No matter if your data are produced in-house or ex-house by CROs you need to (should) store them in a structured and accesable manner so they can be analysed, retrieved and reused by others as well as be available for future ML and AI algorithms.
In our grit42 platform 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 grit42 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.
If your software is far from supporting your daily workflows or suffers from a poor interface, then it’s rarely something you look forward to work with. That’s why we have built software that fits to what you’re doing and looks pleasing to the eye, rather than attempting to fit your routines to what the – often outdated – software requires.
Ultimately one of our core philosophies is to create software that supports you in the most ideal way, while being as easy to work with as possible.
If you’d like to test that, please get in touch so you can take it for a spin yourself!
We do scientific data management the simple way. The platform is a no code, ready to use product delivered in a package ready for easy deployment inhouse or hosted by us
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 pyhton, R or similar.
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 dta 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.
We do all the boring stuff under the hood, like managing, computing, and analyzing your data, so you can focus on the important stuff: Everything that leads to insights.
If you look at the pyramid below, we make it easy for you to focus on the top two levels, where you get the results and insights that drive your research. Leave the tedious tasks to us.
We enable new insights and discoveries by managing your data in a way that allows you to mine data and look for patterns across different datasets.
