Chat with us, powered by LiveChat How To Better Anticipate And Mitigate Adverse Drug Reactions [an Infographic] | Lhasa Limited

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

How do you assess nitrosamine impurity risk? Work through five steps: identify where nitrosamines could form, gather existing mutagenicity and carcinogenicity data, …

by David Ponting, Senior Principal Scientist, Lhasa Limited On 24 September 2026, the US Food and Drug Administration (FDA) published a guidance …

Forced degradation study design that is both defensible and efficient requires insight into the specific reactivity of an API before work begins …