Giovanni Stracquadanio awarded EPSRC Early Career Fellowship
Giovanni Stracquadanio, a senior lecturer in synthetic biology and co-director of the Edinburgh Genome Foundry, is the recipient of UK government fellowship that helps early career researchers with the greatest potential to develop world-leading research.
Engineering and Physical Sciences Research Council (EPSRC) early career fellowships support talented and ambitious researchers to deliver research excellence.
The fellowships provide applicants with the flexibility and freedom to design a package that fits their career ambitions, research needs and personal development requirements.
Fellowships can focus on discovery science, innovation, instrumentation/technique development or software engineering, or a combination of these.
Giovanni Stracquadanio, based at the Institute of Quantitative Biology, Biochemistry and Biotechnology, has been awarded £1.4M to develop therapies to treat Fabry disease – a rare metabolic disorder.
About Fabry Disease
Fabry disease is a genetic condition resulting in a lack of functional versions of an enzyme – known as alpha-galactosidase A (alpha-GAL), which breaks down lipids or fats.
These fats collect in blood vessels and tissue, raising the risk of heart attack, stroke and kidney failure.
Approximately one in every 40,000 males has classic Fabry disease. Late-onset Fabry disease is more common and affects about one in every 1,500 to 4,000 males.
The condition frequently goes undiagnosed in women as they may only display mild symptoms or lack symptoms entirely.
Enzyme Replacement Therapies
Giovanni’s fellowship will integrate machine learning, synthetic biology and lab automation to establish a platform for designing, building and testing enzyme replacement therapies.
This new data-driven engineering platform will overcome the challenges faced by traditional methods of making and administering these enzymes.
Human enzymes are currently manufactured using mammalian cell-based systems, which are expensive, difficult to scale and provide low yields.
These challenges mean that enzyme replacement therapies cost up to 500,000 USD per year per patient. This limits access and places a significant burden on patients and national health systems.
Human enzymes, manufactured using traditional methods, also become unstable in blood, have poor cellular uptake and can cause immune responses leading to unwanted side effects.
By using better design methods the new approach will offer more precise control of the enzyme’s amino acid sequences – which determines the enzyme’s properties.
This will speed the discovery of new amino acid sequences that can encode the same function while limiting side effects. The new design method will also significantly reduce the cost of manufacturing these enzymes.
The fellowship is supported by two industrial partners, Fujifilm Dyosynth and iBioIC.
Combining machine learning with synthetic biology and lab automation will allow us to design effective Enzyme Replacement Therapies (ERTs), cutting costs and time for R&D from years to months and provide an affordable therapeutic options for those who need it the most, the patients.