Cognitive Dataworks

Cognitive Dataworks creates data analysis solutions for drug discovery by leveraging artificial intelligence and machine learning methods. With over 20 years of biotech experience and expertise in bioinformatics and cheminformatics, we provide our clients with a range of consulting services.  

Solutions

The scientific informatics landscape changes rapidly as new data and methods become available seemingly everyday.  We make an effort to provide our clients with the best of these new solutions blended with traditional informatics practices.  Some of our services are listed below:

AI Assisted Drug Discovery
Predictive models coupled with novel chemistry generation are changing the landscape for small molecule programs by shortening lead generation time and providing pre-screening of desired properties.  We have developed full solutions in this area which can be applied to your target/program.
Analysis Pipelines
Whether it is chemical screening or genomics data we can build a custom pipeline that fits your team’s needs merging public or collaborator data with your own proprietary data.  We can handle data procurement, cloud setup, method deployment and build or configure custom analyses.
HTS to Lead Optimization
Let us do the cheminformatics and let your medicinal chemists focus on the chemistry solutions.  There is a lot of data management involved in small molecule program as well as a need to understand when to apply a given cheminformatics method, we can help you make the right choice so you can focus on the big picture.

About

Founded by Dennis Moccia in 2011, Cognitive Dataworks has supported over 30 Boston area Biotech companies from startups to publicly traded corporations.  We pride ourselves in having the capacity to work directly with scientists or advise at the leadership level.  Our passion is the intersection of science and technology so if you have a challenging project please reach out below or through LinkedIn.

Blog

Adoption of AI/ML into a Small Molecule Discovery

Last week in the Journal of Chemical Information and Modeling (JCIM) a reflection was published on the adoption of AI by medicinal chemists. The viewpoint, written by Alex Zhavoronkov of Insilico Medicine, asked the question “[how can we] advance artificial intelligence for drug discovery?” The article considers the cost and challenges of AI adoption and ultimately proposes a competition between human medicinal chemistry experts and AI generated approaches that will assess each stage of the drug discovery pipeline.

Building a GAN Compound Explorer in Plotly Dash

Last week I found myself with some downtime in between projects and took the opportunity to explore Plotly Dash. Over the past few years I have used Bokeh to build stand-alone analysis applications, but had seen some cool stuff built on top of Dash. Initially I had just planned to take Dash for a test run, but I quickly found myself digging into the capabilities of Dash which centers around it’s powerful DataTable Component. After just a couple of days I had built an application which takes a list of SMILES as input and provides the user with a dashboard to explore properties, clustering, and the raw data.

Contact

We would love the opportunity to work with you or simply have a chat.  Please fill out the contact form below or access us through LinkedIn