grit is enterprise-level data management made accessible to everyone.
The open source platform allows you to store, manage, and visualise your data across all pre-clinical drug discovery phases. Structured, accessible, and ready to be analysed, retrieved, and used in AI algorithms.
In grit, you can store your modalities alongside your pre-clinical assay data from both in vitro, in vivo, DMPK, and toxicological data in SEND format. You get a data store with high-quality, structured, and FAIR data for analysis now and long-term storage.
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 configure the required metadata on the modalities you want to store, configure the relevant assay parameters, and then you’re ready to start loading data.
You can easily filter assays and compounds based on metadata to get the overview of your data you need for analysis.
We will also be adding SAR and project functionality to the platform. This means that when you have data on compounds (oligos, antibodies, etc) and experiment results loaded into the platform, the SAR functionalities enable the scientists or project managers to configure their own pharmacological overview of relevant compounds vs. most interesting assay results and decide which compounds to progress.
Or alternatively, they can 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, oligos, antibodies, etc)
Structure > Compound > Batches registration
Controlled vocabularies
Support synonyms & combinations
Drag'n'drop assay data upload
Plot, visualise or export for external analysis
Lists & SAR tables (upcoming functionality)
Drug discovery project manager overview (upcoming functionality)
We've answered some of the most frequently asked questions here.
Any other burning questions?
Don't hesitate to send Marvin a message at marvin@grit42.com.
That’s easy. Either you go to GitHub and grab the code, or you follow the instructions in the README file on GitHub to download the Docker image and run the full platform in Docker.
The platform was originally developed by grit42, a Copenhagen-based software company built on +25 years of experience in managing data and developing software for drug discovery data management. We continue to improve and add functionality to the platform.
grit is published under a GPL license, which basically means that you can use it and do with it what you please - also if you are a company.
However, if you consider distributing it to others, certain responsibilities apply. Read more about GPL here
In general, we use GitHub for that, so go there to report bugs, suggest features, start a discussion, etc.
If you’re interested in a service contract for support, reach out to us at contact@grit42.com and let’s talk about how we can help.
Yes, absolutely. You - or an admin in your organisation - can define your own “modalities” in the platform and what metadata to store on them.
So, as an example, if you work with oligos, you can add a new modality (compound type) called oligo and fully configure the data columns you want to store in the platform on each oligo. The platform can handle several different modalities simultaneously.
Yes. Then you just ignore the assay/experiment part.
If you work with small molecules, you will get a fully functional compound database with structure viewer, exact match and substructure searching (via RDKit), and other filtering options as well as the ability to export subsets for further analysis.
The assay part of the platform can also be used to define in silico “assays”, so if you run prediction models, you can load the data into the platform, linked to the relevant compounds/structures, as well.
You can upload and store not just the small molecule structures (we use RDKit) and compound-level metadata, but also the individual batch-specific information and thereby ensure the result data are linked to the relevant, used batch.
The platform also supports compound-level synonyms, as well as supports combination therapy whereby two (or more) compounds are combined and registered/tested as a new compound.
Some experimental results are fairly simple tabular data, which the platform naturally support. It can also handle more complex data types, like in vivo animal-level data with dosing groups and other types of metadata 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.
Controlled vocabularies enable platform-wide controlled terms and their accepted values. The vocabularies are a prerequisite for adding controlled assay metadata to the assay model and are essential for following FAIR principles.
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 Pharmagrit42 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 ITMPGrit42 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 ManagementBased 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-PathAs 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 PharmaWe 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 PharmaFor 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