Adherence to Treatment With Imatinib in Chronic Myeloid Leukemia: A Study of the First Decade of Responses Obtained at a Brazilian Hospital.

Adherence to treatment with imatinib in chronic myeloid leukemia: a study of the first decade of responses obtained at a Brazilian hospital.

Rev Bras Hematol Hemoter. 2013; 35(3): 174-9
Dos Reis SR, Quixad√° AT, Nunes ST, Cid DM, de Souza JH, da Costa CM, Silveira CB, Cid DA, de Oliveira MF

The aim of this study was to identify the reasons for failure in adherence to imatinib mesylate treatment in chronic myeloid leukemia.A retrospective review was performed of 100 non-electronic records of patients with Ph(+) chronic myeloid leukemia treated with imatinib mesylate. The study period was from January 2001 to January2011. Data were analyzed by Chi-Square and Correspondence analysis using the Statistical Analysis System software package.At the beginning of treatment 41% of patients were in advanced stages of the disease. The unavailability of the drug (44.8%) and myelotoxicity (25.7%) were the most frequent reasons for interruption. The adherence rate was < 90% in 47% of the cases. The low adherence influenced the cytogenetic response (p-value = 0.020) and molecular response (p-value = 0.001). Very high adherence (> 95%) induced complete cytogenetic response, major cytogenetic response and major molecular response.The population of this study obtained lower-than-expected therapeutic responses compared to other studies. HubMed – drug

in silico analyses of metabolic pathway and protein interaction network for identification of next gen therapeutic targets in Chlamydophila pneumoniae.

Bioinformation. 2013; 9(12): 605-9
Ravindranath BS, Krishnamurthy V, Krishna V, Vasudevanayaka KB

Chlamydophila pneumoniae, the causative agent of chronic obstructive pulmonary disease (COPD), is presently the fifth mortality causing chronic disease in the world. The understanding of disease and treatment options are limited represents a severe concern and a need for better therapeutics. With the advancements in the field of complete genome sequencing and computational approaches development have lead to metabolic pathway analysis and protein-protein interaction network which provides vital evidence to the protein function and has been appropriate to the fields such as systems biology and drug discovery. Protein interaction network analysis allows us to predict the most potential drug targets among large number of the non-homologous proteins involved in the unique metabolic pathway. A computational comparative metabolic pathway analysis of the host H. sapiens and the pathogen C pneumoniae AR39 has been carried out at three level analyses. Firstly, metabolic pathway analysis was performed to identify unique metabolic pathways and non-homologous proteins were identified. Secondly, essentiality of the proteins was checked, where these proteins contribute to the growth and survival of the organism. Finally these proteins were further subjected to predict protein interaction networks. Among the total 65 pathways in the C pneumoniae AR39 genome 10 were identified as the unique metabolic pathways which were not found in the human host, 32 enzymes were predicted as essential and these proteins were considered for protein interaction analysis, later using various criteria’s we have narrowed down to prioritize ribonucleotide-diphosphate reductase subunit beta as a potential drug target which facilitate for the successful entry into drug designing. HubMed – drug