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.

You may also like

“The meeting provided an opportunity to share our common difficulties and discuss solutions to establish robust and accurate methods for analysing nitrites …

Cannabidiol (CBD) is gaining prominence as a sought-after ingredient in skincare and beauty formulations, thanks to its notable anti-inflammatory, antioxidant and anti-bacterial …

Diversity serves as a catalyst for innovation at Lhasa. We believe in cultivating a workplace culture that encourages collaboration, and empowers every …