On September 2, 2022 The National Institute of General Medical Sciences (NIGMS) reported that has awarded $1,729,532.72 to Collaborations Pharmaceuticals, Inc. (CPI) and the University of Arizona to generate in vitro data and develop MegaTransÒ machine learning software for drug discovery (Press release, Collaborations Pharmaceuticals, SEP 2, 2022, View Source [SID1234618941]).
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"The objective of MegaTrans is to develop a new computational system and tools for integrating human transporter data into drug discovery pipelines, as well as enabling its analysis and visualization. It will also assist with developing computational tools for quantitatively modeling drug-drug interactions of xenobiotics. We will generate data for transporters which currently have a paucity of data in the public domain, use validated machine learning algorithms, access the latest curated datasets and develop a user-intuitive interface and visualization system to enable predictions. MegaTrans will be developed as commercial quality software and then commercialized by licensing to companies, as well as used in fee-for-service consulting projects. In Phase I of this project, we have collaborated with Dr. Steven Wright and Dr. Nathan Cherrington at the University of Arizona to generate numerous models for important human drug transporters. CPI have also developed the prototype for MegaTransÒ, curating numerous transporter datasets then generating and tested the resulting models. This Phase II award will allow us to perform additional in vitro testing (at the University of Arizona) to expand our models and develop MegaTransÒ further as a commercial product available for licensing by pharmaceutical and other groups so they can benefit from our expertise." said Sean Ekins, CEO, CPI.
Drs. Stephen Wright and Nathan Cherrington of the University of Arizona are long-term collaborators with Collaborations Pharmaceuticals, Inc. This joint effort builds upon extensive experience and extends the mechanistic understanding of drug disposition to the whole patient by accurately predicting functional disposition. This collaboration is now poised at the forefront of understanding xenobiotic disposition and predicting the mechanistic features that determine human exposure and response to drugs.
We are not aware of any other company pursuing such an approach to both generate new high value datasets or models, performing testing of their own models and creating a wide array of transporter models. MegaTrans can be applied in these various companies or organizations to aid in decision making or in regulatory submissions.