DrugBank, an Edmonton-based University of Alberta spinoff, created a vast database related to pharmaceutical drugs. In what was an ambitious academic project, the startup began finding customers for the data in this database. The venture recently won $125,000 as a top prize in an investment summit and now seeks additional capital infusions to grow. They are on a mission to organize the world’s pharmaceutical knowledge to enable new drug discoveries and medicine.
An Academic Project
What started as an academic endeavor at the University of Alberta lab of Dr. David Wishart, grew in scope and scale and became commercialized in 2015 when the project intellectual property was licensed to OMx Personal Health Analytics Inc. which was founded by Wishart, Craig Knox, and Michael Wilson. Recently, the firm took part in an investment summit and secured the $150,00 top prize. This money will be directed to the company’s sales and product team.
According to its website, DrugBank (version 5.1.5) now has 13,511 drug entries, including 2,629 approved small molecule drugs, 1,369 approved biologics (proteins, peptides, vaccines, and allergenics), 131 nutraceuticals, and over 63,56 experimental drugs. Moreover, the team has included 5,197 non-redundant protein (i.e., drug target/enzyme/transporter/carrier) sequences linked to the drug entries. Each entry contains over 200 data fields with half of the information devoted to drug/chemical data and other half devoted to drug target or protein data.
The first version of DrugBank was built way back in 2006. It is a comprehensive, freely accessible, online database containing information on drugs and drug targets. As both a bioinformatics and cheminformatics resource, DrugBank combines detailed drug (chemical, pharmacological, and pharmaceutical) data with comprehensive drug target (sequence, structure, and pathway) information.
Machine Learning Ready
DrugBank is accessed as a freely available resource. However, the data can be leveraged for commercial purposes but requires a license. Additionally, the data can be licensed for leveraging machine learning algorithms—for example, the DrugBank data can be employed to train machine learning models, enhance data pool, or even build predictive models.
Example clients include Molecular Health, which offers software solutions for evidence-based decision support and smarted drug development. They have integrated DrugBank data seamlessly into in-house products to enhance outcomes for data-driven decision making. Healx integrates DrugBank into their internal databases, empowering them to use a wide range of data to train their drug repurposing algorithms. Healx reports that it can lower the time and cost of their R&D and get repurposed drugs to market faster.
DrugBank is now seeking additional capital to expand more aggressively.
Call to Action: Interested in possibly investing in one of the world’s most robust drug databases? Contact DrugBank.