Chat with us, powered by LiveChat

How to better anticipate and mitigate adverse drug reactions [an infographic]

Are you interested in collaboratively using data to predict and avoid adverse drug reactions? The Effiris consortium – currently composed of Takeda, GSK and UCB – is working to achieve just that.

The project aims to help pharmaceutical organisations accelerate drug discovery through machine learning.

Many readers will be very familiar with the fact that one of the biggest challenges in building accurate predictive models within the pharmaceutical drug discovery space, is the limited availability of high-quality data, due to the often-confidential nature of the data. The Effiris privacy preserving data sharing methodology aims to overcome this obstacle.

Read more about the Effiris approach and progress in the infographic below.

anticipating and mitigating adverse drug reactions through machine learning and privacy preserving data sharing

________________

Did you enjoy this blog? Please let us know.

What else would you like us to write about? Please let us know.

Last Updated on January 25, 2024 by lhasalimited

You may also like

At Lhasa, we believe our people are the heart of everything we do. That’s why we’re thrilled to share our new Life …

The Richard Williams Memorial Award, established in 2020, honours the scientific contributions and memory of Dr. Richard Williams. This award recognises exceptional …

Identification and control of impurities in active pharmaceutical ingredients (APIs) and pharmaceutical drug products is critical in drug development. Mirabilis is our …