WILD-Imaging: platform technology for stain free cancer diagnosis

Timely cancer diagnosis is critical for improving survival, yet pathology services are facing unprecedented pressure. Across the UK, a severe shortage of pathologists has led to cancer diagnostic backlogs stretching up to four months, delaying treatment and directly affecting patient outcomes. Every year, hospitals process over one billion pathology tests, costing £2.2 billion, with a further £27 million spent on outsourcing simply to keep up. In response, the NHS has introduced the Faster Diagnosis Standard, aiming for a 28‑day diagnosis turnaround, and is investing in AI tools such as Annalise.ai and Paige PanCancer to help speed up and digitise diagnostics. However, these systems still depend on H&E‑stained slides, a 130‑year‑old method that is slow, labour‑intensive, and varies from lab to lab, making it difficult for AI to work reliably and consistently.

Our solution is WILD-Imaging, a new technology we developed that uses a simple LED‑powered light guide, similar to the principle behind fibre‑optic cables. This robust and cost‑effective component has been adapted into a microscope that can capture fast, high‑quality images without the expense or complexity of laser‑based systems.

WILD-Imaging transforms the diagnostic process by producing clear images of completely unstained tissue within minutes. Instead of relying on dyes, it detects natural signals already present in the tissue. Early testing in lung cancer samples shows that a WILD-Imaging device, supported by a basic AI tool, can identify tumour areas with around 90% accuracy, showing strong potential as an early triage method. Because WILD fits seamlessly into existing laboratory workflows and requires no changes to sample preparation, it can be easily adopted in NHS settings. It is also suitable for multiple cancer types, offering the potential for a universal, stain‑free diagnostic platform.

Our goal is to introduce WILD-Imaging as a companion tool that supports pathologists by providing early insights even before conventional staining. With support from the C4T funding, we will expand testing to include breast and prostate cancers, adapt the analysis tool for multiple tissue types, and prepare for broader clinical deployment. Ultimately, WILD-Imaging aims to speed up diagnosis, reduce backlogs, and ensure that patients receive quicker, more accurate information about their care.

MyExoFat: Harnessing patient-derived micro-fragmented adipose tissue exosomes as delivery vehicles for glioblastoma

Glioblastoma is the most aggressive type of brain tumour in adults. Even with surgery, radiotherapy and chemotherapy, most patients survive only around 12–18 months after diagnosis. A major reason treatment is so challenging is the blood-brain barrier, a protective “gatekeeper” that controls what can move from the blood into the brain. While it protects the brain, it also blocks many treatments from reaching the tumour in the amounts needed to work well.

This project aims to improve drug delivery to brain tumours using tiny natural carriers called exosomes. Exosomes are very small particles released by cells that act like delivery packages. We will isolate exosomes from micro-fragmented adipose tissue, a patient’s own fat processed into very small pieces using a clinically approved system. The fat is gently washed and filtered in a clean, closed device without harsh chemicals, keeping it close to its natural state and providing a rich source of exosomes.

Because these exosomes are derived from the patient, they are expected to be well-tolerated and less likely to trigger immune reactions. We will test them in well-established laboratory systems that reliably mimic key features of the human body, including a standard blood-brain barrier model where human brain blood vessel cells are grown on a thin support to separate a “blood side” from a “brain side.” This allows us to measure whether the exosomes can cross the barrier. We will also test uptake in glioblastoma cells and, where possible, tumour samples donated for research.

To assess performance, we will compare fat-derived exosomes with other advanced delivery systems, such as lipid nanoparticles already used in medicine. Our overall aim is to create a delivery system that can be used alongside the current standard of care, reducing side effects, improving treatment outcomes, and lowering the risk of the tumour coming back.

A Rapid Pan-Bacteria Diagnostic Assay for use in Human Sterile Fluids

Sepsis is a life-threatening condition responsible for around 11 million deaths each year worldwide. Rapid and accurate identification of bacterial infection is essential to improve survival. Standard blood culture tests can take three to five days to provide results and often fail to detect bacteria that grow poorly under laboratory conditions. In the UK alone, around three million blood cultures are performed annually, particularly in critical care settings, and many return negative results. Because clinicians cannot afford to delay treatment, patients are frequently given broad-spectrum antibiotics before an infection is confirmed. This leads to unnecessary hospital stays, excessive healthcare costs, and widespread antibiotic overuse. Around one in five hospital patients experience harmful side effects from antibiotics, and overuse contributes to the growing global problem of antimicrobial resistance.

We have developed a rapid molecular test that can detect DNA from a wide range of bacterial species in minutes to hours. The assay is highly specific, low-cost, and compatible with existing laboratory equipment. We will use C4T funding to adapt this test for use with real clinical samples, ensuring it works reliably in complex biological material. This work will generate essential data to support future testing within NHS diagnostic pathways, with the aim of improving clinical decision-making and patient outcomes.

Evaluating the effects of cryopreservation of primed mesenchymal stem cells on their regenerative and therapeutic potentials in stroke

The brain is essential for all of our normal functions, but damage to the brain that occurs during stroke results in disability and sometimes death. Inflammation is an important defence mechanism of the body to injury or infection, and after stroke, inflammation in the brain has been shown to be very damaging. Stem cells are a type of cells in the body that are important in repairing damaged tissues. A type of adult stem cell, called mesenchymal stem cells (MSCs), have the potential to protect against inflammation and improve recovery after stroke. Our previous work found that we can modify or “prime” MSCs by growing them under different conditions to make them better at blocking damaging inflammation and potentially repairing the brain. However, for these to be used as a therapy, they must be frozen and stored, and “on the shelf” ready for rapid administration. This research evaluates if primed MSCs retain their superior anti-inflammatory and neuroprotective abilities after being frozen and thawed. Establishing this protocol is a vital step toward providing a rapid, effective, and accessible stem cell therapy for stroke patients.

Improving life after radiotherapy for cancer patients: The Manchester Toolkit

Radiotherapy uses high-energy beams to destroy cancer cells and is used to treat around half of all patients with cancer. Modern radiotherapy is very precise, but some patients still experience side effects that can affect everyday life. As more people survive cancer, understanding how radiation to different parts of the body influences both survival and quality of life is more important than ever.

Researchers in Manchester have developed software that analyses 3D medical images from patients who have received radiotherapy. The software maps where radiation was delivered and links this to detailed information about what happened to patients afterwards. By studying large numbers of patients, it can identify critical areas within organs that are important for survival or linked to side effects. This method has already led to important discoveries. For example, identifying that radiation dose to specific structures within the heart can affect survival in patients with lung cancer. These findings are now changing how patients are treated, as we can adjust the beams to spare those sensitive structures and hopefully improve outcomes for patients.

This project will build on that success. As the amount and complexity of patient data continue to grow, the software must evolve to better analyse side effects that affect quality of life. It will be expanded to handle more complex datasets, including information collected over time and a wider range of clinical outcomes. It will also use new advanced methods to help untangle the effects of radiation from other factors that might influence how a patient responds to treatment, such as age or other medical conditions. Importantly, it will also support researchers from different hospitals to analyse data in a consistent and robust way, so results are reliable and easier to compare, making improvements in radiotherapy available to all patients.

In the long term, this work will help make radiotherapy safer and more effective. By understanding more about how radiation dose relates to side effects, treatments can be planned to improve survival while reducing side-effects – helping more people not only survive cancer but live longer and healthier lives after treatment.