• Partnership aims to deliver the most comprehensive, cost effective and high throughput cancer sequencing and interpretation service in Europe, to enable improved cancer patient management, treatment, and monitoring
  • High throughput precision oncology will provide the scale required to address the backlog of patient samples due to the COVID19 crisis

CAMBRIDGE (UK), L’AQUILA (Italy) and BIRMINGHAM (UK), 15 June 2020: Dante Labs, a pioneer and leader in genomic testing, Cambridge Cancer Genomics (CCG.ai), a software developer specialising in data-driven precision oncology, and Nonacus, a provider of genetic testing products for precision medicine and liquid biopsy, today announced that they have signed a collaboration agreement.

The partnership aims to build the most comprehensive and patient-centric tumour profiling service enabling improved cancer patient management, treatment and monitoring. By combining Dante Labs’ experience and capacity in delivering a sequencing service for both solid tumour and cell free circulating tumour DNA from liquid biopsies, Nonacus’ sensitive targeted pan-cancer NGS libraries, and CCG.ai’s industry leading AI powered software platform, OncOS, the companies will enable precision oncology at scale.

Improving outcomes for cancer patients means ensuring they have the right drug, at the right time to beat their cancer. This means understanding the molecular profile of the individual cancer and using that data to recommend treatments or clinical trials. Oncologists and clinical researchers will be able to send samples for processing to Dante Labs, who will use library preparation kits from Nonacus and software from CCG.ai to create a sample to report solution. If there are actionable mutations, the report will recommend the right treatments for those mutations, if there are novel or unactionable mutations, the software will also be able to match possible clinical trials.

Chris Sale, CEO of Nonacus, said: “Long turn-around time and lack of clinically oriented analysis are the main obstacles to fully deliver the potential of cancer genomics to patients. This partnership will provide the flexibility and accuracy that oncology professionals need to integrate cancer genomics into the care of their patients. The COVID pandemic has increased the backlog of genetic testing for cancer, potentially leaving many suspected cancers unconfirmed and treatments delayed. Dante Labs are one of the biggest clinical sequencing hub in Europe able to process large numbers of samples in high throughput. It is our hope that by combining AI software from CCG.ai and our library preparation kits, together we will be able to process samples and provide bioinformatic analysis critical to determining the best treatment path for patients. Only with this comprehensive content at scale will it be possible to address the COVID backlog.”

Nirmesh Patel, CSO at Cambridge Cancer Genomics, said“With cancer being one of the greatest healthcare challenges we are facing, this partnership opens the door to democratizing access to data-driven cancer treatment. Combining our industry leading precision oncology platform with Nonacus’ precise NGS solutions and Dante Labs’ fast and efficient NGS services provides customers with the ability to perform precision oncology at scale. The combined solution will enable oncologists to precisely and comprehensively profile a patient’s tumor and ultimately improve outcomes.”

Gianmarco Contino, Senior Lecturer (Associate Professor) of Cancer Genomic Medicine, said“It is the beginning of a revolution in cancer treatment. Until now we have been treating cancer by tissue of origin. But each cancer harbors a unique combination of mutation which makes it effectively a ‘rare’ disease. Therefore the right approach should be to start from the mutations and look for the right drugs. There is a great deal we can learn from sequencing cancer genomes: not only what therapy is going to be more effective but also safer and less toxic. We are now at a stage where a patient can benefit directly from this knowledge. Machine learning is helping us to unleash the potential of information hidden in the complexity of the genome.”