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• W2027879878 abstract "The concept of personalized medicine has received much attention in recent years. On the basis of increased knowledge of interindividual differences in DNA sequences, as well as the ability to link variation in the human genome to efficacy and adverse reactions caused by drug treatment, the pharmaceutical industry, clinicians and regulators are now focusing more on the individual response. This has led to a transition from population-based dosing and prescriptions to patient individualization both in drug development and in clinical practice. Furthermore, it has now become clear within the pharmaceutical industry that successful production of ‘blockbuster drugs’ with effects in the entire population will be increasingly less likely in the future; instead, more specific medications targeted towards subpopulations of patients will be required. Pharmacogenomics, the study of the variation in the human genome that can affect the response to drug therapy, was the focus of a symposium on Personalized medicine sponsored by the Journal of Internal Medicine (JIM) in Stockholm on 8 May 2014. In this issue of JIM, several of the speakers at this symposium review their different fields of expertise. Personalized medicine is based on the understanding of genomic, epigenomic, environmental and pathophysiological factors as well as drug interactions (Fig. 1). The major emphasis in personalized medicine today is on genomic factors of variability of drug response 1, 2, but in the future, maybe also epigenomic aspects will have an increasing role 3. Novel biomarkers, including circulating DNA, miRNAs or proteins/peptides that can predict drug response, are becoming increasingly important for personalized medicine. The identification of the genomic factors of variability of drug response is focused mainly on variation in genes encoding: (i) drug-metabolizing enzymes, (ii) drug transporters, (iii) drug targets and (iv) drug receptors and signal transduction molecules. This includes primarily analyses of the germline (host) genome but also the somatic genome of cancer tumours or infectious agents such as parasites and viruses 1. Knowledge about genomic variation of importance is mainly translated into clinical application by the introduction of pharmacogenomic labels into product descriptions [summaries of product characteristics (SmPCs)]. At present, 176 drugs approved by the US Food and Drug Administration contain pharmacogenomic information in the SmPCs (http://www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm), and for the European Medicines Agency, the current number of approximately 130 labels 4 is increasing rapidly. Pharmacogenomic labels state whether predictive genotyping of the patient's germline or somatic DNA is mandatory, highly recommended or informative 5. Furthermore, pharmacogenomic labels are of particular importance for cancer treatment, where dosages must be the highest possible without causing toxicity and where the variation in the cancer cell genome often determines whether or not the drug will have an effect. In addition, specific HLA types are strongly related to the toxicity of many antiviral, anti-epileptic and bacteriostatic drugs. Psychiatry is also an area in with many drug labels mainly related to pharmacokinetics of the drugs. In this issue of JIM, Stingl and Viviani 6 discuss the application of personalized medicine to psychiatry, focusing on the role of the polymorphic CYP2C19 and CYP2D6 genes for optimal treatment of depressive disorders with antidepressants and antipsychotics. The role of human genome variation is important for the treatment of other diseases of the central nervous system as highlighted by Walker et al. 7 exemplified, for example by the role of different HLA genes for the risk of adverse drug reactions after treatment with some anti-epileptic agents. Walker et al. also discuss the involvement of the sodium pump SCN1A polymorphism in dosing of and resistance to treatment with anti-epileptics as well as the role of inflammatory mediators as protein biomarkers for epilepsy. The role of pharmacogenomics in oncology is reviewed by Rodríguez-Antona and Taron 8. The authors highlight different pharmacogenomic studies in oncology as well as biomarkers established in the clinics, and focus on advances in personalized lung cancer and renal cancer treatment. In addition, they review the anticancer drugs with pharmacogenomic labelling. Personalized medicine for the treatment of rheumatoid arthritis (RA) is reviewed by Huizinga 9. The importance of personalization in different types of treatment for RA is discussed, and the role of anticitrullinated protein antibodies as markers for treatment intensity is highlighted. A novel and very important aspect of personalized medicine is the development of drugs targeting specific mutated variants of endogenous proteins. By screening the mutated target with specific low molecular weight compounds, ‘hits’ can be identified that are able to refold proteins that were originally incorrectly folded due to inherited mutations. Amaral 10 elegantly discusses the recent rapid and fruitful progress in the search for new therapies with compounds that, in a mutation specific manner, can correct misfolding of the CFTR protein causing cystic fibrosis. Such treatment causes a considerable increase in quality of life for many patients carrying some of the common mutated variants of the CFTR gene. Similarly, Zawacka-Pankau and Selivanova 11 describe the impressive progress in finding specific compounds that can restore mutated p53 function, thereby establishing a novel putative therapy for many different forms of cancer. The efficacy of antidiabetic drugs in the treatment of type II diabetes and cancer is affected not only by polymorphisms in genes encoding drug-metabolizing enzymes but also by polymorphic variants of transporters and targets involved in the action of antidiabetic drugs, such as metformin, acarbose, rosiglitazone, pioglitazone, repaglinide and sulfonylureas. These findings are mainly based on retrospective studies, and Emani-Riedmaier et al. 12 recommend that larger prospective studies should be conducted with a high power to determine the precise influence of such polymorphisms on treatment response. Finally, Milani et al. 13 provide an epidemiological perspective of the use of personalized medicine, reviewing different European initiatives. They focus on the results from the impressive Estonian approach including an extensive biobank. In recent years, the improvement in genome sequencing methods has yielded databases with a considerable amount of data from whole-exome sequencing of >200 000 human genomes (e.g. see http://evs.gs.washington.edu/EVS/). From this information, it is evident that many previously undiscovered rare functional mutations occur in the open reading frame of genes of critical importance for drug response. The total number of these new rare functional variant alleles often exceeds the number of those previously known, which emphasizes the need for exome sequencing instead of targeted genotyping to determine the specific individual genotype. We face a future in which drugs are developed to a much greater extent for specific subpopulations, with genomic and other biomarkers helping to provide more efficient personalized therapy. The principle of personalized therapy has been successful in increasing survival in, for example, patients with different forms of leukaemia, where few new drugs have been developed but where treatment with existing drugs has been more personalized. We are entering an era of development of drugs targeting specific inherited or acquired mutations in the germline or somatic genomes; thus, drug treatment is becoming so much more versatile. In addition, the number of useful pharmacogenomic and other biomarkers with potential to greatly enhance the future efficacy of drug treatment is steadily increasing and will help to improve the health status in the populations. No conflict of interest was declared." @default.
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• W2027879878 title "Personalized medicine into the next generation" @default.
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