Research Director: Dr Pantelis Georgiou
Recent trends in daily lifestyle and poor diet have led to an increase in metabolic disorders which are affecting millions of people worldwide. A metabolic disorder develops when organs responsible for regulating metabolism fail to carry out their operation. Diabetes mellitus, currently the most severe metabolic disease and the leading cause of mortality and morbidity in the developed world, is caused by an absolute, or relative, lack of the hormone insulin which is responsible for homeostasis of glucose concentrations. Insulin deficiency leads to elevated glucose concentrations which, in turn, cause organ damage including retinopathy leading to blindness, nephropathy leading to kidney failure and neuropathy which is irreversible nerve damage. At least 3% of the world’s population today is diagnosed with diabetes and this number is doubling every 15 years.
Current research includes:
The bio-inspired artificial pancreas – a fully closed loop system, which mimics the functionality of a healthy pancreas. The core of the system contains a silicon integrated circuit, which behaves in the same way as biological alpha and beta cells of the pancreas. In doing so, it aims to offer more physiological control to subjects with type 1 diabetes, using insulin to control hyperglycaemic events and glucagon to prevent hypoglycaemia.
We are pleased to announce that to date we have successfully validated the bio-inspired artificial pancreas in adult participants with type 1 diabetes acquiring over 800 hours of clinical data with the system, and proving it’s safety and efficacy. Clinical trials were conducted at the NIHR/Wellcome Trust Imperial Clinical Research Facility, Hammersmith Hospital. Studies conducted so far include a 6-hour fasting closed-loop (CL) study (n=20), 13-hour overnight/post breakfast closed-loop study (n=17), 24-hour Randomised controlled crossover study (n=12), 24- hour CL study without meal announcement (n=8) and a 6-hour bi-hormonal study (n=6).
We are delighted to report that our results to date have proven the safety and efficacy of the Bio-inspired Artificial Pancreas and we are now moving forwards to conduct 3 month ambulatory trials on type 1 diabetic subjects in their home environment.
Diabetes management systems – an integrated system of wireless sensors (glucose, heart rate and motion), decision support systems and smart-phones to create a telemedicine platform capable of continually monitoring, recording vital parameters and providing advice on insulin dosing which is required for treatment of diabetes. Additionally, the smart-phone provides a constant link to a clinicians database to allow constant monitoring from the hospital.
We are delighted to report that our smart-phone based Advanced Bolus Calculator for Diabetes (ABC4D) is currently undergoing clinical trials in people with Type 1 diabetes and results to date are promising.
Sensory systems for continuous monitoring of metabolites - which includes devices which fully integrate chemical sensors and low power processing algorithms to provide cheap, disposable and intelligent chemical monitoring systems with long battery lifetimes. These are currently being used to make reliable and robust continuous glucose sensors by integrating glucose sensing micro-spikes with CMOS technology, making the sensor more robust, intelligent and adaptive. These will be expanded to sense other metabolites as well relevant to diabetes management.
Lab-on-chip diagnostics for diabetes – which includes devices that fully integrate a number of electrochemical sensors in CMOS to provide cheap and disposable diagnostics, which can be used at the point of need. These are diagnostic systems for potential genetic screening of type 1 and type 2 diabetes and their associated variants and complications such as MODY (Maturity Onset Diabetes of the Young).
Metabolic Algorithms and Models –– which includes developing in silico models describing the interaction between glucose, insulin, glucagon and other metabolites within the body to allow reliable simulation and validation of algorithms used for diabetes management. We also develop fault detection systems to account for glucose sensor and insulin pump failures and variability within our closed loop system.