Keeping track of internal research data in a drug discovery organisation so that the data is stored in accessible formats and named so that others than the data producer can find, understand and use it can be challenging enough.

There's no point in trying to hide it: Aligning processes and integrating tools in a drug discovery organisation is often a bit of a hassle. It requires resources and discipline, which is why it often doesn't happen.

This video will give you an introduction to the grit project tool and how this support the drug discovery process.

Learn how you can use grit project as an analysis tool in your drug discovery process.

In many drug discovery organisations, analysing and evaluating data is a matter of juggling numerous Excel sheets and manually keeping track of the phases of the screening cascade, comparing compounds, and deciding what compounds to move forward. It’s a widely used practice but the drawback is the ...

New release - April 2024 For details regarding new features please refer to the knowledge base. This is a "stabilising" release with a number of improvements and bugfixes but no new features. We are cleaning up and preparing for the feature we will be adding in the next release

The process of curve fitting is a fundamental step in interpreting data in drug discovery, and the process may seem straightforward:

In drug discovery, laboratories generate a lot of data from various pieces of equipment and data systems. Often this data is formatted for a specific use case making it difficult to use efficiently across systems and teams.

Speed of progress is an important parameter in drug discovery. Not just because moving fast is by default good but because there are several potential business benefits of executing the research work highly efficiently.