Skip to main content

New research collaboration to advance prostate cancer diagnostics

Following MedCity’s Collaborate to Innovate Speed networking event held on 25 April 2022, Curenetics – an innovative AI Diagnostics company – and Prof Yong-Jie Lu – a leading expert in molecular oncology – and his team at Queen Mary University of London (QMUL) signed a Confidential Disclosure Agreement (CDA). This has allowed them to share data in order for Curenetics to carry out preliminary analyses on prostate cancer data using Curenetics AI predictive models.

The collaboration focuses on working to improve the classification of benign vs malignant prostate patients, using a subtype of immune cells. Combining novel work carried out by Prof Lu’s lab and Curenetics’ cancer-based AI modelling, the collaboration aims to improve the standard of care for prostate cancer diagnosis.

We spoke to Curenetics founder Sola Adeleke and QMUL’s Prof Lu to find out more.

Q: Please explain Curenetics core technology and what problem it aims to solve?

Sola: We are a med-tech company, with a very strong background in AI, cancer genomics, immunology and clinical oncology. We leverage our know-how across these fields to find deep insights into complex, multi-modal data. Our AI platform is able to find insights or signatures that could for instance, (i) diagnose common cancers using novel biomarkers, (ii) predict response to immunotherapy, (iii) predict disease recurrence and (iv) also be used for disease prognostication.

Q: Prof Lu, what is your research focus?

Prof Lu: Prostate cancer is the most common cancer in men in the industrialised world. Approximately 48,000 new cases and 12,000 deaths occur annually in the UK. The current method for early detection is a prostate specific antigen (PSA) test from a blood sample. However, in around half of cases the test does not accurately diagnose clinically significant prostate cancer, leading to invasive, unnecessary biopsies. My work concentrates on identifying biomarkers that will enable more accurate early diagnosis.

Q: What was the catalyst for the collaboration?

Sola: Finding the right academic to collaborate with can be challenging. Academics are very busy teaching and conducting research, so their time is quite limited. Being able to navigate through a long list of academics and identifying one who might be interested and have an overlapping interest with the company is key. MedCity has long-standing relationships with many academic institutions and also individual academics. They are able to sign-post companies to the right people within a very complex academic ecosystem. The Collaborate to Innovate event is an example of how MedCity curates sign-posting opportunities, and it turned out to be the catalyst for this new collaboration.

Q: How did the collaboration develop?

Sola: We met Prof Lu through the speed networking sessions that were part of the event. Although we initially only had four minutes to introduce ourselves, we immediately thought that Prof Lu was a great fit for Curenetics because his lab is generating high-quality genomic data from experiments for prostate cancer diagnosis and risk stratification. This large, complex, genomic data lends itself well to AI tools, which could be used to find novel biomarkers.

Prof Lu: During our conversation at the event, it quickly became clear that we were working in complementary areas. Curenetics has expertise in bioinformatics analysis of large amounts of genetic and clinical data from clinical samples, and through my research in developing biomarkers I have generated a large amount of molecular and genetic data from clinical samples with associated clinical data.

Q: What is the scope of the collaboration?

Sola: Following the speed networking event, we have signed a CDA and data has been transferred to us to carry out some preliminary analyses on prostate cancer data using our AI predictive models. We are working to improve the classification of benign vs malignant prostate patients using a subtype of immune cells. This is novel work carried out by Prof Liu’s lab. We are hoping we can use our cancer-based AI modelling to improve prostate cancer diagnosis compared with what is currently achieved in their lab.

Q: What results do you hope to achieve?

Sola: A better understanding of patterns or gene expression profiles within subset of immune cells which, if successful, could potentially transform how we diagnose patients with prostate cancer.

If these proof-of-concept studies are successful, we intend to validate our findings in clinical trials. The final product will be an AI-driven, novel biomarker assay for prostate cancer.

Prof Lu: As Sola explained, we hope to identify prostate cancer diagnostic biomarkers using Curenetics bioinformatics analysis of our data. The next step will be further validation in a clinical setting for future clinical use.

Curenetics is part of the Collaborate to Innovate: London Diagnostics cohort. The programme is delivered with our partners at: UCL, Imperial College London, King’s College London, Queen Mary University of London, Roche, Cancer Research UK, NHS, BIVDA, NIHR London In Vitro Diagnostics Cooperative, Imperial College Health Partners, King’s Health Partners, UCL Partners.

Future opportunities

To discuss partnering opportunities on future programmes, please contact our Partnerships and Programmes Lead, Rikesh Patel at


Sola is an NHS England Clinical Entrepreneur and NIHR Academic Clinical Fellow in Clinical Oncology. He completed a PhD in cancer magnetic resonance imaging at University College London. His research was focused on prostate cancer and analysing multi-centre data to determine accuracy of PET CT versus WB-MRI for patients with prostate cancer. He founded Curenetics in 2018 and has won numerous grant awards. They are currently collaborating with a number of universities/NHS trusts on various AI projects. He is an avid golfer.


Prof Yong-Jie Lu is Professor of Molecular Oncology at the Centre for Cancer Biomarkers & Biotherapeutics, Barts Cancer Institute, Queen Mary University of London. He joined QMUL in 2003, after spending eight years as a researcher at The Institute of Cancer Research in Sutton, South London. He studied at Henan Medical University and Harbin Medical University, before completing his PhD in Pathophysiology at the Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College (PUMC), Beijing.

Contact us