunity for the development of innovative business solutions. We invite you to discuss and debate these challenges in a dialogue amongst top professionals in Pharma and Artificial Intelligence.

Key topics

How predictive models generated with AI could be effectively used in pharma?
How Artificial Intelligence helps to reach truly data-driven drug discovery?
How can advancements in AI and ML tools improve prediction of infectious disease outbreaks? What kinds of innovative public-private partnerships can be used to develop new AI tools? How does the pharma industry invest in the right AI solutions to deliver the right drug?
How Real World Evidence can make drug development cheap and more effective?
What is the best way to validate Clinical Trial Data with Artificial Intelligence?
What are the obstacles in the clinical trials for patients, physicians, IRB/HA, legal, Industry?
How AI can help in management, transmission and interpretation of imaging data?
How AI can help to interpret genomic variations and their effects on cellular responses? How AI is playing a role in managing medication safety at multiple levels?
How AI is used for knowledge sharing based on scope of collaborations and business models?