Genomics and the NHS Clinic

July 1, 2014 | Rodrigo

In 2012, the Human Genomics Strategy Group had already highlighted the need to develop a workforce skilled in genomics in the NHS, the changing R&D models in the domain and the establishment of bioinformatics hubs across the UK. Later this week, at the NHS England board, Tim Kelsey and Sir Bruce Keogh will present a paper on “Genomics: NHS Preparedness for Delivery of the 100,000 Genome Project”. This sets out a couple of key demands on the NHS – the establishment of “NHS Genomic Medicine Centres” and assessments of the availability of data from the NHS into the Genomics England programme. Genomics England’s desired outcomes include a genomics service ready for adoption by the NHS, delivered through making whole genome sequencing ‘faster, reliable, low cost with useful results’.

Our work for Genomics England prioritises integration with the clinic. When we looked at the challenges and unmet needs in the area, it was clear that reaching the clinician desktop was key. The other challenges are related – how to facilitate the delivery of clinically relevant annotation pipelines (“industrialisation”) and how to make sure that the evidence base for annotation is reliable.

Offering a genomic medicine service in the NHS will have to take into account both the clinical and organisational features of the UK health environment. One difference with other models may be in the diversity and depth of annotation sought. Genomics England has developed the “Genomics England Clinical Interpretation Partnership” (GECIP) to add value to funding initiatives in the area and offer ways for the NHS community to engage with the broader initiative.

Annotation services take the output of DNA sequencing and extract the relevant data points for understanding a person’s health. Biological and medical know-how are applied to maximise the utility of that information. Ultimately, this information is prioritised to deliver something clinically relevant, or stored in a database for ongoing research. Our view at Aridhia is that there is enormous potential to be clinically led, given the variety of diseases and conditions that require specialist interpretation or algorithms. We don’t believe one size fits all in clinical informatics, especially when it comes to integrating with operational electronic medical records and clinician desktops, but we will provide patterns and accelerators for reaching the end user.

There is an increasing amount of clinical data available in digital form, but the state of the art is that datasets are not standardised, and often not available in standard APIs. For the industrialisation agenda, that increases the cost and the time to deployment. We welcome the inclusion of a “Data Maturity Assessment” in the NHS deliverables, with an accompanying IT investment to deliver the best data possible to the Genomics England programme. The outcomes depend on understanding clinical and genomic data, how they fit together, and how to set up the information governance for such data flows.

We are developing a platform that will make it easier for start ups, research groups and clinical consortia to develop their own annotation services, validate them at scale with Genomics England or Stratified Medicine Scotland. This platform builds on the computing services that underpin our AnalytiXagility service. For those wanting to take an annotation service ‘to market’ we will offer a process for qualifying and improving the implementation, through better programming resources (APIs) to genomic and clinical, world class content and the ability to optimise for different computing and storage strategies. At the same time, we are building on our experience of developing clinical applications for the NHS to offer building blocks for offering annotation to the ‘last mile’, whether that’s to a specialist clinician desktop, a clinical genetics lab or ultimately patients and their families. As a development partner, we’d expect to help innovators to deliver validated products in an increasingly regulated environment.

Aligned with the NHS deliverable to be operationally prepared for routine whole genome sequencing, we are interviewing practitioners in the field, to capture what the level of knowledge is, where expectations lie, and how to measure ‘good’ in annotation services. This information will be crucial to establishing how the NHS will integrate the emerging genomic services into existing structures such as clinical laboratories, the UK genetic testing network, education and genetic counselling services. By building these quality measures directly into our industrialisation process, we expect to narrow the gap between genomic and medicine.

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rodrigo

Chief Technology Officer

Rodrigo Barnes is CTO at Aridhia, which he joined in 2007. He is an R&D software engineer and with a mathematical background and has designed and developed analytical and data management applications in a number of healthcare, life sciences and knowledge management start-ups.

He is skilled at developing new approaches to healthcare information problems. Rodrigo has been instrumental in designing Aridhia’s approach to big data within healthcare and to the development of our collaborative analytics service. He is now responsible for technical and product strategy and takes a lead in Aridhia’s approach to precision medicine. He is currently working on Aridhia’s platform for genomics, including executing evaluating annotation pipelines for clinical use.

Since 2007 Rodrigo has led a range of programmes, from core technical design, to on-the-ground delivery of collaborative projects involving multiple academic and healthcare organisations, including:

  • Online dynamic anonymisation of patient records
  • Patient pathway analysis for NHS Referral to Treatment analysis & reporting
  • Real-time infection control & bed management information
  • Clinical analytics dashboards
  • A platform for chronic disease management and professional education of clinical staff
  • The collaborative analytics service, AnalytiXagility
  • Tools to search, integrate and process data with controlled vocabularies and clinical ontologies

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