Journal of IiMER June 2024 Dr Dezső Modos, Imperial College London, UK Dr Dezső Modos is an Imperial College Research Fellow in the Systems Medicine division of the Department of Metabolism, Digestion and Reproduction. He completed his medical degree at Semmelweis University and a minor in bionics at the Pázmány Péter Catholic University. Later he obtained his PhD at the Semmelweis University on network biology. His primary focus was the intracellular signalling network in cancer and understanding the role of paralogues in signalling. After his PhD he moved to Cambridge and learned cheminformatics. He used network biology to understand and predict compound synergy in cancer. Here he also learned about various cheminformatic techniques, which he is adapting for his fellowship. The current inflammatory bowel disease (IBD) therapies maintain remission only in around 30% of cases forming therapeutic celling. His fellowship aims to find the right drug to the right patient in IBD. Similarly, we can use the targets of IBD drugs as a source node and build a drug specific network footprint. The comparison of patient-specific disease and drug networks, much like connectivity mapping, can aid in identifying the correct drug for each patient. Single nucleotide polymorphisms (SNPs) in inflammatory bowel disease are often in the non-coding region of the genome. He and his colleagues developed a tool called iSNP (https://github.com/korcsmarosgroup/iSNP) which can map these single nucleotide polymorphisms to regulatory regions and through that SNP affected genes. From the SNP affected genes, patient specific signalling networks, individual pathogenetic pathways and patient specific network footprints can be constructed. Already, he has used this method to understand ulcerative colitis pathogenesis. Precision Life, UK PrecisionLife is a precision medicine company focused on finding better, more personalised treatment options for complex chronic diseases such as Alzheimer’s, diabetes, and endometriosis. It analyses large amounts of data from sources such as clinical trials, patient charities, biobanks, and research organisations to stratify, or segment, patients into clinically relevant subgroups. It can then identify potential drug targets based on the cause of each subgroups’ condition and help healthcare providers diagnose these conditions more accurately and effectively. PrecisionLife received an Advancing Precision Medicine grant from Innovate UK to investigate the causes of ME and long Covid. One of the first project objectives will be for PrecisionLife to use its precision medicine approach to identify the biological mechanisms driving disease in different groups of patients. The results will be used to create the first predictive diagnostic tools and risk models that can rapidly triage patients presenting to a doctor with potential ME/CFS or long Covid symptoms. Invest in ME Research Page 28 of 32
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