Invisible Customisation - A Data Driven Approach to Predictive Additive Manufacture Enabling Functional Implant Personalisation

Additive manufacturing (AM), otherwise known as 3D printing, is enabling the production of medical implants that are customised, in terms of size and shape, to a person's skeleton. Compared with devices of a standard size, these personalised designs fit the patient better and as such offer improved aesthetics and reduce surgery times. While customisation has many benefits, the challenge is to ensure each bespoke device is made to the same quality. This is difficult because the implant shape is completely unique and may be very complex.

Currently in an effort to ensure quality, researchers make lots of plain cube test samples using various manufacturing settings and then compare properties before deciding what combination to use for the real implant. This trial and error approach takes a lot of time and may not even produce very predictable devices because the optimisation is not performed on shapes that are representative of real implants. In this project we will make various design features common to medical implants (e.g. curved surfaces, screw holes) and collect key performance data during and post manufacture. By using cutting edge mathematics, we will create a network that allows us to accurately predict which manufacturing settings will produce the best quality for any design shape. This tool will help businesses to standardise production of customised medical devices in a quick and accurate manner that is not dependent on the user's knowledge. Thereby we will open up the advantages of AM to more companies and help existing adopters to meet the standardisation requirements of the impending new Medical Device Regulations.

Overall this project aims to better understand the relationships between additive manufacturing settings and implant properties, which will help us to improve the quality of these anatomically personalised devices. Beyond this we plan to create a tool to enable the creation of implants that are not only customised to the size and shape of the patient's skeleton but also two critical functionalities: mechanical strength and cell adhesion. It is known that if an implant is too strong compared with the surrounding native bone this can cause it to fail. As such, developing a way to select manufacturing or design parameters that enable mechanical matching to the patient's skeleton will help implants to last longer and reduce the number of failures. Besides mechanical mismatch, the other biggest threat to bone implants is infection. Our preliminary work has shown that surface roughness directly impacts the ability of cells, mammalian and bacterial, to stick onto AM devices. In this project we will exploit this knowledge to enable users to select manufacturing settings that result in a defined surface roughness that either enables or prevents cell attachment. This novel capability could be used, for example to create implants with a surface that stops bacterial cells from sticking and thus minimises infection risks. There is also potential that this tool could help to improve bonding between the implant and native tissue by recommending manufacturing settings that result in surface topographies that encourage growth of bone forming osteoblast cells.

In summary, this project is focused on standardising the way we use 3D printing to ensure the properties of bespoke implants are predictable. This will be achieved by using mathematics to move the AM field away from trial and error. By understanding the relationships between manufacturing settings and key properties, we will create two tools that will enable us to make functionally personalised devices. The ability to predictively and selectively tailor mechanical properties and surface roughness will drive a new generation of implants that last longer and fail less often. Thereby, this project will ultimately improve the lives of millions of people who receive bone implants and help to reduce the associated healthcare costs.

A multidisciplinary approach will be employed to improve the predictability of additive manufacturing (AM) enabling customised medical implants to be made in a more standardised way. The new knowledge gained from this approach will be exploited to move beyond current industrial capabilities and deliver the next generation of functionally tailored devices that better meet patient needs. Overall, this project will deliver several toolkits to standardise AM of bespoke medical devices while also driving innovations in customisation that will holistically impact all research stakeholders.
Patients: this research will ultimately be of most benefit to the millions of people who receive metal implants to replace damaged or diseased bones. The proposed multidisciplinary approach to standardise production of bespoke implants will enable manufacturers to rapidly adhere to the new Medical Device Regulations. This will ensure that more patients may benefit from the significant advantages of receiving an anatomically tailored implant. Development of mechanically and biologically customised implants will offer patients further benefits through reduced failure risks and prolonged device life-spans. This will improve the patient's quality of life and welfare while also reducing associated healthcare treatment costs.
Industrial: by reducing the reliance of AM on user expertise this project will open up use of these technologies to more companies whom will benefit from improved design freedoms and cost savings. Furthermore, improving the performance predictability of bespoke AM medical devices will offer valuable support to businesses who already use selective laser melting. Specifically, the outcomes of this project may serve as a best practise guideline to meet the new Medical Device Regulations, helping minimise associated costs and thus ensuring competitiveness of UK manufacturers within this growing market. Highlighting the extra value that may be gained in healthcare through the novel functionally tailored devices will also raise the profile of AM. This may increase demand for supply chain products, such as software, materials, and metrology equipment. Thereby, the disruptive nature of this project will lead to the growth of numerous interrelated industrial sectors.
Clinical: failure of implants has a potential to damage surgical reputation. As such, clinical stakeholders will indirectly benefit from the improved reproducibility and functionality of custom medical devices made in this project. This multidisciplinary proposal is also the ideal opportunity for healthcare professionals to learn more about future innovations. Regular engagement between the research team and key clinical opinion leaders will ensure the outcomes of this project are relevant to current practise and thus more likely to achieve the impacts described for all stakeholders. It is also anticipated that these partnerships will grow into other collaboration opportunities beyond the proposed project, which may focus on applying these developments within orthopaedics, craniomaxillofacial, trauma, and dental applications.
Educational beneficiaries: the application of mathematics in this proposal to solve cutting edge physical science challenges creates the perfect opportunity to inspire future generations into a range of STEM subjects. It also offers the research team great training opportunities creating a strong foundation from which to widely share this useful new knowledge. This learning will be passed on to numerous students through new teaching activities and to the public via workshops/events, which will also provide the team valuable feedback to help guide progress. Through working closely with world leading industrial and clinical partners there is also significant potential for this research to support alignment of academic standards with commercial practise, which will be integrated into the team's teaching activities to enhance student employability.