Five Thoughts on Transforming Disease

Perdita Barran
 

We need to work fast – we need to keep up with the predictive power offered by machine learning and we need to test their hypotheses.

When we have robust markers there will be two types of assay, to develop -point of use and point of care. Both are based on analytical science. We also need to keep both accessible. MRM assays for biomarkers in the clinic remain the most affordable way to provide results, especially for non-infectious disease.

Juergen Popp
 

Demographic change, together with the expected shortage of doctors, will pose major challenges for healthcare in Germany, for example. In this context, new telemedical approaches are becoming increasingly important. This is precisely where light-based analytical (especially spectroscopic) methods in combination with AI will come into play and, in my opinion, play an increasingly important role in the future in the diagnosis or monitoring of a wide range of vital functions. The vision is a system like the tricorder used in the science fiction series Star Trek. As far as the monitoring of vital functions such as pulse or blood pressure is concerned, this is already possible with optical analytical approaches integrated into smartwatches. I am sure that the portfolio of optical methods integrated into mobile phones, smartwatches, etc. for determining other vital parameters or for diagnosing diseases (see the example of infection diagnostics using Raman point-of-care spectroscopy above) will expand significantly in the future and thus relieve the burden on general practitioners.

Albert Heck
 

We need to start analyzing and monitoring protein levels in each healthy individual, as this is the genuine control to be able to diagnose diseases states later on.

Lingjun Li
 

Most of the current disease diagnosis and treatment have been focusing on a single protein or a pathway, however, many diseases are multifactorial disorders that require a more holistic view at the systems level, especially for those diseases that we currently do not have effective treatment or lack of early diagnosis. With the continuous development of more advanced analytical instrumentation, especially mass spectrometers that offer higher throughput, better sensitivity, and higher resolution, together with innovative sample preparation and chemical tagging approaches, we are positioned to obtain a more complete and deeper coverage of various biomolecules. This advancement will lead to discovery of novel biomarkers for disease diagnosis and evaluate treatment efficacy in a broader system context. It will also generate new hypotheses for better understanding of disease mechanisms and potentially lead to novel therapeutic targets and treatment.

Michal Holčapek
 

I hope for improvements in high-throughput quantification of many biomolecules (lipids, metabolites, proteins, etc.), which will be correlated with the prediction and diagnosis of serious human diseases. The highest possible quality of analytical measurements and subsequent statistical evaluation of the data are prerequisites for such transformation because the mediocre quality of analytical data does not lead to the goal. I believe that physiological ranges of concentrations will be defined for particular subgroups (gender, age, BMI, ethnicity, etc.), so the outlying values will be used for the prediction, diagnosis, and treatment monitoring of many diseases using advanced statistical algorithms in combination with machine learning approaches and AI. However, the basis will always be the quality of the analytical measurements.