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Objective: To synthesize peer‑reviewed knowledge on the frequency of different types of chemotherapy medication errors. Methods: The data were collected from studies published between January 1, 2000, and March 3, 2018, and are identified through online resources such as Medline/PubMed, PubMed Central, Agency for Healthcare Research, and Quality and the Cochrane Library. The manuscripts published in peer‑reviewed scientific journals in English language were included in the study. Initially, 19,723 articles were retrieved and finally 11 were found to be eligible to include in the review and were assessed for quality. Error percentages were calculated from the ratio of error type (numerator) to sample size (denominator: medication orders or prescriptions).

DNA repair genes are crucial in maintaining the integrity of the whole genome. Single nucleotide polymorphisms (SNPs) in DNA repair genes have been attributed to the development of various cancers. SNPs of DNA repair genes (ERCC1 and ERCC2) have been implicated in the causation of various cancers as well as inter-individual variability in the therapeutic outcomes of platinum based therapy. Thus establishing the frequency of these functional SNPs in the healthy population is of significance. The present study was aimed to establish the allele and genotype frequencies of ERCC1 (19007C>T, rs11615; 8092C>A, rs3212986) and ERCC2 (Asp312Asn, rs1799793) genes in South Indian healthy population and to compare the data from HapMap populations. The study population consisted of 128 healthy South Indian unrelated individuals of either sex aged between 18 and 60 years. Standard phenol-chloroform method was used to extract DNA from peripheral leukocytes. The genotype of DNA repair gene polymorphisms was determined by quantitative real-time polymerase chain reaction using TaqMan genotyping assay. The observed frequency of the studied polymorphisms followed Hardy-Weinberg equilibrium (p>0.05). The frequencies of the minor alleles of the SNPs rs11615 (T), rs3212986 (A) and rs1799793 (A) were 43.8%, 29.3% and 35.6%, respectively. Gender-based analysis showed no significant difference in the frequency pattern. The observed allele and genotype frequencies showed significant ethnic difference between South Indians and other HapMap populations. This is the first study to provide the normative frequency data of allele and genotype distribution of three SNPs of ERCC1 and ERCC2 in South Indian healthy population. It might be useful in future genotype-phenotype association studies, especially for predicting the efficacy and adverse events of platinum based drugs.

The last decade has witnessed a greater transparency in clinical research with the advent of clinical trial registries. The aim of the study was to describe the trends in the globalization of clinical trials in the last five years. We performed an internet search using the WHO International clinical trials registry platform (WHO ICTRP) to identify the clinical trials conducted from January 2007 to December 31, 2011 among 25 countries. Among the 25 countries, the United States, Japan and Germany occupy the top positions in the total number of clinical trials conducted. Clinical trials in the US (36312) constituted 31.5% of the total number of trials performed during this period. However over a period of five years both US and Western Europe appear to show a decline, while the emerging countries show a rise in clinical trials registered. Among the emerging countries China, India and Republic of Korea are most active regions involved in clinical trials. Cancer, diabetes and respiratory diseases were most widely researched areas overall. Although the study confirms the transition in the clinical trials research towards emerging countries, the developed regions of the world still contribute to more than 70% of the trials registered worldwide.

To refer to metabolomics as a new field is injustice to ancient doctors who used ants to diagnose the patients of diabetes having glycosuria. Measuring the levels of molecules in biological fluids believing them to be the representatives of biochemical pathways of carbohydrates, fats, proteins, nucleic acids or xenobiotic metabolism and deciphering meaningful data from it is what can be called as metabolomics, just as high glucose in urine suggests diabetes mellitus. Genomics, epigenetics, proteomics, transcriptomics finally converge to metabolomics, which are the signatures of mechanisms of bodily processes which is why understanding this science can have many applications. Just as a heap of stones does not make a house, having data of metabolite levels does not make it a science. Analyzing this data would help us in constructing biochemical pathways and their interactions. Analyzing the changes caused by a drug in the metabolite levels would help us in deriving the mechanisms by which the drug acts. Comparing metabolite levels in diseased with non-diseased, good-responders with poor-responders to a particular drug can help in identifying new markers of a disease or response to a drug respectively. Also, metabolite levels of an endogenous substrate can tell us the status of a person’s metabolizing enzymes and help in drug dose titration. Generating hypothesis by identifying the new molecular markers and testing their utility in clinics seems to be the most promising approach in future. This review narrates the modes of quantifying and identifying metabolome, its proposed applications in diagnosis, monitoring and understanding the diseases and drug responses. We also intend to identify hindrances in using metabolomics in clinical studies or experiments.