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The implementation of data science in Biomedical Sciences

Lars Eijssen, Mike Gerards and David Barnett are all involved in implementing data science in the bachelor’s and master’s programmes in Biomedical Sciences. All three concur that data science is inevitable in this rapidly changing field. Students must have at least a working understanding of data science to graduate as versatile, professional biomedical scientists. The group compares the recent introduction of data science to an evolution in education. “We cannot expect the introduction to be perfect from the start; that’s not how evolution works. We are improving what works and removing what does not.” The introduction of data science began as a bottom-up initiative from the teaching staff. It was the accreditation panel and the quality cycle for the programmes that served as catalysts and sped up the process.

From Excel spreadsheets to data science

“If you can represent information as numbers in an Excel spreadsheet, it is probably data, and if you use that information to try to answer a quantitative question, it is probably data science.” Although there is still no agreed definition of data science, it is based on three pillars: statistical methods, computer coding and critical domain knowledge. “That combination is of great value for biomedical scientists who work with large data sets such as patient information, genetic sequencing, imaging and lab results. If you apply data science approaches to gain insights into biological mechanisms, and then validate the obtained results in the lab to continue with those insights, you can save a lot of time and money compared to only using lab experiments. In the early stage of the course development, we asked specialists in the field what profiles they would like to recruit, and this efficient way of working is one aspect that makes biomedical scientists with data science capabilities increasingly important.”

Future-proof programmes

Adding highly sought-after skills to a curriculum is a viable way to future-proof bachelor’s and master’s programmes. “Academic programmes age quickly. Not only is biomedical knowledge growing exponentially, its character is also changing. The field of biomedical sciences is characterised by rapid developments in the application of innovative techniques, as well as rapid evolution of knowledge. If you don’t keep adapting your educational programmes, you will fall behind, which will ultimately affect the student experience.”

“We are ensuring that graduates can understand data science and, along with it, work with data scientists. Although talking about data can spook some students, we are noticing a shift where students work with data science in their own time: some because they find it interesting, others because they know they will encounter it later in their careers. It is important to note that we are not training full-fledged data scientists, although students can choose to specialise in it later on.”

Data science will become an integral part of the curriculum. The master’s programme was revised first, as these students are closest to entering the job market. “In some specialisations and electives, we’re already using data science. This sporadic approach is now being transformed into a fundamental integration of data science in the core modules.”

Bits and bytes of the curriculum

A fundamental change to a curriculum does not come easily. “Data science was a highly debated topic among coordinators, teachers, the Education Programme Committee and management teams.” The last accreditation panel concluded that data science is integral to biomedical sciences and advocated for both the bachelor’s and master’s programmes to offer more thorough coverage of this topic within the curriculum. “The report of the accreditation panel acted as a catalyst. We now have a strong position in the educational landscape, because there are not many biomedical sciences programmes in the Netherlands that are integrating data science as extensively as we are in Maastricht.”

 

The introduction of data science

How do you start introducing a new competency into an existing curriculum? “The first question that came to mind was whether it was going to be a separate track or integrated into the courses. The emphasis of Biomedical Sciences is on building bridges to real-life practice, so we opted for integration in the courses. This resembles the reality of biomedical sciences the most.” Data science will be integrated into the core bachelor’s curriculum next academic year. “It’s going to be a fundamental base upon which students can further build. This will involve both conceptual ideas and practical skills.”

FHML - Eijssen,Gerards en Barnett

Quality assurance in education

Science is continuously evolving, and education must anticipate the future challenges of the field. This is embedded in the quality assurance cycle, in which staff and students examine the curricula critically and extensively. “If colleagues and students keep talking to each other about what they think future scientists need, and there are platforms in place to support those suggestions, our education will continue to maintain the high standard of quality it has today.”

Text: Ruben Beeckman

Photography: Jonathan Vos

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