IRICoR, a pan-Canadian drug discovery and research commercialisation centre, Université de Montréal (UdeM), the Institute for Research in Immunology and Cancer (IRIC) of the Université de Montréal, and Valence Discovery, an emerging leader in AI-enabled drug design, have announced a collaboration focused on the discovery of novel drug candidates for the treatment of levodopa-induced dyskinesia in Parkinson’s disease.
Parkinson’s disease is a progressive neurodegenerative disease with the prevalence of one in 100 people over the age of 60, or around five million people worldwide. Of these patients, almost all receive levodopa (also known as L-Dopa), a dopamine precursor that enables patients to reinitiate normal movement.
Although this treatment offers relief of the major motor symptoms, in a majority of patients, prolonged levodopa use leads to abnormal involuntary movements called levodopa-induced dyskinesia, which can be highly debilitating. Levodopa-induced dyskinesia occurs with an average latency of around six years and affects 95% of all patients within 15 years of chronic L-Dopa treatment. Current treatments for this condition are not universally effective, have only transient efficacy, and are associated with side effects including fainting, dizziness, and hallucinations.
The collaboration builds on research from the team of Dr Daniel Levesque, Professor and Associate Dean for Research and Graduate Studies of the Faculty of Pharmacy at UdeM, and focuses on the design of highly selective modulators of the Nur77/RXR nuclear receptor complex, a promising new pharmacological target for movement disorders. Through co-funding from IRICoR and the Partenariat-UdeM program and with oversight of the project from IRICoR, scientists in the Drug Discovery Unit at IRIC will rapidly advance selected hits through lead optimisation. The research team will leverage Valence’s machine learning platform for few-shot learning, generative chemistry, and multiparameter optimisation to address critical challenges in lead optimisation through the design of novel, highly selective drug candidates against the Nur77/RXR target, presenting a new pharmacological approach to managing the limitations of current treatments.
“We are extremely pleased to have Valence’s support on this important drug discovery program, and are confident that our joint efforts will significantly accelerate our path to identifying novel compounds that can treat levodopa-induced dyskinesia, a serious side effect of the most common treatment for Parkinson’s disease,” says Dr. Levesque.
“We’re thrilled to be working with Dr. Levesque and the world-class team at IRIC, who have an extensive track record of collaborating with leading industry partners including BMS, Ipsen, and Merck.” says Daniel Cohen, CEO of Valence Discovery. “This collaboration is an important example of how we’re bringing modern machine learning methods, custom-built for drug discovery, to innovative R&D organisations of all shapes and sizes.”
“This collaboration is a testament to IRICoR’s commitment to investing in high-potential projects for indications with high unmet medical need, while staying at the cutting edge of drug discovery by combining an impressive array of homegrown technologies at the intersection of machine learning, chemistry, and biology,” says Dr. Steven Klein, Vice President of Business Development at IRICoR.