Development of a 3D model of the cortex for investigation of neurodegenerative diseases

Neurodegenerative diseases are becoming increasingly prevalent. Advances in modern medicine have led to an increase in life expectancy, which has led to an increase in age-associated disorders, such as dementia. The risk of developing dementia doubles every 5 years after the age of 65 (Corrada et al., 2010, Matthews et al., 2016). Current estimates suggests that AD costs the NHS~£23 billion a year (NHS, 2020). This cost divides into informal care (~42%), social care (~39%) and healthcare (~16%) (Prince, 2014). An improved understanding of the progression and diagnostic features of Alzheimer's disease (AD) will promote earlier diagnosis. There is no cure for AD, with current treatments only acting to limit symptoms and doing little to address the underlying pathology. Current platforms for testing of potential novel therapeutics are outdated and unreliable, resulting in a lack of viable treatments for neurodegenerative diseases such as AD. Animal models and conventional 2D culture platforms fail to recapitulate the complex environment found within the human cortex, an area heavily implicated in the development of age-associated neurodegeneration.
Whilst animal models do possess the three-dimensional environment necessary to model neuronal tissue, translation to human physiology is difficult. Conversely in vitro culture systems do possess the necessary humanised components but fail to reproduce the complex 3D morphologies observed in vivo. This project aims to bridge the gap between in vivo and in vitro modelling of the cortex, via creation of a 3D printed tissue engineered construct with physiologically relevant architecture and composition. Utilisation of biomaterials will enable creation of printable hydrogel scaffolds capable of supporting cell culture, while providing mechanical and biochemical cues to cells encapsulated within. A secondary support gel will be utilised to enable printing of low-viscosity bioinks necessary for creation of soft tissues such as the cortex. The ultimate aim of this project is to produce a printed hydrogel construct capable of mimicking the healthy and diseased cortex, while promoting formation of functional neuronal networks in 3D

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