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Disease classification must catch up with science

Posted by
Duncan McHale, Global Exploratory Development
We all owe a great debt to 19th century medicine. This was a period when doctors began to apply some of the knowledge emerging from medical science to help diagnose and treat common illnesses.

It saw rapid advances in combatting infectious disease, in the use of anaesthesia and in medical statistics. Medical education, specialisation and research developed, laying the foundation for major progress in the 20th century.

Of course, as with all science, the ideas proposed and tested at the time remain open to ongoing scrutiny. In recent decades, advances in genetics and molecular biology have deepened our understanding of the underlying causes of ill-health.

19th century thinkers did not have this privilege. When they sought to classify diseases (itself a somewhat revolutionary idea we now take for granted), they did so based on patients' symptoms.

This, from a 19th century perspective, was perfectly reasonable. Symptoms were observed, conditions were described, and diseases could be categorised. From there, medical specialties developed whereby physicians would treat groups of patients with broadly similar symptoms such as joint pain or dementia.

That was then. Today we can see that the 19th century approach to disease classification was imperfect. We now know, for example, that not every patient with joint pain is the same even if their symptoms appear to be similar.

Some are suffering as a result of mechanical stress on their joints while others have an underlying inflammatory disease which may, in fact, be more closely related to other autoimmune diseases than to wear and tear.

This matters because people with the same symptoms can respond differently to treatment depending on the mechanism underlying their disease.

Yet the revolution in biomedical science which has delivered modern 21st century therapies has not yet been followed by a revolution in how we classify disease. If we fail to rethink this, we cannot expect to develop new therapies which radically transform the lives of all patients.

New approach
There are reasons for optimism. We understand the underlying causes of diseases like never before. We now have new tools which help us to unlock the potential of large volumes of clinical data, imaging, biomarker and genetic data to unveil patterns which would otherwise go unseen.

A recent paper in the journal Nature Reviews which I  co-authored highlights two significant projects in this field undertaken by the Innovative Medicines Initiative (IMI). The IMI is a public-private partnership co-funded by the EU and Europe's research-based pharmaceutical industry.

Together with its academic partner UCB is jointly leading the IMI’s AETIONOMY project which looks at classifying neurodegenerative conditions, particularly Alzheimer’s disease and Parkinson’s disease.

Working with academics and other companies, we are collecting and organising the large volumes of molecular data and information on symptoms. Based on this, the project aims to classify patient groups based on the underlying cause of their disease. The result will be new tools which can be used by the biomedical community to develop new treatments and diagnostic tests.

UCB is also leading the sister IMI project which aims to reclassify lupus, connective tissue diseases and rheumatoid arthritis. The PRECISESADS research consortium is drawing on the power of bioinformatics and OMICs to identify new classifications for diseases known to share common pathophysiological mechanisms.

These projects have the potential to feed into the development of a new 'taxonomy' of disease – a brand new classification system.

It is an ambitious goal but the reward would be huge. Smarter disease classification would help doctors to select therapies with greater confidence of success. For patients, this would mean less trial and error in search of the right treatment.

This in turn offers the promise of higher success rates in drug development, attracting greater investment which increases the likelihood of new cures.

From a societal and economic point of view, treating illness quickly and effectively saves resources and, by intervening early, may reduce the impact on patients' lives.

Reimagining how we categorise diseases will not be easy but it will be worth it.

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