Wren possesses a novel network kinetics drug discovery platform that precisely quantifies the effects of small molecules on the protein misfolding and aggregation pathway that causes neurodegenerative diseases.
Wren's approach to synucleinopathies is focused on identifying novel small molecules that selectively control the aggregation process of α-synuclein, which is associated with the onset and progression of these diseases.
The collaboration will use Wren's network kinetics drug discovery platform, alongside Eisai's extensive experience in drug discovery for neurodegenerative disorders, to accelerate the development of clinical candidates.
Wren's proprietary network kinetics drug discovery platform enables an entirely new approach to drug discovery, designed specifically to address the unique challenges associated with protein misfolding diseases.
The kinetics-based approach solves for the distinct molecular reaction network that underlies each misfolding disease and produces a fully predictive, quantitative map of the network and its dynamics.
The platform identifies the optimum intervention points in the network to reduce the populations of toxic misfolded and aggregated species, and subsequently makes it possible to identify and optimise molecules with the desired kinetic inhibitory activity.
Synucleinopathies are neurodegenerative diseases characterised by the aberrant misfolding and aggregation of α-synuclein in neurons and glial cells.
Synucleinopathies include Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy.
Eisai Co., Ltd. is a global research and development-based pharmaceutical company headquartered in Japan.
Wren is a spin-off company from the University of Cambridge and Lund University (Sweden), focused on drug discovery and development for protein misfolding diseases.
Wren is advancing an entirely novel approach to address this class of diseases, based on more than a decade of research from its scientific founders focused on the chemical kinetics of the protein misfolding process.
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