New drugs can be developed from old ones. This revolutionary pharmacological approach that has been gaining ground recently was confirmed by a study published in Nature Communications.
Everything starts from an analysis of big data: the existing drugs and, in particular, their molecular properties, were analyzed with a new algorithm to see whether they could be used to treat other conditions, to bring benefits to patients with conditions that are difficult or impossible to treat. This technique, known as 'drug repositioning', has been already used in the past, but it has become even more effective today thanks to new technologies, which facilitate the quick and systematic analysis of a vast amount of data.
We have achieved promising results, explained the senior author: "We have tested the new algorithm to search for new therapies to treat metabolic syndrome, a condition that increases the risk of heart disease and type 2 diabetes and which is characterized by obesity, elevated levels of cholesterol and/or triglycerides, high blood pressure and diabetes. We identified the mutated genes that are responsible for these alterations and then searched pharmaceutical databases for already approved molecules that could interact with the networks that these genes form in the adipose tissue, liver and muscles. To carry out such a complex study we adopted a new computational approach that measures the "distance" between the proteins targeted by the drug and those found in the networks affected by the disease. That is how we found a new application for an already existing drug: Ibrutinib, which was originally developed to treat completely different conditions, and specifically B-cell tumors like mantle cell lymphoma, chronic lymphocytic leukemia, and Waldenström macroglobulinemia. Other studies on this drug are under way to determine if it could be used to treat autoimmune diseases".
The results of the computational analysis were validated on zebrafish larvae to confirm the response to the drug. The head of the research team explained how it worked: "By testing this drug in the laboratory we saw that the it is possible to limit the detrimental impact of obesity induced by a high-fat diet. The drug succeeded in limiting the inflammatory condition associated with lipid accumulation. Testing the effectiveness of a drug that is already on the market makes it possible to skip a number of long and complex stages of the approval process for new medical products, because their tolerance and safety have already been demonstrated. Our data are just a start and more in-depth studies and clinical tests are required, but they demonstrate that combining experience in big data analysis and the ability to develop models for biological validation can boost drug repurposing research".
Finding out that a market approved drug can potentially be used to treat metabolic syndrome is great news. The incidence of the disease and seriousness of its consequences on health (cardiovascular diseases and diabetes complications) have made metabolic syndrome a social problem in recent decades, especially in wealthy societies, where many people have a diet rich in sugars and fats and a sedentary lifestyle. In particular, the disease affects people over 50 years of age, about 30% of the male population and 35-40% of women. The metabolic syndrome becomes more common in women after menopause.
The study has enabled researchers to shorten the drug discovery process, but the findings would need to be validated in a clinical context to be able to use the drug for a disease different from the original indication. More research will be needed in the coming years to translate the experimental finding into a clinical application.
Using big data to repurpose old drug in metabolic syndrome
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