Control of ECM organisation and the mechanical environment in a joint 'on a chip' device.

'Organ on a chip' (OOAC) devices provide new approaches to miniaturized in vitro models for co-culture of multiple tissues such as in the joint. These tools offer new physiological systems for screening of new drug targets and for use in disease stratification and diagnostics. These devices organize multiple cell types from complex tissues in potential 3D static and dynamic environments. The development of effective biological scaffold materials for OOAC devices relies on the ability to present precise environmental cues to specific cell populations to guide their position and function.

Ordered dynamic nano-scale structures such as fibres in the extracellular matrix can modulate cell behaviors in health and disease. Using biomagnetic strategies, fibres can be orientated in collagen scaffolds in a tailored way. Understanding the role of dynamic environments on joint behaviour is fundamental to these models. The El Haj group has been developing innovative approaches to utilise magnetic nanoparticles (MNPs) to deliver mechanical forces in cell culture models, which is being taken forward into a new product, DYNASCREEN by an industrial partner, MICA Biosystems. However, such approaches can also be adopted for organising fibres and cells, and this student project aims to establish a new collaboration to adapt the technology to develop organised matrices for OOAC models. This work complements well the novel magnetic mesenchymal stem cell spheroid 3D models which has been developed by the Berry group in Glasgow University.

El Haj with Screen (QMC) have recently been awarded an MRC UKRMP project (2019-2023) to design a 'joint-on-a-chip' which aligns with an existing MRC UKRMP Hub held by El Haj focused on Engineering the stem cell niche (2019-2023). This CDT student will be an aligned project to investigate a new research area of ordered matrices and dynamic loading delivered through biomagnetic approaches in vitro in the chip devices. The student will work closely with our clinical co-supervisor from ROH in terms of sourcing human tissues and ensuring clinical relevance and pull. The student would work with partner commercial companies, EMULATE (a partner in the MRC Organ on a chip project and QMUL centre) and MICA Biosystems (DYNASCREEN product development) who are designing new products in this area, directly linking with ongoing activity in funded projects. Their interactions will be through visits to their R&D labs and training in the use of the EMULATE organ chips and MICA DYNASCREEN systems.

Humanised, 3D tissue models are finding interest due to current overly-simplified immortal cell lines and non-human in vivo models providing poor prediction of drug safety, dosing and efficacy; 43% of drug fails are not predicted by traditional screening and move into phase I clinical trials1. Phase I sees a 48% success rate, phase II a 29% success rate and phase III a 67% success rate [1]. The drug development pipeline is pressurised due to adoption of high throughput screening / combinatorial libraries. However, while R&D spend has increased to meet this growing screening programme, success, measured by launched drugs, remains static [2]. This poor predictive power of the >1 million animals used in the UK each year drives the 12-15 year, £1.85B pipeline, for each new drug launch [3]. Contract research organisations (CROs) are also similarly hit by these problems.

Drive to reduce animal experimentation in toxicology and outright banning of animal testing for e.g. cosmetics in the UK has driven companies to outsource or to adopt the limited number of regulator approved NAT models for e.g. skin [4,5].

Another key area that uses 3D tissues is the field of advanced therapeutic medicinal products (ATMPs), i.e. tissue engineering/regenerative medicine. Regulation is a major ATMP bottleneck. It is thus noteworthy that regulators, such as the UKs Medicines and Healthcare Products Regulatory Agency (MHRA), are receptive to the inclusion of NAT-based data in investigative medicinal product dossiers [6].

The lifETIME CDT will directly address these issues through nurturing of a cohort training not only in the research skills required to conceive and design new NATs, but also in skills based on:

- GMP and manufacture.
- Commercialisation and entrepreneurship.
- Regulation.
- Drug discovery and toxicology - a focus on the end product.
- Policy.
- Public engagement.

Our NAT graduate community will impact on:

- Pharma - access to skills that develop tools to unlock their drug discovery and testing portfolios. By helping train graduates who can create and deploy NATs, they will increase efficiency of drug development pipelines.

- ATMP manufacturers - the same skills and tools used to deliver NAT innovation will help to deliver tissue engineered / combination product ATMPs.

- CROs - access to skills to create platform tools providing more sophisticated approaches to the diverse research challenges they face.

- Catapult Centres - access to skills that provide innovation that can be deployed across the broader healthcare sector.

- Regulatory agencies e.g. MHRA - better education for the next generation of scientists on development of investigational new drug / medicinal product dossiers to speedup approvals.

- Clinicians and NHS - access to more medicines more quickly through provision of highly skilled scientists, manufacturers and regulators. NATs will help drive the stratified/personalised medicine revolution and understand safety and efficacy parameters in human-relevant tissues. Clinicians will also benefit from development of ATMP-based regenerative medicine.

- Patients - benefit from skills for faster and more economically streamlined development of new medicines that will improve lifespan and healthspan.

- Public and Society - benefit from the economic growth of a thriving drug development industry. Benefits will be direct, via jobs creation and access to wider and more targeted healthcare products; and indirect, via increased economic benefit of patients returning to work and increased tax revenues, that in turn feed back into the healthcare systems.


[1]. Cook. Nat Rev Drug Discov 13, 419-431 (2014).
[2]. Pammolli. Nat Rev Drug Discov 10, 428-438 (2011).
[3]. DiMasi. Health Econ 47, 20-33 (2016).
[4]. Cotovio. Altern Lab Anim 33, 329-349 (2005).
[5]. Kandarova. Altern Lab Anim 33, 351-367 (2005).
[6]. https://goo.gl/i6xbmL