J Mark Treherne

Talisman Therapeutics Ltd, UK

Title: Pluripotent stem cells as models of neurodegenerative diseases to support drug discovery programmes

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Biography

Dr Mark Treherne is the Chairman and a founder of Talisman Therapeutics. He has over 25 years’ experience in the discovery of novel treatments for diseases of the central and peripheral nervous systems, including Parkinson’s and Alzheimer’s diseases. He formerly worked with Pfizer where he was responsible for research into neurodegenerative diseases, including using stem-cell derived lines for screening compounds. Mark has worked with many early-stage biotechnology companies, including Cambridge Drug Discovery, Xention, Ampika, Population Genetics Technologies, Domain Therapeutics, Cyclofluidic and NeuroSolutions. He is an author of over 90 articles published in the scientific and trade press. Mark obtained his PhD in receptor neuropharmacology from Cambridge University.

Abstract

There are unmet medical needs that would benefit from advanced in vitro approaches, such as with the discovery of new treatments for Alzheimer’s disease. Historically, drug discovery has been overly dependent on animal models that can be poorly predictive of human pathology, including when engineered in transgenic mice. Costly late-stage drug failures are common. Increasingly, advanced human-specific cellular models are filling this void, such as those that recapitulate both amyloid and tau pathologies. These in vitro translational models are enabling pivotal decisions to be made earlier in drug discovery and can be established in conventional tissue culture laboratories. For example, induced pluripotent stem cells (iPSC) sourced from patient donors to support drug discovery programmes. Human stem cell-derived neuronal and glial (astrocytes, microglia) models of several genetic forms of dementia have been developed. These models include monogenic forms of Alzheimer’s disease (PSEN1, APP), frontotemporal dementia (MAPT mutations), Trisomy 21/Down syndrome, Nasu-Hakola disease (TREM2 mutations). Such models in 2D, 3D and co-culture models can be optimised for both high-content and high-throughput analysis. Case studies that demonstrate the utility of such models in enabling drug discovery will be presented.