Today, I’m thrilled to share the public launch of AXL, a new venture studio building the next generation of AI-powered companies, right here in Canada.
Scientists in drug discovery work with a lot of data. They're expected to translate this complexity into clear high-impact decisions that can shape entire drug programs.
BioBox simplifies this with our Graph Reasoning Models!
Learn more here 👇
Pioneering startup in drug discovery knowledge management, @BioBoxAnalytics has won the inaugural Innovation Incubator competition at the AI Driven Drug Discovery Summit in Boston: https://t.co/2V1KwTWbHW… #AI#Drugdiscovery@UofT@UofTStartup
Long non-coding RNAs will be the next gold mine for novel drug targets.
In the past two weeks, we saw two major partnerships announced, specifically hunting for lncRNA targets:
@HAYA_lncRNA and @EliLillyandCo - $1B+
NextRNA and @Bayer - $550M+
The hardest part is deciding which lncRNA to target.
LncRNAs have cell-type, tissue-type, and disease specific expression patterns. They're involved in complex and often pleiotropic biological processes. Epigenetics is notoriously hard. You have to integrate bioinformatic data from all kinds of experiments (ChIP, ChIRP, RIP, eCLIP, ATAC, etc...) to understand the epigenetic landscape and test your hypotheses.
"What does my lncRNA bind with?"
and
"Where does the lncRNA-protein complex bind to on the genome?"
and
"Are they promoters? Enhancers? Is the region even accessible in my cell type? Tissue? Disease?"
and
"Do those genes show expression changes when I knock down my lncRNA?"
These types of multi-hop questions are where knowledge graphs shine. Traversing these paths and finding patterns become trivial once you've modeled and loaded the data into a knowledge graph on the @BioBoxAnalytics platform.
Interested in learning more? DM me and let's chat.
#ncRNA #epigenetics #KnowledgeGraph
"...the true value of a knowledge graph lies not in its complexity but in its utility."
Check out our latest blog post by @biobox_chris where we share guidance on how to do useful things with multi-omic knowledge graphs.
#KnowledgeGraph#multiomics
https://t.co/e10y5SOYoP
Knowledge Infrastructure for the Modern Biopharma.
Check out our latest post where we highlight how teams are using the BioBox platform to solve complex drug discovery challenges.
https://t.co/8plTzIlNTm
🚀 v5.5.0 is out with some highly requested updates!
Object Views and Search. Find any object in your data graph quickly with smart lookups.
Remove unused data packages from your graph.
Read more about it here👇
https://t.co/N174JMVO1w
🚀 BioBox v5.3.0 just landed!
Data packages now have their data dependencies mapped, ensuring your graph is semantically sound.
Exporting network graphs as .png and extracting nodes and edges into a .csv file
Read the release notes here: https://t.co/M91Vcnb8Qd
Check out our latest blog post by Lauren Phillips (@LaurenP23_) breaking down what the new FDA guidelines could mean for platform therapeutic companies 👇
https://t.co/1kmEU58WLs
Platform therapeutic companies that can zero-in on high quality causal drug targets will win in the next decade.
Lauren Phillips(@LaurenP23_) discusses the impact in our latest blog post 👇
Bottom line is that drug discovery is a business activity, which disincentivizes therapeutic development in rare diseases with smaller market sizes. New FDA guidelines look to shake things up, providing a path for platform companies to massively fast track therapeutic development.
https://t.co/xBQgYXqrNs
🚀Excited to share our latest update to the @BioBoxAnalytics platform. Introducing the Graph Explorer - a seamless way to build a GPS for disease biology in drug discovery.
Interactively explore a canvas of highly connected multi-modal biological data, all in one place.
To learn more, you can read about it here:
https://t.co/c6XD2kYdlX
🚀Excited to share our latest update to the @BioBoxAnalytics platform. Introducing the Graph Explorer - a seamless way to build a GPS for disease biology in drug discovery.
Interactively explore a canvas of highly connected multi-modal biological data, all in one place.
To learn more, you can read about it here:
https://t.co/c6XD2kYdlX
Having data is not the same as having knowledge.
Big pharma teams are using Knowledge Graphs to accelerate drug discovery and get assets to market faster.
Here's how they do it:
https://t.co/7sayaP30eu
🚀Exciting news to share!
Our latest update unleashes the BioBox Knowledge Engine. Built upon 80k+ datasets and 4.6 billion observations, the engine is the most powerful way for scientists to identify and validate targets faster.
Contact us to learn more!
This week on MENT TO BE, we are joined by Lauren Phillips, CPO of @BioBoxAnalytics In this clip, Lauren gives advice to women interested in tech startups.
Stream the full podcast episode here: https://t.co/91vAH9nWLU
New episode every Tuesday! #mentorship#careers