In this interview as part of the Early Career Innovators series, recognising the amazing translational work being done by postdocs and non-tenured researchers at University College London (UCL), Dr Mikaël Simard highlights his Devices & Diagnostics Therapeutic Innovation Network (TIN) Pilot Data Fund awarded project, involving the development of a prototype low-cost imaging system for lung proton therapy. 

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In this interview as part of the Early Career Innovators series, recognising the amazing translational work of postdocs and non-tenured researchers at University College London (UCL), Dr Sarah Massey highlights her Devices & Diagnostics Therapeutic Innovation Network (TIN) Pilot Data Scheme awarded project involving the use of a mobile app to manage spasticity symptoms.  (more…)

In this interview as part of the Early Career Innovators series, recognising the amazing translational work being done by postdocs and non-tenured researchers at University College London (UCL), Dr Matthew Wilcox highlights his Devices and Diagnostics Therapeutic Innovation Network (TIN) Pilot Data Fund awarded project, BANTER (Blood biomarker Assessment of Nerve Trauma and Early Reinnervation). 

What is the title of your project and what does it involve?

BANTER (Blood biomarker Assessment of Nerve Trauma and Early Reinnervation), involves the development of a blood test which hopes to improve nerve injury identification. This study will use the SIMOA^TM Neurofilament Light (NfL) chain assay which has been tried and tested in capturing changes associated with a number of diseases of the brain and/or spinal cord such as Alzheimer’s disease and Traumatic Brain Injury. For the first time, this project will repurpose this technology to determine whether it is possible to detect the presence and severity of nerve injury using a well-established animal model. This will involve a collaboration between the UCL Centre for Nerve Engineering and UK Dementia Research Institute Fluid Biomarker Laboratory.

What is the motivation behind your project/therapeutic?

Nerve injuries often lead to permanent loss of movement and pain leading to significant quality of life impairments for patients. It currently takes too long for nerve injuries to be identified and referred for assessment by clinicians with special expertise in this area who may be able to offer surgery to improve outcome. In many cases, this means many patients suffer worse outcomes than had earlier referral been made. A major reason for this is because swift identification of nerve injuries depends on patients being able to access facilities with expensive imaging and tests which measure the electrical properties of nerves (such as MRI scans and Electromyography). Even if patients are able to access this technology, clinicians often find them difficult to interpret.

This project addresses this issue by developing a cheaper, readily available and objective test which may be able to predict the presence and severity of a nerve injury from a small blood sample.

Why did you want to apply to the Devices & Diagnostics TIN Pilot Data Fund?

A challenging step in transitioning from an early career researcher to an independent investigator is turning research ideas into compelling grant proposals. The TIN Pilot Data Fund provided an invaluable opportunity to develop a research idea right the way from planning and costing the experiment through to pitching to academics and industry representatives. This funding will provide the data necessary to design larger studies and help establish my research identity.

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How did you find the process for the TIN Pilot Data Fund?

Throughout the application process, support was provided through the ACCELERATE training workshops which focused on developing communication and presentation skills. This experience has helped me to understand how to develop convincing pitches to different members of the academic and industry community; a skill that will be essential in my next career steps towards a surgeon-scientist.

Learn more about the translational training offered through ACCELERATE 

What do you hope to achieve in the 6 months duration of your project?

We will reach the first milestone of our project in 6 months. The success criteria of this will be to show the validity of the SIMOA^TM Neurofilament Light (NfL) chain assay in identifying the presence and severity of nerve injury in a controlled animal model. Alongside this laboratory-based research, I will be working closely with clinical colleagues at the Royal National Orthopaedic Hospital to design a corresponding study in nerve injured patients.

What are your next steps from now?

I hope to move into full time clinical training as a Foundation Doctor from August 2022 with the long term view of becoming a reconstructive surgeon-scientist. I am excited by the challenges I will encounter within the clinical arena along the way and look forward to addressing some of these by continuing to work closely with the diverse research community that UCL offers.

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About Dr Matthew Wilcox

Dr. Matthew Wilcox is a Research Fellow at the UCL School of Pharmacy and a final year UCL medical student. In 2020, Matt was awarded a PhD in Translational Neuroscience which benefited from a collaboration between the Peripheral Nerve Injury Unit, Royal National Orthopaedic Hospital (a national referral centre for nerve injury) and the UCL Centre for Nerve Engineering.

Matt works within an interdisciplinary team focused on providing novel insights into the cellular and molecular basis of human nerve regeneration, developing improved imaging-based outcome measures of nerve regeneration and diagnostic tools for nerve injury. Together, this is informing the development of clinical trials which hope to test the efficacy of regenerative therapies for nerve injury and disease.

In this Devices & Diagnostics TIN interview as part of the Early Career Innovators series, acknowledging the amazing translational work being done by early career researchers within the UCL Therapeutic Innovation Networks (TINs), Dr Nikolas Pontikos highlights his Devices & Diagnostics TIN (co-lead by the UCL Institute of Healthcare Engineering’s Translational & Industry Delivery Group) Pilot Data Fund awarded project, involving the use of artificial intelligence to accelerate genetic diagnosis of inherited retinal disease.

What is the title of your project and what does it involve?

The title of my project is: “Eye2Gene: Accelerating Genetic Diagnosis of Inherited Retinal Disease with AI”

Inherited retinal diseases are a leading cause of visual impairment in children and the working age population. Mutations in over 300 genes are associated with IRDs and identifying the affected gene in a patient is the first step towards diagnosis, prognosis and treatment. Currently, inherited retinal diseases are detected first by retinal imaging analysis and later confirmed by genetic analysis. Teams combining these analytical skills are scarce hence my idea is to train an AI (artificial intelligence), Eye2Gene, to achieve this in one algorithm. The training data will consist of retinal images from 4000 inherited retinal disease cases at Moorfields Hospital segmented over a 2 month period.

What is the motivation behind your project/therapeutic?

Around 30,000 individuals in the UK have an inherited retinal disease (3.5M globally). Less than 40% of patients have been diagnosed because of poor screening. A late diagnosis means less chances for treatment. Genetic diagnosis is crucial for management and treatment of patients by upcoming gene-targeted treatments. Rare disease drug development is one of the fastest growing pharma markets ($262bn by 2024). Eye2Gene will increase the rate of genetic diagnosis, allowing more to be treated sooner. There are currently no competing products for inherited retinal disease genetic diagnosis.

Why did you want to apply to the Devices & Diagnostics TIN Pilot Data Fund?

I first heard of the Translational Innovation Network Pilot Data Fund through the UCL newsletters of Personalised Medicine. I attended a few events organised by the UCL Translation Research Office and was really impressed by the guidance and support that was provided to Early Career Researchers such as translational pathways, presentation skills and grant writing workshops often led by experienced professional external consultants.

Having recently published the dataset for inherited retinal diseases from Moorfields Eye Hospital (Pontikos et al., 2020) and developed the deep-learning algorithm Eye2Gene prototype, the Pilot Data Fund seemed like the ideal kickstarter grant to launch my research project in order to build a pilot imaging dataset of segmented inherited retinal disease scans to allow for explainable AI and enhance algorithm performance.

How did you find the process for the TIN Pilot Data Fund? What did you learn?

The process was very educational. The workshops organised were of a very high standard and for the first time in my career, I received professional training in writing grants and pitching ideas. I also learnt about the translational pathway and the different stages of technology readiness. I think perhaps two workshops that stood out for me were the ones presented by Granted Ltd and by Simon Cain. As an exuberant scientist, project management (Gantt charts, KPIs, risk management etc) is always something that came as an afterthought for me, so it was quite revealing for me to see just how central it is to the grant writing process and funding success. In the future, through additional TIN opportunities, I am also very much looking forward to learning more about regulatory aspects of medical device development.

What do you hope to achieve in the 6 months duration of your project?

After 6 months I hope to have a dedicated retinal imaging annotation platform and a large manually segmented dataset of inherited retinal disease scans (>2000). This will allow Eye2Gene to offer interpretable output, highlighting to healthcare professionals exactly which parts of an image were used to derive a diagnosis. These outputs will be useful for the training of multiple AI algorithms including Eye2Gene.

Furthermore, the retinal image annotation platform that will be developed will support future image segmentation projects by facilitating collaborative editing and training of medical graders, as well as supporting medical image annotation for clinical trials. In the future, I hope to share these annotated rare disease datasets with the community and promote natural history studies and drug development. On the back of this funding from TIN, I have already submitted a project grant application to NHSX and the Wellcome Trust to support further development of the Eye2Gene software as a medical device.

What are your next steps from now?

For the Eye2Gene project I have already exported the inherited retinal disease imaging datasets and the software development of the image annotation platform has started which should be finished by end of May. After which, the annotation of images will start and I anticipate will finish in July. Further to this, the UCL Translational Office has been incredibly supportive in helping me apply for large project grants such as the Wellcome Trust Innovator Award and the NHSX AI Award. They have helped me connect with relevant individuals outside of my area of expertise, such as experienced project managers, regulatory consultants and health economists at UCL. These individuals have taken an active part in helping me write my grant applications which has been really fantastic! I will hear back from these grants in February and hope to be successful (fingers-crossed).

Whether or not I am successful with these grant applications in the short-term, I believe the whole process has greatly strengthened my grant and fellowship writing skills, especially by teaching me good project management and pitching skills.
Career wise I have also recently submitted two fellowship applications one to NIHR and one to MRC which if I am successful, will start in October 2021, giving me five years of funding. I also plan on submitting a studentship to hire a PhD student (as subsidiary supervisor).

About Dr Nikolas Pontikos

Dr Pontikos is an early career researcher funded by a short-term Moorfields Eye Charity Career Development Award. He is based at the UCL Institute of Ophthalmology and Moorfields Eye Hospital, and collaborates with the Institute of Health Informatics and the Genetics Institute. He has an MEng in computer science from UCL, a postgraduate MSci in bioinformatics from Imperial College and a PhD in genetics and machine learning from Cambridge University. He is very interested in the analysis of healthcare data to provide personalised care.

He jointly analyses genetics, medical imaging and text data to develop decision support systems for diagnosis, prognosis and treatment. His focus has mostly been on rare eye diseases but his methodology is widely applicable to rare genetic diseases. He is very interested in learning more about the regulatory aspects of developing software as a medical device.

References

Pontikos, N., et al. (2020). Genetic basis of inherited retinal disease in a molecularly characterised cohort of over 3000 families from the United Kingdom. Ophthalmology. https://doi.org/10.1016/j.ophtha.2020.04.008

In this next Devices & Diagnostics TIN interview as part of the Early Career Innovators series, acknowledging the amazing translational work being done by early career researchers within the UCL Therapeutic Innovation Networks (TINs), Dr Frédéric Lange highlights his Devices & Diagnostics TIN (co-lead by the UCL Institute of Healthcare Engineering’s Translational & Industry Delivery Group) Pilot Data Fund awarded project, “Understanding the role of brain oxygenation and metabolism in the pathophysiology and prognosis of relapses and progression in multiple sclerosis”.

Please give an overview of your research and the project that has been funded by the TIN Pilot Data Fund.

I am a biomedical engineer/physicist with a focus in biophotonics. Since I started my PhD, I’ve been working on using near infrared light to monitor the human brain physiology. Indeed, light in that range can probe deep tissues like the brain, giving us access to very useful information on tissue oxygenation or metabolism. If you are interested in that subject, I recommend consulting our public engagement website, https://metabolight.org, that explains the basics of the physics and engineering of what we do, and how we use our systems in the clinic.

The title of my TIN Pilot Data project is “Understanding the role of brain oxygenation and metabolism in the pathophysiology and prognosis of relapses and progression in multiple sclerosis”. In this project, I will use an optical instrument that I developed with some colleagues, to collect information on brain’s oxygenation and energy levels in people with multiple sclerosis (pwMS).

What is the motivation behind your project/therapeutic?

MS is the most common cause of non-traumatic disability in young adults, affecting 131,720 people in the UK. UCLH alone treats more than 5000 people with MS. Despite advances in treatments, at 17 years post-diagnosis, 11% of patients cannot walk unaided, and 18% enter a progressive form of the disease. Identifying additional mechanisms of disease progression and which patients are most likely to benefit from additional treatments therefore represents a huge unmet need.

All current MS treatments target neuroinflammation, yet substantial pre-clinical and clinical data suggests a causal role of hypoxia. We hypothesise that our instrument will allow us to identify those pwMS with the greatest such deficits, hence allowing:

• Enrichment of future clinical trials testing interventions aimed at reversing these processes.
• The monitoring the patient’s response to such treatment.

Why did you want to apply to the Devices & Diagnostics TIN Pilot Data Fund?

The Devices & Diagnostics TIN Pilot Data Fund was a great opportunity for me as it was perfectly fitting the stage of my current research. Indeed, I was just finishing the developmental phase of the instrument that I wanted to build, and I was transitioning to its use in the clinic. With my clinical colleague, we could start to use the instrument on patients, but we realized that a few changes were needed in order to facilitate its use in a clinical environment, so we needed to make some adjustments. However, it can be difficult to find funds at this stage of a project, as it is not an engineering project anymore, but at the same time, it is not a clinical project yet. We needed some preliminary data on patients in order to be able to apply to a more clinically focused grant. So, this kind of fund is perfect to close the gap between an engineering and clinical project.

Moreover, from a more personal point of view, this fund was a good opportunity to apply to my first independent grant, which I hope will be the first step towards my independent career.

Learn more about TIN opportunities for researchers

What do you hope to achieve in the 6 months duration of your project and what are the next steps from now?

With this project, I will be able to upgrade my existing optical instrument, so it is easier to use in the clinical environment and more robust. The fund will be used to buy the essential components needed to make these upgrades. I am currently purchasing the equipment needed. The upgrade process will occupy the first half of the project, between the hardware and the software work, and the recalibration of the system. Then, in the second half of the project, we will aim to scan as many pwMS as possible, so we can have a good set of preliminary data. This will certainly prove challenging in these trouble times, but I am confident that we will be acquire some very useful data.

About Dr Frédéric Lange

Dr Frédéric Lange received his Ph.D. degree in biomedical optics from the University of Lyon and INSA de LYON in France in 2016. Since then, he has been a Research Associate with the Biomedical Optics Research Laboratory, which is part of the Department of Medical Physics and Biomedical Engineering at UCL.

His main research interests are in the development of diffuse optics instrumentation and methodologies for biomedical applications, especially for brain monitoring.