Towards development of eye-safe multiplex resonance raman device for point-of-care neurodiagnostics

Aiming at improving trauma triaging and point-of-care and emergency medicine, this project will focus on exploring and validating the Raman-based detection of TBI-indicative biochemical changes from biofluids, brain tissue cultures and in poartcilarly, the cerebrospinal fluid (CSF), collected immediately after TBI. Since the optic nerve is visible at the back-of-the-eye, as a projection of brain tissue and bathed in CSF, it provides an optically clear window into the brain. Therefore, the crucial knowledge acquired during this project, will lay the platform towards development of a novel eye-safe Raman imaging technique to examine the optic nerve and screen for neurological biomarkers as well as allow monitoring drug-delivery, towards developments of new pharmaceutical interventions.

This project will enable crucial development steps towards the long-term approach required to address this urgent clinical need, developing a new generation of PoC technology capable of playing a direct role in TBI detection. The implications of having a rapid, non-invasive, quantitative test for TBI would be particularly useful in settings where rapid decisions have to be made regarding whether or not a patient is safe to return to full activity e.g., contact sports or after exposure to blast injury on the battlefield. Engineering novel device and testing it for detection of TBI-indicative markers from biofluids and tissues as well as for monitoring medical interventions and drug delivery post TBI (through rapid, reliable, non-invasive and safe methods of detecting and quantifying TBI), the project will deliver medical tools for better treatment decisions and improved outcomes subsequent to TBI for greater quality of life and ultimately, improved survival.

The idea of using laser spectroscopic techniques to non-invasively detect, quantify and monitor treatment of TBI is highly novel and thus, it is likely that this project will break new ground in fields of diagnostic laser applications, advanced optical set-ups, brain-injury and neuro-rehabilitation. The Raman device could find a wide range of related applications in future e.g., in exploring drug interactions within the eye, either in new medicine development or as part of a treatment.

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