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EVQLV, Manhattan BioSolutions Announce UB CAT Grant Award

Jun 29, 2021 | Press Releases | 0 comments

University at Buffalo Center for Advanced Technology in Big Data and Health Sciences

New York City, New York Jun 29, 2021 (  – EVQLV, an innovator in developing artificial intelligence to accelerate how biologic therapies reach patients, and Manhattan BioSolutions, an emerging biotechnology company developing immunoregulatory therapies for the treatment of metastatic cancers, have been awarded a grant from the University at Buffalo Center for Advanced Technology in Big Data and Health Sciences (UB CAT) program. The UB CAT grant will enable the pharmacological assessment of novel computationally-designed biologic agents for the treatment of immune-mediated and viral diseases. This collaborative research will be conducted in partnership with the laboratory of Dr. Dhaval Shah, an Associate Professor at the Department of Pharmaceutical Sciences, University at Buffalo, whose cutting-edge research in protein therapeutics and pharmacokinetic-pharmacodynamic modeling has significantly impacted the drug development field around the globe.

The proposed project is based on the novel evolution-based, artificial intelligence (AI)-enabled antibody discovery platform developed by EVQLV. The in silico designed fully human antibody candidates against preselected targets will be tested experimentally for pharmacological effects in preclinical models to further demonstrate the utility of the EVQLV’s AI engine to deep-mine vast amounts of massive sequencing and structural databases to guide therapeutic antibody discovery and development.

Andrew Satz, Chief Executive Officer of EVQLV, commented: “Through our collaboration, we will continue to demonstrate how AI and machine learning can guide therapeutic antibody discovery and development. We strongly believe that generating and testing biologics, in the computer, prior to proceeding into biologic systems can accelerate how medicines reach patients in need”.

Dr. Boris Shor, Chief Executive Officer, Manhattan BioSolutions, commented, “We are pleased to collaborate with EVQLV and Dr. Shah’s laboratory at the University at Buffalo. Our efforts will augment Manhattan BioSolutions’ current discovery plans aimed at the development of unique monoclonal antibodies targeting immunoregulatory receptors implicated in both cancer and inflammation”.

Dr. Dhaval Shah commented: “The primary benefit of this collaboration is the strong synergy between our teams based on the unique expertise in computational science, translational pharmacology, and pharmacokinetic modeling of novel biologics. Together, we will be in a strong position to fully validate the computationally designed antibodies in preclinical experiments.”


EVQLV develops artificial intelligence to accelerate the speed at which biological therapies reach patients. Comprised of experts in machine learning, molecular biology, computational biology, pharmacology, software engineering, antibody design, cloud computing, and preclinical/clinical development, EVQLV is on a mission to transform how healing reaches those in need. For further information, visit

About Manhattan BioSolutions

Manhattan BioSolutions, Inc is a privately held biotechnology company focused on the development of immunotherapies that target microbial recognition and inflammatory signaling pathways for the treatment of metastatic cancers and immune-mediated diseases. Manhattan BioSolutions leverages two therapeutic modalities for drug discovery: synthetic microbes — genetically engineered living drugs and monoclonal antibodies against innate immune sensors that recognize pathogens or endogenous “danger signals” released as a result of tissue injury or inflammation. 

About UB CAT

The University at Buffalo Center for Advanced Technology in Big Data and Health Sciences (UB CAT) is a project cost-sharing grant program funded by NYSTAR, Empire State Development’s Division of Science, Technology, and Innovation to drive the growth of life and health science businesses in New York State.


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