Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Oxford University has recently led a successful bid to establish a €52M international consortium to develop induced pluripotent stem (iPS) cell lines for drug discovery and safety assessment.

Dopamine neurons (in green) grown using stem cell technology
Dopamine neurons (in green) grown using stem cell technology

The StemBANCC bid, led by Dr Zam Cader was truly a team effort and involved researchers from across Oxford including the Nuffield Department of Clinical Neurosciences, Dunn School of Pathology, the MRC Functional Genetics Unit, the Departments of Chemistry, Psychiatry, Pharmacology, and Physiology Anatomy and Genetics, the Oxford Centre for Diabetes, Endocrinology and Metabolism and the Centre for Health, Law and Emerging Technologies.

The consortium also includes academic researchers and big pharma partners from across the UK and 10 other European countries. The project will build on Oxfords established strength in iPS cell technology to deliver a robust platform for research and to support drug discovery in the areas of Alzheimer’s, Parkinson’s, Autism, Schizophrenia, Bipolar, Migraine, Pain and Diabetes.

Similar stories

Research shows how the brain reorganises old memories when new ones are made

MRC BNDU Research

Researchers have discovered that the arrangement of existing memories in the brain is altered when we embed new memories

Capturing immune cells that colonise the brain to prevent disease progression in multiple sclerosis

Clinical Neurology Research

Researchers have revealed a disease-causing population of immune cells, which travel to the brain in patients with multiple sclerosis. They demonstrate how to trap these cells in the blood, which means they can be targeted to prevent disease progression.

New machine learning system developed to identify deteriorating patients in hospital

Anaesthetics Research

Researchers have developed a machine learning algorithm that could improve clinicians’ ability to identify hospitalised patients who need intensive care.

Accidental awareness in obstetric surgery under general anaesthesia more frequent than expected

Anaesthetics Research

The largest ever study of awareness during obstetric general anaesthesia shows around 1 in 250 women may be affected, and some may experience long-term psychological harm.