When I got the news that I have become a Data Fellow, I expected the fellowship to be both serendipitous and straightforward; time to delve deeper into my research question and also a chance to meet interesting people and exchange ideas. However, it ended up being a much more meandering path – a feeling I know is shared by many other Fellows. This blog will only discuss some of the forks in the road I have taken.
My initial goal was to investigate current developments and challenges in data management within precision medicine and genomics. This particular area of health data has interested me for over a decade. One of the questions I have really been interested in is how to make genetic data and test results approachable to a wide variety of people, especially as this area of medicine is making its way into mainstream healthcare.
Genetic data and health data in general can have significant ethical implications throughout the entire process of gathering and analysing data. Some of those are fairly well known, such as lack of demographic variability within the genomic datasets or that the results of genetic analysis can affect the blood relatives of the analysed person. However, an insightful report from K. Ferryman and M. Pitcan titled Fairness in Precision Medicine highlighted a lot of the less obvious effects of precision medicine such as biases of analysis and outcomes.
Later I had a chance to have a conversation with Dr Kadija Ferryman to further discuss some of the issues mentioned in her report. We were also discussing potential solutions, such as increased collaboration between social and data scientists, as well as introduction of stronger regulatory powers.
However, reading upon the history and development of genomics, I started to notice a pattern about the people who worked in this field. As it is relatively novel and the discoveries and technological advances are very fast paced, genomics specialists have to be polymaths. Their insights, coming from a range of experience across disciplines as varied as genetics, cloud infrastructure and medical ethics, cross the established boundaries further fuelling the innovation.
That made me wonder about the influence and benefits of a broader skill set – in general the society is not encouraging about moving across disciplines, preferring specialists with long careers. However, there is no established practice to walk a more winded path of exploration and discovery; to nurture polymathy. Is there a way to make it more acceptable in a modern workplace? Would that be the road to further innovative successes?
Those were the threads of thoughts I have been following throughout the Fellowship journey – and I am grateful to the SWCTN team and the rest of the Data Fellows for encouraging me to find my own voice and follow an unexpected road into the future. I am looking forward to find how it will unfold…