Concr CSO and Co-Founder, Dr Uzma Asghar, was accepted to the NHS Clinical Entrepreneur Programme’s (NHS-CEP) 2022 cohort, using the opportunity to grow the VISION study through learning experiences and networking. Her involvement in the programme was recently profiled by Emily Graham of the NHS-CEP as a case study. To view the original piece on the NHS-CEP’s website, click here.
Addressing a clear and urgent need in the clinic
The VISION study, devised and led by Dr Asghar, is Concr’s first clinical validation project exploring the use of machine learning (ML) technology to predict drug responses and patient prognosis for women with early triple negative breast cancer (TNBC).
It is designed as an observational, retrospective clinical study analysing cancer tissue samples from patients with early triple negative breast cancer (TNBC) treated with neoadjuvant chemotherapy +/- immunotherapy, with the aim to define biomarkers of chemotherapy response and validation of the Concr breast cancer therapeutic response predictive algorithm.
Dr Asghar, identified the need for the VISION project, exploring the evidence that up to 50% of women diagnosed with stage 1 to 3 TNBC relapse, and approximately 40% of these women die within 5 years despite curative breast surgery(*1-3).
Concr’s translational team concluded that despite chemotherapy, surgery and radiotherapy, this treatment approach will continue to fail if there is no change, and the medicine that is routinely used in clinic for women with triple negative breast cancer is associated with multiple side effects. Additionally, Uzma observed that the NHS clinical teams did not have the technology or the infrastructure to enable quick integration of tumour genetics and the patient’s clinical data. The VISION study aims to address these challenges.
A step in the right direction, at the right time
Concr identified that change could happen as the number of cancer drugs available to clinicians for the treatment of early breast cancer has significantly increased, genomic profiling of tumours is more affordable, and the UK government recognises the positive potential impact this could have for both cancer and non-cancer patients, which has resulted in the development of genomic laboratory hubs (GLH).
Consequently, the VISION project was designed with a key objective to use ML technology to predict drug responses and patient prognosis for women with early triple negative breast cancer. The predictive algorithm –developed using Concr proprietary technology– will be applied to model cancer drug responses and patient survival (outputs) by using patient clinical information and tumour profiling (inputs). Once validated, the algorithm will continue its journey to serve as the go-to support tool for cancer specialists to make “smarter” treatment choices and provide a solution for the NHS by demonstrating how to effectively integrate genomic features and interpret their impact for patient care.
The VISION study addresses two key areas:
It identifies which cancer drugs will work and which drugs will fail before the patient has started treatment.
Provides a solution for downstream bioinformatics analyses and how to link genomic data to clinical information quickly without the need for a bioinformatician or a genomics expert anywhere in the UK or abroad.
Looking to the future
Dr Uzma and the team are working towards the successful activation of the VISION study. The initial phase includes a retrospective clinical study (non-CTIMP) to focus specifically on the early Triple Negative Breast Cancer population and will generate further proof-of-concept data for clinical applicability.
The team would like to identify clinicians in the NHS who are willing to participate in the future prospective VISION study – identify future sites and future end users, test the product, and provide feedback.
Additionally, the team would like to speak to experts from ASHN Network, Accelerated Access Collaborative and NHS to get advice on how to successfully implement Concr predictive algorithms in the clinic, and to be involved in shaping technology-driven policy specifically for cancer in the UK.
To contact Dr Asghar and the Concr translational team to explore how you can get involved in the VISION study, please get in touch.
References
Liedtke C, Mazouni C, Hess KR, et al: Response to neoadjuvant therapy and long-term survival in patients with triple-negative breast cancer. J Clin Oncol 26:1275-81, 2008.
Guarneri V, Broglio K, Kau SW, et al: Prognostic value of pathologic complete response after primary chemotherapy in relation to hormone receptor status and other factors. J Clin Oncol 24:1037-44, 2006.
Costa RLB, Gradishar WJ: Triple-Negative Breast Cancer: Current Practice and Future Directions. J Oncol Pract 13:301-303, 2017.
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