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Bench to bedside: From Idea to Impact - Professor Neil Carragher

 
24 Mar 2021

When Professor Neil Carragher moved from industry to academia to establish a drug discovery group at the Cancer Research UK Edinburgh Centre he already had an innovative vision for disrupting the way in which therapeutics are discovered.

He wanted to create a state of the art phenomics engine to open up whole new classes of drug targets. But it would only work if it was integrated with world leading clinical excellence and access to the latest advances in “high-content” screening technologies. The University of Edinburgh provided exactly that. 10 years on with a spinout company established and a back catalogue of industrial collaborations Neil’s vision is becoming a reality and a blueprint for a new paradigm in therapeutic development.

In 2010, inspired by emerging advances in cell based assay technologies, Professor Carragher made the unusual career switch from industry to academia to establish an innovative drug discovery group at the Cancer Research UK Edinburgh Centre within the College of Medicine and Veterinary Medicine, University of Edinburgh. With over 25 years of translational research experience from within the pharmaceutical industry and academia Neil believed the emergence of new technologies provided new opportunities for more evidence-led approaches to drug discovery. The convergence of these technologies made it easier to find novel therapeutic targets, chemical starting points and prioritize candidate drug and drug combination strategies within the context of complex disease biology.

The creation of the Phenomics Drug Discovery platform

To further exploit these new technologies Neil and colleagues at the Cancer Research UK Edinburgh Centre established their Phenomics Drug Discovery platform. Phenomics Drug Discovery (PDD) is the application of the latest advances in genetics, proteomics, imaging and informatics tools to explore target biology and drug mechanism-of-action across complex cell and tissue based models of disease. The platform can operate at scale by integrating automated liquid handling with high content microscopy, the latest image analysis and machine learning pipelines. This enables comprehensive surveys of pharmacological and target classes across multiple disease cell phenotypes.

The development of advanced cell and tissue based models, including patient-derived models of disease coupled with advanced genetic, proteomic and phenotypic analysis is particularly suited to the strengths of the University of Edinburgh College of Medicine and Veterinary Medicine. These strengths, in turn, brilliantly complement those within the pharmaceutical industry and have led to multiple collaboration agreements between the Edinburgh PDD platform and several Pharmaceutical and biotechnology industry partners.

The Host and Tumour Profiling Unit research facility

This approach to understanding patient samples, target biology and drug mechanism-of-action at transcriptomic and post-translational pathway levels with high precision and sensitivity has been so successful it has now spun out as its own independent research facility: The Host and Tumour Profiling Unit (HTPU). Following the same integrated approach as the PDD platform, HTPU utilizes the latest advances in mass spectrometry, antibody-based proteomics and NanoString spatial transcriptomics technologies. Indeed, the HTPU facility supports multiple research programs and also conducts contract research for external academic and industry partners.

Other key therapeutic developments

It was therefore a very natural step when the success of PDD as well as demand from industry partners led to the next stage in this journey with two key developments.

The first development was in 2015 when Carragher and colleagues opened a satellite laboratory in the Queen’s Medical Research Institute at the Bioquarter campus (Edinburgh Phenotypic Assay Centre). This enabled the PDD platform to expand drug discovery and translation research to other disease areas including inflammatory and neurodegenerative disorders, reproductive health and regenerative medicine.

The second was the addition of world leading expert in regenerative neurology Professor Siddharthan Chandran to the collaboration. Professor Chandran brought exceptional clinical insight and human induced pluripotent stem cell models together with the already successful phenomics platform, creating the blueprint for the future. This dynamic partnership created PhenoTherapeutics Ltd to focus on identifying new treatments for demyelinating disorders such as Multiple Sclerosis and secured a £5million series A investment.

The Impact the PDD platform has already had is massive. It has identified several lead compounds and new therapeutic target opportunities which have been subsequently validated in relevant human cell and in vivo models of disease. It has supported major translational research programs in oesophageal cancer, brain cancer, multiple sclerosis, motor neuron disease and regenerative medicine securing over £17.5million in research funding. The continued investment in the University of Edinburgh PDD platform facilitates both early stage drug discovery and the selection and prioritization of late stage drug candidates, drug combination strategies and biomarkers to guide optimal clinical trial designs.

Professor Carragher’s idea became a reality and in precisely the same way the University of Edinburgh continues to support drug discovery from bench to bedside.

Related links

  • Discover more about the University of Edinburgh’s therapeutic discovery capability at Bench to Bedside webpage.
  • If you would like to read more, the work of the Carragher group in leading the development of high content imaging and artificial intelligence/machine learning approaches in cancer drug discovery was recently featured in a Nature news article: Deep learning takes on tumours.
  • The Host and Tumour Profiling Unit (HTPU) which utilizes the latest advances in mass spectrometry, antibody-based proteomics and NanoString spatial transcriptomics technologies.