Integrating imaging and drug delivery systems to improve radiotherapy

Aim of the PhD Project:

Targeted radionuclide therapy (TRT) and radiotherapy are effective methods to treat cancer but with side effects.
The use of radiosensitisers improves their efficacy but they have suboptimal pharmacological properties.
We will use drug delivery strategies based on nanomedicine combined with imaging to improve and guide TRT and radiotherapy.

Project Description / Background:

Targeted radionuclide therapy (TRT) relies on a radiopharmaceutical to target diseased tissues, such as those containing cancer cells. These radiopharmaceuticals consist of a molecule containing a radionuclide that emits beta or alpha particles, combined with a cell-targeting moiety for specific binding to the target cell (e.g. cancer cell receptor). Recent clinical achievements using TRT include treatment of neuroendocrine tumours with 177Lu-somatostatin analogue peptides and treatment of prostate cancer patients with 225Ac-PSMA (prostate-specific membrane antigen).

Despite their high therapeutic efficacy through targeted radiation damage at the cell level, TRT also induces side effects. These include nephrotoxicity, salivary glands toxicity/xerostomia and myelosupression. In order to improve the therapeutic efficacy of radiation therapies, a group of small-molecule drugs termed radiosensitisers have been developed. The rationale is that by making the target/tumours more radiosensitive using these chemotherapeutics, the radiation dose of TRT and hence their side effects can be minimised. Examples of radiosensitisers include PARP inhibitors such as olaparib and epigenetic modifiers such as vorinostat and 5-aza-2-deoxycytidine. These work by inhibiting key enzymes of the DNA repair (PARP) and DNA acetylation/methylation (epigenetic modifiers) of cells. Unfortunately these radiosensitising drugs - like most chemotherapeutics - are themselves not free from undesirable side effects, which include, among others, increased risk of infection and nephrotoxicity. Most of these are a result of the systemic administration of the drugs, which results in unspecific biodistribution to normal tissues.

Here, we propose to kill two birds with one stone by delivering radiosensitisers using nanomedicine-based drug delivery systems, providing targeted radiosensitisers delivery (thus fewer side effects) to allow targeted radionuclide therapies at lower radiation doses. This approach has previously been clinically proven to preferentially deliver the drugs at the target site (tumours, inflamed tissues) while reducing the side-effects of systemically administered toxic drugs in both cancer and in arthritis.

But, can we identify if the radiosensitisers are reaching its target and what is its local concentration? Being able to do so will allow us to predict the response of each specific target tissue to TRT, thereby influencing the amount of radioactivity that will be used to achieve therapeutic outcomes. In addition, combination of this information with image-based information of the concentration of TRT in the same lesions should be highly predictive of overall response to the combination therapy. Hence, we propose to develop a multi-radionuclide imaging method (multi-isotope PET or SPECT) that will allow us to radiolabel and track independently a nanomedicinal formulation of a radiosensitiser for improved target delivery and lower systemic side-effects, as well as the TRT agents. This will be possible using standard multi-radionuclide SPECT or multi-radionuclide PET imaging, by exploiting the new generation of total-body scanners. We aim to prove that the level of co-localisation of the two imaging signals in the target(s) will show a positive correlation with the response to the treatment. The student should have a background in chemistry, pharmacy or radiopharmacy, or any field related to drug delivery and molecular imaging.

Strains on the healthcare system in the UK create an acute need for finding more effective, efficient, safe, and accurate non-invasive imaging solutions for clinical decision-making, both in terms of diagnosis and prognosis, and to reduce unnecessary treatment procedures and associated costs. Medical imaging is currently undergoing a step-change facilitated through the advent of artificial intelligence (AI) techniques, in particular deep learning and statistical machine learning, the development of targeted molecular imaging probes and novel "push-button" imaging techniques. There is also the availability of low-cost imaging solutions, creating unique opportunities to improve sensitivity and specificity of treatment options leading to better patient outcome, improved clinical workflow and healthcare economics. However, a skills gap exists between these disciplines which this CDT is aiming to fill.

Consistent with our vision for the CDT in Smart Medical Imaging to train the next generation of medical imaging scientists, we will engage with the key beneficiaries of the CDT: (1) PhD students & their supervisors; (2) patient groups & their carers; (3) clinicians & healthcare providers; (4) healthcare industries; and (5) the general public. We have identified the following areas of impact resulting from the operation of the CDT.

- Academic Impact: The proposed multidisciplinary training and skills development are designed to lead to an appreciation of clinical translation of technology and generating pathways to impact in the healthcare system. Impact will be measured in terms of our students' generation of knowledge, such as their research outputs, conference presentations, awards, software, patents, as well as successful career destinations to a wide range of sectors; as well as newly stimulated academic collaborations, and the positive effect these will have on their supervisors, their career progression and added value to their research group, and the universities as a whole in attracting new academic talent at all career levels.

- Economic Impact: Our students will have high employability in a wide range of sectors thanks to their broad interdisciplinary training, transferable skills sets and exposure to industry, international labs, and the hospital environment. Healthcare providers (e.g. the NHS) will gain access to new technologies that are more precise and cost-efficient, reducing patient treatment and monitoring costs. Relevant healthcare industries (from major companies to SMEs) will benefit and ultimately profit from collaborative research with high emphasis on clinical translation and validation, and from a unique cohort of newly skilled and multidisciplinary researchers who value and understand the role of industry in developing and applying novel imaging technologies to the entire patient pathway.

- Societal Impact: Patients and their professional carers will be the ultimate beneficiaries of the new imaging technologies created by our students, and by the emerging cohort of graduated medical imaging scientists and engineers who will have a strong emphasis on patient healthcare. This will have significant societal impact in terms of health and quality of life. Clinicians will benefit from new technologies aimed at enabling more robust, accurate, and precise diagnoses, treatment and follow-up monitoring. The general public will benefit from learning about new, cutting-edge medical imaging technology, and new talent will be drawn into STEM(M) professions as a consequence, further filling the current skills gap between healthcare provision and engineering.

We have developed detailed pathways to impact activities, coordinated by a dedicated Impact & Engagement Manager, that include impact training provision, translational activities with clinicians and patient groups, industry cooperation and entrepreneurship training, international collaboration and networks, and engagement with the General Public.