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

Following the success of the 2022 Science of Stability (SOS) Conference in Philadelphia, we’re excited to announce its return to Barcelona! The …

We are delighted to share our important new open access article: In silico prediction of pharmaceutical degradation pathways: A benchmarking study using …

Throughout 2023, our dedicated team contributed significantly to various journals through authoring and co-authoring a plethora of publications. Here are the articles, …