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Cambridge Cancer Genomics Ltd.. (2/28/20). "Press Release: Precision-Panc and CCG.ai Partnership". Cambridge & Glasgow.

Organisations Organisation Cambridge Cancer Genomics Ltd. (CCG.ai)
  Group Cambridge Cancer Genomics (CCG.ai) (Group)
  Organisation 2 Precision-Panc Platform (GB)
  Group University of Glasgow
Products Product OncOS platform for clinical decision support
  Product 2 artificial intelligence (AI) / machine learning
Persons Person Clifford, Harry (Cambridge Cancer Genomics 201812 CTO & Co-Founder)
  Person 2 Cassidy, John (Cambridge Cancer Genomics 201812 CEO Co-Founder)
     


Precision-Panc and Cambridge Cancer Genomics (CCG.ai) announce clinical trial partnership Partnership announced to develop AI led standardisation practices to improve data analytics, distribution and sharing in clinical trials.

PRECISION-Panc and Cambridge Cancer Genomics (CCG.ai) today announce a broad partnership to improve and standardise data analysis, distribution and sharing in platform clinical trials. CCG.ai, a startup building software for data-driven precision oncology, will partner with Precision-Panc, a UK wide network of over 20 hospitals that can offer precision medicine clinical trials to patients with pancreatic cancer.

OncOS, CCG.ai’s platform for clinical decision support, forms the basis of the piloted standardisation infrastructure and will provide insights into Precision-Panc’s large-scale, multi-centre, oncology trials. OncOS automates the analysis of cancer DNA samples and matches suitable clinical trials based on the underlying molecular features of a tumour, simplifying and streamlining data sharing to accelerate translation into the clinic.

Additionally, CCG.ai will use machine learning (ML) to help uncover complex biomarkers of response to individual, or combinations of, therapies. This builds on work published at NeurIPS 2018 and NeurIPS 2019, outlining their machine learning led advances in identifying cancer mutations and predicting tumour growth.

The partnership aims to build on and improve Precision-Panc’s adaptive clinical trials by: incorporating CCG.ai’s artificial intelligence (AI) technologies to help test and predict therapy response; and building a framework to share and distribute data and analytics. If successful, this pilot could form the framework for clinical and genomic data sharing the world over, and validation of both Precision-Panc as the gold-standard platform for clinical trials and for CCG.ai’s clinical decision support tools.?

Dr Harry Clifford, CTO of CCG.ai, who will lead the project says: “Whilst cancer is one of the greatest challenges facing healthcare systems around the world, and cancer-genomics data is hugely rich and widespread, there has been surprisingly little progress on applying AI based methods to the oncology clinical trial space. This collaboration is the first step to using AI-supported clinical decision support in cancer care and a huge step forward for the design of clinical trials.” ?

Work presented at CSBIO 2019 showcased preliminary results from the partnership, with CCG.ai presenting a new workflow for more accurate identification of cancer sub-types, and better analysis of raw data, on publically available pancreatic cancer datasets. This work will be built on by applying CCG.ai’s data analysis techniques to Precision-Panc’s rich clinical trial datasets; ultimately leading to development of AI led analytics and frameworks for use in clinical trials.?

Prof Andrew Biankin, Regius Chair of Surgery at the University of Glasgow, the Chair of the Precision-Panc and Executive Director of the International Cancer Genome Consortium (ICGC) adds: There is a real need for secure and robust, yet flexible and timely data access, with enhanced interactability for scientists and clinicians of all backgrounds. We need to build the frameworks for advanced analytics using AI – data from clinical trials will pave the way to using health care data to accelerate therapeutic development.”

Dr John Cassidy, CEO of CCG.ai says: “As next generation sequencing (NGS) becomes an ever more important part of the standard clinical workflow, ensuring data standardisation and ease of data sharing, amongst accredited researchers, is of paramount importance. We are thrilled to be working with Precision-Panc on this project, they are amongst the world leaders in platform clinical trials.”


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About Cambridge Cancer Genomics

Cambridge Cancer Genomics (CCG.ai) are on a mission to ensure that each patient has the right drug, at the right time, to beat their cancer. We build the software to enable data-driven precision oncology and systematically develop data-driven biomarkers indicative of treatment response.

We believe that increasing amounts of clinical and genomic data have the potential to transform cancer treatment, and enable oncologists to make smarter decisions about which drug to use in which circumstance.

Find out more at www.ccg.ai

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About Precision-Panc

Precision-Panc is a synergistic and dynamic platform aligning and coordinating pre-clinical discovery and clinical development. The ultimate goal is to offer every pancreatic cancer patient molecular profiling with a viable and attractive clinical trial option; to find “the trial for the patient”, rather than “the patient for the trial”; to create opportunities for scientific research that were previously not possible and enable forward and backward translation between the laboratory and the clinic.

The Precision-Panc Platform has 3 pillars: Discovery, Pre-clinical Development and Clinical Development. These constitute the essential elements for the advancement of personalised therapeutic strategies. The principle is that integrative analysis of large multidimensional datasets identifies novel pathophysiology and potential improved treatment approaches for testing in clinical trials, which in turn guide scientific strategy. Central to this strategy is a Systems Biology approach, generating rich datasets of molecular and clinical data.


Press Enquiries:

For more details, or to request an interview, please contact:

Press@CCG.ai

   
Record changed: 2020-03-02

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