Using systems biology to evaluate targets and mechanism of action of drugs for diabetes comorbidities

• Published in: Diabetologia Vol. 59; no. 12; pp. 2503 - 2506
• Main Author: Mayer, Bernd
• Format: Journal Article Book Review
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2016; Springer Nature B.V
• Subjects: Animals; Comorbidity; Diabetes Mellitus - metabolism; Diabetic Nephropathies - metabolism; Human Physiology; Humans; Internal Medicine; Medicine; Medicine & Public Health; Metabolic Diseases; Mini-Review; Pharmacogenetics; Systems Biology - methods; Biomarker; Molecular model; Network; Prediction; Diabetic nephropathy; Review; Pharmacogenomics
• ISSN: 0012-186X; 1432-0428; 1432-0428
• DOI: 10.1007/s00125-016-4032-2

Medications approved for diabetes-associated renal and cardiovascular morbidities and candidate drugs currently in development are subject to substantial variability in drug response. Heterogeneity on a molecular phenotype level is not apparent at clinical presentation, which means that inter-individual differences in drug effect at the molecular level are masked. These findings identify the need for optimising patient phenotyping via use of molecular biomarkers for a personalised therapy approach. Molecular diversity may, on the one hand, result from the effect of genetic polymorphisms on drug transport, metabolism and effective target modulation. Equally relevant, differences may be due to molecular pathologies. The presence of distinct molecular phenotypes is suggested by classifiers aimed at modelling progressive disease. Such functions for prognosis incorporate a complex set of clinical variables or a multitude of molecular markers reflecting a diverse set of molecular disease mechanisms. This information on disease pathology and the mechanism of action of the drug needs to be systematically integrated with data on molecular biomarkers to develop an experimental tool for personalising medicine. The large amount of molecular data available for characterising diabetes-associated morbidities allows for elucidation of molecular process model representations of disease pathologies. Selecting biomarker candidates on such grounds and, in turn identifying their association with progressive disease allows for the identification of molecular processes associated with disease progression. The molecular effect of a drug can also be modelled at a molecular process level, and the integration of disease pathology and drug effect molecular models reveals candidate biomarkers for assessing drug response. Such tools serve as enrichment strategies aimed at adding precision to drug development and use.