By Dr. Angela Davies

Developing a New Profession: Introducing the Clinical Bioinformatician

The development of high throughput next generation sequencing (NGS) technologies has revolutionised the field of genetic testing and promises to have similar impact in other medical fields such as personalised medicine and pathology. Large scale sequencing projects such as England’s 100,000 Genomes project are building capacity within the NHS to pave the way for whole genome sequencing of patients, allowing a much more personalised approach to the delivery of patient care.

Clinical Bioinformaticians are responsible for converting the data from such sequencing initiatives into something more meaningful that can be interpreted at a clinical level. They will work closely as part of a multidisciplinary team that will work to determine the clinical relevance of variation found within the genome.

Their role will entail analysing data from gene panels that may contain hundreds of genes, whole exomes and will soon be required to analyse whole genomes. These tasks require Bioinformaticians to develop bioinformatics pipelines (or workflows) that often include multiple algorithms, databases and interfaces, that need to work together to ensure the best possible analysis is undertaken.

This will involve tools to check the quality of sequencing data in the raw Fastq file generated by the sequencing machine; align the millions of sequencing reads to a reference genome; call variants and filter them, removing any known to be benign or cause synonymous changes; annotate variants, associating each one with a rich set of metadata and finally prioritisation to generate a list of candidate variants which are potentially disease causing (1).

The results of a bioinformatics pipeline can be greatly influenced by the choice of algorithms and input parameters thereby requiring full validation with a test set when a new pipeline is created or any components of the pipeline are changed (2). The huge amounts of data and metadata generated by NGS will pose new challenges for data management in healthcare, and the large number of variants being generated will require a suitable infrastructure capable of sharing this data with other clinical laboratories in a secure manner to enable maximum patient benefit.

In order to fully realise the potential of NGS, healthcare needs to overcome a serious shortage of the bioinformatic skills required to analyse, integrate and manage the large data sets generated by this approach. It is concomitantly well acknowledged that there are skills shortages in bioinformatics and computational biology within the biosciences and the availability of those with suitable skills to train and educate in this area is also limited (3). The situation is more acute when considering the transition into the clinic and the specialist skills required for the analysis of genomic data in a clinical setting.

To ensure that the NHS was well placed to take advantage of this genomic revolution Health Education England developed a portfolio of genomics Scientist Training Programmes (STPs) covering many areas of genomics including the Clinical Sciences (Bioinformatics) programme, designed to develop the Clinical Bioinformatician profession, under the umbrella of Modernising Scientific Careers (4).

This programme consists of a three-year training programme, undertaken within a clinical genetics laboratory in the NHS, trainees study part-time for a Master’s programme delivered by The University of Manchester integrated within their training. The first graduates of the Clinical Sciences (Bioinformatics) Genomics STP graduated in summer 2016, all securing roles within clinical genetics laboratories across the UK. The career pathway can be extended through the Higher Specialist Scientific Training programme, completion of which can allow a Clinical Bioinformatician to apply for a Consultant Clinical Scientist position.

As a profession Clinical Bioinformatics is still in its infancy and therefore is largely unknown to many other healthcare professionals and certainly to the wider public.  Therefore as educators and close collaborators of Clinical Bioinformaticians across the UK we began a project to create an open educational resource (OER) to introduce this new profession and highlight its importance. In order to extend our reach globally we embarked on the development of a free Massive Online Open Course (MOOC): Clinical Bioinformatics: Unlocking genomics in healthcare.

MOOCs came into existence around a decade ago with George Siemens and Stephen Downes opening up the first course of this kind to 2,300 learners on connectivism and connective knowledge (5). The aim of MOOCs initially was altruistic, aiming to widen participation in higher education to the masses, importantly for free. The number of universities offering MOOCs expanded rapidly and the number of learners increased dramatically,  in tandem, as have the companies providing the platforms to host the MOOCs, including Udacity, edEx, Coursera and FutureLearn to name a few. Some universities displayed caution at treading this path, perhaps concerned about reputational impact, potential or devaluing of programmes. Yet in 2018 the MOOC concept continues to flourish, and with many different models of participation now in existence it has become a source of notable income for some institutions.

The MOOC’s inception and development took an intense six months of work, with the academic team (myself, Prof. Andy Brass, Kieran O’Malley and Learning Technologist Fran Hooley) needing to develop new skills that we had not anticipated, including: writing and learning scripts; talking to camera (sometimes unscripted!) and working with a media production team, some of the results of which can be viewed in our MOOC trailer. The MOOC was launched in June 2016, with more than 5,000 learners joining. In the four iterations delivered since, nearly 13,000 participants have been reached.

Developing a New Profession: Introducing the Clinical Bioinformatician

Our MOOC is a 5 week long course, with approximately 2-3 hours of learning per week covering:  genomic medicine and learning where clinical bioinformatics fits within this area of healthcare in week 1; in week two introducing variation in the genome, what it is, its affects, and how we can analyse and classify it within a clinical setting; in week 3 drilling into the detail of interpreting clinical variants; in week 4 focussing on the ethical considerations and consequences of generating huge quantities of genomic patient data and in week 5 culminating in reflection on a final case study.

Futurelearn courses embrace a social constructivist approach to learning, the social discourse encouraged through the discussion topics allows the exchange of ideas thus allowing knowledge to evolve that is shared by participants in the course (6). From a pedagogical perspective specialist subject matter content is interspersed with discussion areas which are monitored by expert facilitators (all with expertise as Clinical Bioinformaticians themselves) and ourselves as the educational leads. Within this MOOC, case studies, video content and articles are interspersed with quizzes, polls and discussion topics to encourage debate and discussion amongst learners. Facilitator and educator engagement and participation is certainly important to the learners and our experience has been that MOOC learners engage better in discussions when educator and facilitator presence is high – which of course adds to the academic pressure of running a MOOC.

Martin Weller – author of ‘The Ed Techie’ blog and advocate of open educational resources – has mused on the concept of positive openness, the issue being that making our educational materials completely open does not necessarily lead to equity of access for all because learners learn in different ways and require differing levels of support to do so. Therefore, not only do we need to make our content free and open to all in the context of an OER  but we also need to support and nurture learners within their learning journey to support different learning styles and levels, which of course does not come for free.

This demand from the learners does develop us as educators, ensuring we keep up to speed with updates in the field and simultaneously developing our public and patient engagement skills. The MOOC has provided a good forum to explore how our science interacts with the wider community – for example learners who are carers for people with rare genetic conditions have joined some of our courses. Reflection from this community brings the science to life allowing learners to realise how essentially a non-patient facing profession is actually contributing to improve outcomes for patients.

Our learner demographic (below) has been largely centred to the UK, which is indicative of the fact that FutureLearn is affiliated to the UK-based Open University and also the course has been heavily promoted through Health Education England and UK clinical genetics laboratories. However, there were some surprises with noticeably high numbers of learners from Arab countries including Egypt and Saudi Arabia.

Developing a New Profession: Introducing the Clinical Bioinformatician

Worldwide distribution of MOOC participants over 5 iterations of the course.

Feedback from the MOOC has been overwhelmingly positive as can be seen below, for many learners it was their first experience of engaging with an online course, yet many learners commented that with support from the facilitators and educators they were able to navigate their way through some quite complex terminology and concepts:

Final week feedback, run March 2017:

  • “Thank you to the mentors and fellow online students for your amazing comments on different topics that have been covered on this course. This was my first online course and trust me, it’s better than I expected.
    Thank you again.”
  • “Really enjoyed being part of an online community. Loved recognising names and hope F2F might ever happen! Felt at home online, being myself and loved the mentors encouragement. Thanks to all.”
  • “This has been an amazing course, which has challanged my grey matter a lot! I feel I do know the learning objectives which is great. This course followed on from the WGS course so I feel the two were complementary, as I realised how the data was produced and what the pros and cons were. This is an exciting and developing science which I think will grow into a useful tool to help people live healthy lives. I particularly liked learning about the computing power needed and the all the software out there.” 
  • “Thank you to all the people involved and especially the mentors who have commented and helped me.”

At Manchester the experience of developing and delivering this MOOC has been an enriching one, allowing us to develop innovative pedagogy, research ideas and projects and also to widen participation in genomic education, which has in turn added value to our institution (7). MOOCs generate inordinate amounts of data, but pre-course survey participant data suggests that we have certainly made a difference in health and social care, but also with high numbers participating with a background in science and pharmaceuticals and also teaching and education.

Finally, it has allowed us to test new markets and has enabled the launch of a new Distance-Learning course in Clinical Bioinformatics in 2018 – watch this space!

 

Dr. Angela Davies 
Senior Lecturer in Clinical Bioinformatics and Genomics, Programme Director: Master’s Degree in Clinical Sciences (Bioinformatics), 
Univerisity of Manchester.

 


References 

 

  1. Lohmann K, Klein C. Next Generation Sequencing and the Future of Genetic Diagnosis. Neurotherapeutics. 2014;11(4):699-707.
  2. Roy S, Coldren C, Karunamurthy A, Kip NS, Klee EW, Lincoln SE, et al. Standards and Guidelines for Validating Next-Generation Sequencing Bioinformatics Pipelines: A Joint Recommendation of the Association for Molecular Pathology and the College of American Pathologists. The Journal of Molecular Diagnostics. 2018;20(1):4-27.
  3. Attwood TK, Blackford S, Brazas MD, Davies A, Schneider MV. A global perspective on evolving bioinformatics and data science training needs. Briefings in Bioinformatics. 2017:bbx100-bbx.
  4. Department of Health. Modernising Scientific Careers: The UK Way Forward 2010 Available from: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/138326/dh_113990.pdf.
  5. Siemens SDaG. MOOC: Connectivism and Connective Knowledge 2011. Available from: http://cck11.mooc.ca/index.html.
  6. Ferguson R, Sharples M. Innovative Pedagogy at Massive Scale: Teaching and Learning in MOOCs. In: Rensing C, de Freitas S, Ley T, Muñoz-Merino PJ, editors. Open Learning and Teaching in Educational Communities: 9th European Conference on Technology Enhanced Learning, EC-TEL 2014, Graz, Austria, September 16-19, 2014, Proceedings. Cham: Springer International Publishing; 2014. p. 98-111.
  7. Davies A. Do MOOCs generate return on investment? : Times Higher Education; 2017. Available from: https://www.timeshighereducation.com/blog/do-moocs-generate-return-investment.