High Content Screening as a Window to Understanding and Modulating Ageing Pathologies for Drug Discovery
Introduction
People are living longer but in poorer health. It is well reported that lifestyle choices such as regular exercise, maintaining a healthy weight, eating a healthy diet, calorific deficit, taking alcohol moderately and not smoking can increase the probability of staying healthy for longer; extending healthspan as well as lifespan. This type of lifestyle is not always achievable and other factors such as disease, injury, genetic pre-disposition and medication can accelerate pathologies that underly ageing; leading to health issues, frailty and a collection of morbidities in later life. Understanding the pathologies that underlie the ageing process and the possibility to intervene early with new or repurposed medications could reduce the financial burden of healthcare for the global economy and extend the time we can live productively and in good health. Although the nine hallmarks of ageing, plus the additional influence of the microbiome are now widely discussed, fully understanding these underlying biological processes, plus defining areas we can safely intervene with chronic therapies is key.
High content screening (HCS) is an important tool and a powerful analytical technology, yielding biologically relevant, statistically robust data that is amenable to high throughput. It allows novel types of phenotypic and disease relevant assays to be screened in a multiplexed manner. When coupled with artificial intelligence (AI) and omics platforms with disease relevant tissues, it can prove a powerful tool in broadening our understanding of and seeking therapeutic interventions for healthy ageing. Here we will show case study examples of where HCS can be applied to explore a selection of pathologies associated with ageing. These examples form a part of our ‘toolbox for ageing’, in addition to other technology platforms and assays we deploy in this field.
Contributors:
Olszewski, M.B., Gostyńska, N., Leśniak, K., Lempart, Z. & Winn, K
Contact
kirsty.winn@selvita.com
maciej.olszewski@selvita.com