Innovator Awards: people we've funded

Jump to

2018

Professor Geraldine Boylan

University College Cork

Development of a Neonatal Brain Health Index (DELPHI)

Neonatal encephalopathy is the most common cause of brain injury in full-term infants and it is caused by insufficient oxygen and blood supply to the brain during birth. Serious brain injury can cause death or permanent disabilities, such as cerebral palsy, epilepsy or learning difficulties. It is very difficult to gauge the severity of the injury by simple observation, but monitoring the electrical activity of the brain can provide critical information about severity, cause and possible outcomes. Treatment, such as whole body cooling, can improve the outcome if applied in time. 

We aim to develop the first ‘smart’ automated system using machine learning to recognise patterns in electrical brain activity in infants with neonatal encephalopathy to help accurately detect the severity of their injury.

This system will allow babies with severe injuries to be identified early so they can be given appropriate therapies that are tailored to their needs.

Professor Dimitri Kullmann

University College London

Glutamate-gated chloride channel treatment of epilepsy

Pharmacoresistant epilepsy affects approximately 0.3% of the population in developed countries and more than 200,000 people in the UK. Surgery can be used to stop seizures, but it carries risks to normal brain function.

We have developed a targeted gene therapy strategy based on a modified glutamate-gated chloride channel (eGlCl) expressed in excitatory neurons using a viral vector. eGluCl decreases neuronal excitability by opening in response to extrasynaptic glutamate when excitatory neurons fire excessively, without affecting normal brain function. We have demonstrated the efficacy of eGlCl in an acute chemoconvulsant model of evoked focal seizures and in a neocortical model of established epilepsy. It had no detectable behavioural side-effects. 

We will adapt this study for clinical translation by: redesigning the construct; optimising delivery; and demonstrating efficacy and tolerability in a model of long-term limbic epilepsy. This will minimise the potential risks and attract investment for first inpatient clinical trials.
 

Dr Andrea Mechelli

King's College London

Using deep learning technology to make individualised inferences in brain-based disorders

Brain-based disorders, including psychiatric and neurological illnesses, represent 10.4% of global disease. At present, objective tools for detecting and monitoring brain disorders are not available. 

Deep learning is an area of artificial intelligence which allows detection of complex and distributed patterns in data that are difficult to capture using existing approaches. We will assemble a very large dataset of neuroimaging data from more than 12,000 disease-free people and more than 2,000 patients with psychosis. Using deep learning technology we will develop a model of the disease-free brain across different ages and genders and illustrate how this model can be used to detect neuroanatomical alterations and inform clinical assessment in individual patients. 

This will lead to the development of a flexible web-based tool for measuring neuroanatomical alterations in any brain-based disorders. This could help clinicians assess the presence of a disease, monitor its progression and optimise treatment in individual patients.

Professor Richard Pleass

Liverpool School of Tropical Medicine

Hypersialylated fragment crystallisable regions for the treatment of antibody-mediated central nervous system demyelination and microglial activation

Intravenous immunoglobulin (IVIg) is a key therapy for the treatment of immune-mediated neuropathies, including chronic inflammatory polyneuropathy (CIDP) and Guillain-Barre syndrome. The worldwide consumption of IVIg has increased more than 300-fold since 1980 and approximately 100 tons are consumed each year. Less than 5% of injected IVIg is therapeutically active meaning that high treatment doses are needed and adverse events due to excessive protein loading sometimes occurs. There is a dependence on human donors for manufacture and global supplies are critically limited, making IVIg expensive. 

I have developed a means to manufacture recombinant hypersialylated fragment crystallisable regions that bind critical receptors implicated in CIDP. Together with Professor Norbert Goebels and colleagues at the University of Dusseldorf, we will test whether lead molecules protect in pre-clinical models of CIDP, a prerequisite for translation to human studies.

These findings could lead to a cheaper, safer, and more effective alternative to IVIg. 

Dr Marco Prosdocimi

Rare Partners

A clinical trial to assess the repurposing of sirolimus to induce fetal haemoglobin as a strategy to improve quality of life in beta thalassemia

Beta thalassemias are hereditary blood disorders caused by reduced or absent synthesis of haemoglobin beta chains. Patients can be clinically asymptomatic or experience severe anaemia. Survival rates have improved, even for patients requiring transfusions, but quality of life is poor for many patients.
 
Building on a Wellcome Trust Pathfinder award, our team has shown that the drug sirolimus can stimulate fetal haemoglobin (HbF) production. Stimulation of HbF results in a positive clinical outcome for people with beta thalassaemia, and pre-clinical evidence suggests that sirolimus can be used to treat the condition. A pilot clinical trial will explore the use of sirolimus in people with beta thalassemia by evaluating the effect it has on parameters related to red blood cell status and levels of HbF. 

This pilot study will be a first step towards the full clinical development of sirolimus in this new indication.