Designing bio-instructive materials for translation ready medical devices

Healthcare relies on medical devices, yet often these have significant risk of infection and failure. The medical device market is estimated to be just under US$500 billion, while US$25 billion is spent annually on treatment of chronic wounds. As our populations becomes older, our healthcare systems are also becoming stressed by multi-antibiotic resistance and viral outbreaks. For example, 50% of initial COVID-19 fatalities were due to secondary bacterial infections [Zhou et al. The Lancet, 2020]. Medical device failure rates of up to 20% burden our health service disproportionately through device centred infection, immune rejection, or both. The biomaterials that devices and external wound care products are made from significantly influence immune and healing responses and affect the outcome of infection.

In the EPSRC Programme Grant "Next Generation Biomaterials Discovery", physical surface patterns (topographies) combined with novel polymers were found which both reduce bacterial biofilm formation and increase the immune acceptance of materials in vitro and in vivo in preclinical infection models. This provides a new paradigm for biomaterials used as implants and wound care products, where novel polymers can be topographically patterned to improved healing and acceptance using bio-instruction. To exploit these findings requires targeting to specific medical device environments and elucidation of the mechanism of action for translation by industry.

This project will utilise 3D printing to manufacture ChemoTopoChips containing over a thousand polymer chemistry-topography combinations that allow the possible design space to be efficiently explored and mapped using semi-automated in-vitro measurements of host immune cell and infecting pathogen interactions individually and in co-culture. These ChemoTopoChips will allow a very high content of molecular information to be extracted from biomolecules secreted into the culture media (the secretome), those adsorbed to the surface (the biointerface) and their impact on both host cells and bacteria. The same fabrication approaches will be used to make devices for preclinical testing; in vivo information will be maximised using minimally invasive monitoring of infection and healing over time and detailed analysis of explants. These information streams will be merged using artificial intelligence (specifically machine learning) to build effective models of performance and provide mechanistic insight, allowing design of materials ready for translation as medical devices outside this project.

After consultation with a wide range of clinicians we have chosen to target the following two devices:

-Wound care products for chronic/non-healing wounds: dressings to reduce infection, induce immune-homeostasis and promote healing in chronic wounds that result in 7000 diabetes related amputations in the UK per year and cost the NHS £1bn a year to manage.

-Implants requiring tissue integration but prone to fibrosis/adhesion and biofilm-associated infection: surgical meshes used for repair of hernias or pelvic organ prolapse commonly afflicting women after childbirth. The NHS undertakes 100k such operation each year with infection rates of up to 10%, plus foreign body response complications.

The team assembled to exploit this opportunity has unique experience in the areas of biomaterials, artificial intelligence, additive manufacturing and in vitro and in vivo measurements of immune and bacterial responses to biomaterials. Facilities including the recently opened £100m Nottingham Biodiscovery Institute, the recently funded EPSRC £1m suite of high resolution/high throughput 3D printers and the unique £2.5m 3DOrbiSIMS Cat2 cryo-facility. These investments in Nottingham make this the only location in the world that is capable of undertaking this project.

An Advisory Board of clinicians, industrial partners and leading academics will meet annually to provide input to the project.