Skip to main content

SciBite - Open Intelligence on Pharmaceutical Discovery & Development



Lee Harland, is a visitor in the ChEMBL group here at EMBL-EBI, and he is collaborating with us on semantic web data integration, text-mining, target ontologies and so forth. I asked him to write a small piece for the ChEMBL-og on one of his personal projects - SciBites, and here is what he wrote......


"SciBite is a new biomedical alerting service tailored to pharmaceutically relevant questions and focused on targets, diseases and drugs. The premise is simple, right now if you're a scientist interested in say, Asthma, how can you stay on top of all the lastest developments? You can of course, set up pubmed searches, patent searches, google news searches (making sure you have remembered every possible synonym as these tools won't do that for you). What you'll get back is a stream of articles. Some relevant, many not, and you'll have to read them to actually find out. We thought there had to be a better way.. What we really wanted was a kind of Twitter for "things", where the drugs, disease and targets could each tweet relevant news, in an easily consumable (and discoverable) way. So we built SciBite.

SciBite works by continually scanning 1000s of sources including literature, patents, news feeds, blogs, databases and more. It looks at every new article and automatically tags the targets, diseases, drugs, companies and 'contexts' (such as "biomaker study", "regulatory approval", "animal model" etc), that it finds. Users can then go to the website and view information by topic, not by source. The lists can be filtered based on source or other criteria such as regulatory approval or biomarkers. Everything is available as an RSS feed so users can stay on top of latest news. Information is presented in a very visual way, making it really easy to scan new articles and identify the key topics. We also have relevancy filters to remove spurious and irrelevant news (although this will never be perfect!). Finally, our "related topics" function allows you to quickly find the targets, diseases or drugs being co-mentioned with the thing you're interested in, which is an incredibly powerful way to spot new and interesting connections.

There are a number of major content companies doing this sort of thing, and as a small (tiny) company, we cannot hope to match their levels of curation and resources. However, we believe that this sort of information should be available to everyone and so we hope that by using technology we can provide something that comes close to what the major players offer. We decided early on that as we were using a lot of public data (including ChEMBL), the site itself should be free and support these efforts. We're also making all our data and APIs freely available to any non-profit organisation expressing an interest. 

We've seen a great growth in user numbers since our very low-key launch at the start of February. Over 2000 people have used the site, and we've done hardly any advertising... Its daunting to see that many so soon, but its a great feeling to know people are finding it useful! What's there now is really just the start. The aim was to build a platform that connected news to things, which we've done. The next stages are to do much more with the data. This is one of the things I'll be exploring as part of my Visitorship with the ChEMBL group, we're looking at some interesting company-centric profiling, tracking whats going on with each organisations drugs. There's a whole lot more planned for 2012 too!

Anyone interested can use the system for free now, at http://scibite.com. I tweet as @SciBitely and our blog is at http://about.scibite.com."

Wow! Look at what is there.

Comments

Popular posts from this blog

ChEMBL 34 is out!

We are delighted to announce the release of ChEMBL 34, which includes a full update to drug and clinical candidate drug data. This version of the database, prepared on 28/03/2024 contains:         2,431,025 compounds (of which 2,409,270 have mol files)         3,106,257 compound records (non-unique compounds)         20,772,701 activities         1,644,390 assays         15,598 targets         89,892 documents Data can be downloaded from the ChEMBL FTP site:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/ Please see ChEMBL_34 release notes for full details of all changes in this release:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/chembl_34_release_notes.txt New Data Sources European Medicines Agency (src_id = 66): European Medicines Agency's data correspond to EMA drugs prior to 20 January 2023 (excluding ...

SureChEMBL gets a facelift

    Dear SureChEMBL users, Over the past year, we’ve introduced several updates to the SureChEMBL platform, focusing on improving functionality while maintaining a clean and intuitive design. Even small changes can have a big impact on your experience, and our goal remains the same: to provide high-quality patent annotation with a simple, effective way to find the data you need. What’s Changed? After careful consideration, we’ve redesigned the landing page to make your navigation smoother and more intuitive. From top to bottom: - Announcements Section: Stay up to date with the latest news and updates directly from this blog. Never miss any update! - Enhanced Search Bar: The main search bar is still your go-to for text searches, still with three pre-filter radio buttons to quickly narrow your results without hassle. - Improved Query Assistant: Our query assistant has been redesigned and upgraded to help you craft more precise queries. It now includes five operator options: E...

Improvements in SureChEMBL's chemistry search and adoption of RDKit

    Dear SureChEMBL users, If you frequently rely on our "chemistry search" feature, today brings great news! We’ve recently implemented a major update that makes your search experience faster than ever. What's New? Last week, we upgraded our structure search engine by aligning it with the core code base used in ChEMBL . This update allows SureChEMBL to leverage our FPSim2 Python package , returning results in approximately one second. The similarity search relies on 256-bit RDKit -calculated ECFP4 fingerprints, and a single instance requires approximately 1 GB of RAM to run. SureChEMBL’s FPSim2 file is not currently available for download, but we are considering generating it periodicaly and have created it once for you to try in Google Colab ! For substructure searches, we now also use an RDKit -based solution via SubstructLibrary , which returns results several times faster than our previous implementation. Additionally, structure search results are now sorted by...

Here's a nice Christmas gift - ChEMBL 35 is out!

Use your well-deserved Christmas holidays to spend time with your loved ones and explore the new release of ChEMBL 35!            This fresh release comes with a wealth of new data sets and some new data sources as well. Examples include a total of 14 datasets deposited by by the ASAP ( AI-driven Structure-enabled Antiviral Platform) project, a new NTD data se t by Aberystwyth University on anti-schistosome activity, nine new chemical probe data sets, and seven new data sets for the Chemogenomic library of the EUbOPEN project. We also inlcuded a few new fields that do impr ove the provenance and FAIRness of the data we host in ChEMBL:  1) A CONTACT field has been added to the DOCs table which should contain a contact profile of someone willing to be contacted about details of the dataset (ideally an ORCID ID; up to 3 contacts can be provided). 2) In an effort to provide more detailed information about the source of a deposited dat...

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEM...