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How A Leading Cancer Research Facility Pioneered Biomarker Technology to Personalise Patient Treatments Pathways

OCB’s mission is to develop precision oncology diagnostic technology with the aim of providing patients and clinicians with tools to personalise cancer treatment. Thereby improving patient outcomes and driving cost savings within healthcare systems. The technology OCB has developed allows clinicians to better understand an individual patient’s cancer and tailor treatment to that person.

As pioneers of precision oncology, OCB uses an array of technologies to develop precision diagnostic technologies; from molecular techniques to cytopathology. Recent developments in the field of machine learning has allowed OCB to explore ways of interrogating traditional histopathology images in order to deliver actionable information to the clinic. This emerging sector termed digital or computational pathology promises to revolutionise cancer care but brings with it a unique set of technology requirements and challenges.

OCB has partnered with CSI to address its technology requirements, ensuring it has access to the most appropriate server and storage architecture to run its data and computationally intensive workloads, enabling OCB to deliver digital pathology based precision diagnostics to the clinic.

Towards A Personalised Treatment of Cancer

Cancer is a complex, heterogeneous disease driven by multiple, often interrelated factors acting at the genetic, epigenetic, transcriptional and translated protein level. The inherent complexity of the factors driving the disease dictates that different cancers, with different driving factors will respond to different treatments and therapies.

Until recently, very few tools have been available to clinicians to allow them to interrogate and characterise different factors driving a given cancer, this has necessitated a largely empirical approach to treatment, i.e. by means of observation or experience rather than theory or pure logic.

The concept of precision oncology is centred on the principle of patient stratification. In practical terms, this means the ability to characterise clinically significant subtypes of cancer and thus tailor treatment to the individual for the best outcomes. In broad terms, it aims to advance the clinical conversation on from ‘how do we best treat cancer?’ towards ‘how do we best treat this individual patient’s cancer?’.

OCB designs, builds and deploys the next generation of precision oncology diagnostic technology which allows clinicians to stratify patent groups that traditionally would have been treated empirically, thus allowing its clients to deliver the benefits of precision oncology to their patients.








Digital Pathology & OCB

Digital or computational pathology is the transformation of traditional pathology services using technology; it has the potential, as OCB has identified, to positively impact patient care, making stratification possible.

The work OCB has undertaken with CSI is aimed at enabling the stratification of bowel cancer patients. Currently, the majority of mid to late stage bowel cancer patients (Stage IIb disease and higher) are offered what is known as adjuvant chemotherapy. This is chemotherapy that is given after surgery and has been shown to improve 5-year survival rates of bowel cancer patients by up to 8% compared to surgery alone. There are however, disadvantages to this approach, principally clinicians end up giving a lot of people adjuvant chemotherapy in order help a relatively small number. Conversely in means that a lot of people are given chemotherapy who do not benefit from it but are still at risk significant side effects. The question that the technology that OCB is developing with the help of CSI is seeking to address is;

‘Can we identify and treat the 8% of patients who will benefit from adjuvant chemotherapy and spare those who will not, from unnecessary treatment.’

Under the Scope – How the Technology Works

As part of the normal treatment for bowel cancer, after surgery, a sample of the patient’s tumour is processed in the pathology laboratory of the hospital and examined under a microscope by a pathologist. In addition to the pathologist’s examination, OCB’s technology takes images of these same tumour samples and subjects them to machine learning based image analysis algorithms. These algorithms identify features in the tumour microenvironment indicating whether the tumour is an aggressive type and therefore more likely to recur. Patients whose tumours have these high-risk features are likely to benefit from adjuvant chemotherapy i.e. they are likely to be one of the 8%.

CSI provided OCB with a high-performance platform designed for AI deep learning in an Infrastructure as a Service (IaaS) model based in the CSI PowerCloud.

OCB’s AI initiatives are supported by an IBM Power System AC922 combining 40 POWER CPUs with four NVIDIA Tesla GPUs. NVLINK2 technology provides direct CPU-GPU communications delivering the high performance required. IBM V7000 delivers 14TB of SAN-attached storage for datasets and AI models.

The IBM Power9 server (AC922) also offers Large Model Support where AI models can be trained on images larger than the memory available on the GPU by using system memory – this allows high-definition images to be used.

Deep learning model training is compute-heavy, but OCB is now able to take advantage of the AC922’s distributed training feature which allows jobs to be broken down and processed in parallel over a cluster of GPUs.




A group of cutting-edge oncology researchers wanted to take advantage of the latest artificial intelligence models to develop tools which enable a more tailored or individualised approach to cancer therapy.


Creating Cost-Efficiencies in Patient Care

When commercialising healthcare products in Europe, desirable treatments should demonstrate both real-life clinical impact (improving patient care, for example) and create cost-efficiency. Within the familiar European markets, technological innovation is being explored to save money in healthcare settings, especially where budgets are notoriously restricted.

A close health-economic evaluation of our solution shows savings all-the-way down the value chain. Early, expediated cancer screenings help doctors inform decisions regarding patient care, removing clinical guesswork, administrative burdens, and resource wastage.

Our solution and team of experts supports OCB by:

  • Reducing overheads by streamlining processing times
  • Simplifying treatment pathways and the workflows of clinicians
  • Removing barriers to deploying treatments in regulated markets
  • Reducing clinical errors
  • Freeing resources
  • Refocusing the time of clinicians to supervise patient care
  • Improving turn around times
  • Providing technical skills to drive efficiencies from the IT environment.

In highly-regulated, global healthcare markets, patient care is the driving impetus for innovation, but what is emerging now is a scalable, cost-effective form of digital pathology.

About our client

OCB was spun out from the University of Oxford in 2012. Oxford Cancer Biomarkers (OCB) is a world-class team led by Professor David Kerr, delivering cutting edge precision oncology tools to clinicians worldwide.

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