Store, manage, and visualise data across all pre-clinical drug discovery phases

No matter if your data are produced in-house or ex-house by CROs you need to (should) store them in a structured and accessible manner so they can be analysed, retrieved and reused by others as well as be available for future ML and AI algorithms.

In grit you can store your different modalities (small molecules, oligo's, antibodies etc) alongside your pre-clinical assay data from both in vitro, in vivo, DMPK and toxicological data in SEND format.

Hence, with the grit platform we can help you with your scientific data management across the pre-clinical value chain so you can ensure you have a data store with high quality structured - FAIR enough - data for analysis now and storage on the long term.

new grit - compounds overview mockup (1)

Open source version coming up

Right now we are working on preparing an open source version of grit.

We decided to stop selling the platform on a traditional software license and instead offer it free of charge as open source under a GPL license.

We're aiming for a relaunch in Q1 2025. Would you like a notification, when we have something ready for you to download?

Scientific data management made easy

We do scientific data management the simple way. The platform is a no code, ready to use product delivered as open source under a GPL license.

To get started you agree on and configure the required meta data on the modalities you want to store, configure the relevant assay parameters and then start loading data.

When you have data on compounds (oligos, antibodies etc) and experiment results loaded into the platform the SAR functionalities enables the scientists or project managers to configure their own pharmacological overview of relevant compounds vs. most interesting assay results and analyse what compounds to progress.

Or they export the SAR table dataset for further analysis in external tools or by data scientists in Python, R or similar.

Configure for different modalities - small molecules, oligo's and antibodies
Structure > Compound > Batches registration
Support synonyms & combinations
Drag'n'drop assay data upload
Lists & SAR tables
Drug discovery project manager overview
Plot, visualise or export for external analysis

Simple - but FAIRly advanced - scientific data store

You can upload and store not just the small molecules structures (we use RDKit) and compound level meta data but also the individual batch specifik information and thereby ensure the result data are linked to the relevant, used batch.

The platform also supports compound level synonyms as well as support combination therapy whereby two(more) compounds are combined and registered/tested as a new compound.

Some experimental results are fairly simple tabular data which we naturally support. But we also handle more complex data types like in vivo animal level data with dosing groups and other types of meta data information about the study.

Users can add visualisations of the data in the platform out of the box (we use the plotly library) by selecting from a dropdown or for more advanced visualisations, equipment data or specific workflows use one of our focused applications.

Based on the work in different IMI projects we now also support upload and storage of pre-clinical data in the CDISC SEND format as well as clinical data in the CDISC SDTM format. The data formats can be configured so we also handle "modified SEND" where the data does not fully match the classical SEND format.

Our browse feature where users can search across the different types of experiments in the database and view the data on the right hand side.

This enables questions like “Show me all the experiments where compound = XYZ and specie = rat” etc. This is done by opening the filter option.

In the words of...

Words of wisdom shared by our esteemed customers, brilliant collaborators, and valued partners.

grit42 and Zealand Pharma have, for many years, collaborated to effectively report Zealand Pharma’s animal use to the authorities.

Recently, we have been able to further increase our efficiency with the addition of a new overview module that has simplified our ability to track how many rodents we have in our facilities and to plan future study capacity.”

Bill Vestergaard

Principal Scientist, Zealand Pharma

grit42 has given our project team access to enterprise level software tools for data management, archiving and analysis which are uniquely able to work with discovery, clinical and clinical data sets in an interoperable environment.

They are a great company and we are very proud to collaborate with them to try and improve the process of antibiotic drug discovery through the implementation of FAIR data management and tools.

Philip Gribbon

Head of Discovery Research at Fraunhofer ITMP

Grit42 is providing the IMI ERA4TB project with innovative, flexible data management solutions that greatly facilitate the handling of the variety of complex drug discovery and development datasets needed to support world-class TB research.

Carlos Diaz

Founder & CEO, Synapse Research Management

Based on our experience and the ability to organize all data types in a consistent fashion, this platform can be a key tool for any researcher to address key scientific questions within the areas of drug development and translational research activities.

Patrick O'Meara

Data Team Manager, C-Path

As our research in Nucleic acid-based medicine involves data generation from biological and in silico experiments, both from several different sources, it is of utmost importance that our data consolidation process is streamlined and that the stored data is easily accessible, which is what we get with grit42.

Søren Rasmussen

Director Neuroscience Discovery, Contera Pharma

We see a great potential in applying state-of-the-art data management and data integration to leverage our R&D activities and improve our decision making. To strengthen these capabilities, we selected grit42 as our strategic software partner.

Thorsten Thormann

VP of Research, LEO Pharma

For identification of phenotypes of mutants, we use the high-throughput phenotypic microarrays from OmniLog®. The Growth Curves app from grit42 offers a nice and interactive way to analyse this data as well as making our analysis workflow 15 times faster!

Michael Mourez

Bacterial Infections Group Head at EVOTEC