Technology
QMD. The company's drug discovery platform, Quantum Molecular Design ("QMD"), deploys an integrated combination of Artificial Intelligence, advanced quantum chemistry, and cloud computing to rapidly generate high quality drug-like hits and leads for a wide range of drug targets, including demonstrated success on targets previously considered to be "undruggable", at low cost. The Artificial Intelligence methods used include augmented intelligence, heuristic search, expert systems and machine learning to reduce computational cost and reduce toxic side effects. The company has achieved biological activity and promising preclinical data on 100% of the drug targets it has tested so far, including allosteric targets, protein-protein interaction disruption, nuclear receptors, and drug candidates designed for selectivity.
Quantum Computing. In early 2020, Cloud Pharmaceuticals completed a collaboration with Fujitsu where it developed substantial new intellectual property surrounding how to discover new drugs rapidly using a variation of its QMD technology running on a quantum computing emulator. The collaboration lead to a body of original IPO that Cloud uniquely owns for using quantum computing to design new drugs in a matter of minutes. Cloud is now in the process of transferring this IP to a spinout venture called PolarisQB, a new company whose mission is to speed up molecular design. Cloud expects to launch 10 new drug discovery and development programs using this method.
Polypharmacy Drug Design. Cloud Pharmaceuticals has also developed a new method to use AI and complex systems simulation to design "polypharmacy" therapeutics based on modulating biological circuits rather than inhibiting proteins. Cloud believes this new method will rival targeted therapeutics as a dominant new way to design, develop and deliver therapies for disease. Polypharmacy refers to bundling several drugs, old and new, into a time stages delivery that has the effect of controlling network pathways. Cloud expects this new development to remain a major research project for the next 2-3 years under a new R&D staff who will operate separately from the drug development operation of Cloud.
Collaborative Hit Database for the Druggable Genome. In partnership with NC State University and several other biotech research organizations, Cloud is participating in a project to build and offer a database of a large number of novel hits to the entire druggable genome as an open source research project for pre-competitive collaboration that will enable the industry to skip many early time consuming stages of discovery for inhibiting, drugging or modulating biological proteins and pathways. the first release of this collaborative effort is expected by the end of the year.
AI at Every Stage of Drug Development. Cloud is partnering with multiple R&D organizations to leverage data and AI at every stage of the drug development process, from preclinical, to pipeline management, to clinical stage development. Our partners include, but are not limited to NC State University, Mercury Data Science and Nashville Biosciences.
PREVIOUS PUBLICATIONS:
“Leveraging cloud computing for In-Silico drug design”
Keinan, S.; Hatcher-Frush, E.; and Shipman, W. J.; IEEE Trans. Comp. Sci. Eng. 10 July 2018
https://ieeexplore.ieee.org/abstract/document/8409367/
"An Effective Way to Apply AI to the Design of New Drug Lead Compounds"
Keinan, S.; Shipman, W. J.; and Addison, E.; Pharma IQ Clin. Disc. & Dev. (2019) June 11.
https://www.pharma-iq.com/pre-clinical-discovery-and-development/articles/an-effective-way-to-apply-ai-to-the-design-of-new-drug-lead-compounds
Please also see the Publications page for a longer list.
Quantum Computing. In early 2020, Cloud Pharmaceuticals completed a collaboration with Fujitsu where it developed substantial new intellectual property surrounding how to discover new drugs rapidly using a variation of its QMD technology running on a quantum computing emulator. The collaboration lead to a body of original IPO that Cloud uniquely owns for using quantum computing to design new drugs in a matter of minutes. Cloud is now in the process of transferring this IP to a spinout venture called PolarisQB, a new company whose mission is to speed up molecular design. Cloud expects to launch 10 new drug discovery and development programs using this method.
Polypharmacy Drug Design. Cloud Pharmaceuticals has also developed a new method to use AI and complex systems simulation to design "polypharmacy" therapeutics based on modulating biological circuits rather than inhibiting proteins. Cloud believes this new method will rival targeted therapeutics as a dominant new way to design, develop and deliver therapies for disease. Polypharmacy refers to bundling several drugs, old and new, into a time stages delivery that has the effect of controlling network pathways. Cloud expects this new development to remain a major research project for the next 2-3 years under a new R&D staff who will operate separately from the drug development operation of Cloud.
Collaborative Hit Database for the Druggable Genome. In partnership with NC State University and several other biotech research organizations, Cloud is participating in a project to build and offer a database of a large number of novel hits to the entire druggable genome as an open source research project for pre-competitive collaboration that will enable the industry to skip many early time consuming stages of discovery for inhibiting, drugging or modulating biological proteins and pathways. the first release of this collaborative effort is expected by the end of the year.
AI at Every Stage of Drug Development. Cloud is partnering with multiple R&D organizations to leverage data and AI at every stage of the drug development process, from preclinical, to pipeline management, to clinical stage development. Our partners include, but are not limited to NC State University, Mercury Data Science and Nashville Biosciences.
PREVIOUS PUBLICATIONS:
“Leveraging cloud computing for In-Silico drug design”
Keinan, S.; Hatcher-Frush, E.; and Shipman, W. J.; IEEE Trans. Comp. Sci. Eng. 10 July 2018
https://ieeexplore.ieee.org/abstract/document/8409367/
"An Effective Way to Apply AI to the Design of New Drug Lead Compounds"
Keinan, S.; Shipman, W. J.; and Addison, E.; Pharma IQ Clin. Disc. & Dev. (2019) June 11.
https://www.pharma-iq.com/pre-clinical-discovery-and-development/articles/an-effective-way-to-apply-ai-to-the-design-of-new-drug-lead-compounds
Please also see the Publications page for a longer list.