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Where Treatments Meet Genetics: Making Stratified Medicine a Reality in Scotland

Earlier this week, we announced our part in the Stratified Medicine Scotland Innovation Centre (SMS-IC), along with the healthcare and clinical research community in Scotland, and our industrial partner in this venture, Life Technologies. There’s quite a bit to unpack in that sentence, and the hardest part of that is probably “stratified medicine” itself. As an informatics specialist it’s not familiar territory, and that will be true for many readers.


It may surprise a lot of us to be told that stratified or personalised medicine means, essentially, targeting the right treatment at the right person, to get better outcomes. I tend to think this is exactly what a health professional would do by default.

The truth is that doctors, nurses and allied health professionals operate with a very broad knowledge of illness and wellness, but limited information about us as individuals, and often the guidelines for treatment are sketchy or not agreed or embedded in that broad knowledge base.

Good work is being done to increase knowledge, consensus and evidence for treatment plans and guidelines of care. In some cases, the choice of which treatment will cure or harm a patient will depend on having more information about the individual than is in their history or health records. Then, a variation in the patient’s genome will determine whether a drug will work or cause damage. We have seen some high profile cases of this in breast cancer, cystic fibrosis and cardiovascular disease.

The Stratified Medicine Scotland Innovation Centre is one effort to improve this situation in at least two directions. The first is to integrate clinical records with information from the patient’s own genome sequence. This is different from a specific gene test currently available on the NHS because it creates a record of the whole genome. Over time, links between response rates and specific variations of genomes can be better understood and as a result, specialists can make better informed decisions about treatments.

We have all heard of the Human Genome Project and some might be aware of initiatives like the 1000 Genome Project or 23andMe. The ability to record the whole genome sequence is moving from the lab to the clinic. Part of the challenge here is about scale (tens of thousands of individuals) and part is the expansion of the science from genetic research to clinical research with genomic data as in input. The SMS-IC will initially offer this to patients with critical illnesses such as lung cancer.

In order to achieve this multiple research groups will need to build up the type of analysis and research that provides evidence of those links across different disease types. From there, insights and innovation can be translated into clinical trials and practice. Increasingly, this will mean analysing larger data sets that can only be brought together by a consortium at regional or national level.

The second direction is all about innovation and transfer of good ideas into viable services or products that the NHS and other health systems can use. Take the development of new drugs, for example. Patients with critical illnesses often want to participate in clinical trials, however drug discovery has recently become much more focused on very targeted approaches, where knowing how a patient’s body works at a molecular level. This means that qualifying for a trial means having knowledge of the patient’s genome for that target or variation.

The challenge here is creating an environment where research and clinical trials can happen. This requires a robust framework for data protection (even with anonymised or de-identified data) and a willingness to participate from patients, the health service, researchers and pharmaceutical companies. If that’s in place, then, for me at least, we are back in the familiar territory of informatics.