Collaborations Pharmaceuticals, Inc. Announces Major Updates To 2022 Pipeline
Collaborations Pharmaceuticals, Inc. (CPI) announced major updates to their drug discovery research and development pipeline aided by machine learning software.
RALEIGH, NORTH CAROLINA, USA, May 18, 2022 /EINPresswire.com/ -- “At a time when many small to mid-size pharmaceutical and biotech companies are trimming down their research and development pipelines, we are going in the opposite direction. This also comes at a time when larger companies are looking for assets to bolster their own pipelines. Several recent drug discovery projects at CPI have now been completed and we will be reporting their data in due course in peer reviewed publications said Dr. Sean Ekins, CEO, CPI.” “Notable amongst these are the completion of the Batten disease (enzyme replacement therapy), Chagas Disease, COVID-19 and Acute Flaccid Myelitis preclinical in vivo studies. Most of this late stage preclinical work has been funded via grants from the NIH to CPI or through NIH contracts to third parties. In addition, we have advanced several more projects through the in vitro stages of drug discovery. Most recently we have initiated an early stage NIDA funded project on generating novel non-addictive psychoplastogens in order to develop treatments for opioid abuse disorder.”
“What is apparent is the wide impact machine learning software is having on our pipeline as nearly all the projects have used our Assay Central software. This is also an enabling technology that we actively license to other companies and provide for use on fee-for-service projects. We are also open to partnering with other companies or organizations to advance the treatments in our pipeline for various rare and neglected diseases.” “To date the company has been funded by fee-for service work, grant funding and matching grants from the One North Carolina SBIR/STTR Matching Funds Program. We would be happy to work with larger companies that could benefit from our expertise in building drug discovery pipelines and creating value using machine learning technologies for drug discovery, stated Dr. Ekins”.