Entity

Time filter

Source Type


Patent
Kyoto Constella Technologies Co. and Kyoto University | Date: 2013-08-24

When the interaction of a compound is predicted by using a computer, a technique to highly precisely design a compound having a novel structure has been required. A compound designing device is provided which includes an input unit configured to receive, at least about one or more query proteins, one or more pieces of query protein information corresponding to the one or more query proteins; and a processing unit configured to perform steps of (a) generating one or more pieces of compound information, (b) computing a score indicating interaction potential between a compound corresponding to the compound information and each of the one or more query proteins, (c) updating the compound information by an optimization method with reference to the score computed at step (b) such that the interaction potential increases, and (d) repeating steps (b) and (c) a plurality of times.


Tamura T.,Kinki University | Sakaeda T.,Kyoto University | Kadoyama K.,Kyoto University | Okuno Y.,Kyoto University | Okuno Y.,Kyoto Constella Technologies Co.
International Journal of Medical Sciences | Year: 2012

Objective: Adverse event reports (AERs) submitted to the US Food and Drug Administration (FDA) were reviewed to assess the bleeding complications induced by the administration of antiplatelets and to attempt to determine the rank-order of the association. Methods: After a deletion of duplicated submissions and the revision of arbitrary drug names, AERs involving warfarin, aspirin, cilostazol, clopidogrel, ethyl icosapentate, limaprost alfadex, sarpogrelate, and ticlopidine were analyzed. Authorized pharmacovigilance tools were used for the quantitative detection of signals, i.e., drug-associated adverse events, including the proportional reporting ratio, the reporting odds ratio, the information component given by a Bayesian confidence propagation neural network, and the empirical Bayes geometric mean. Results: Based on 22,017,956 co-occurrences, i.e., drug-adverse event pairs, found in 1,644,220 AERs from 2004 to 2009, 736 adverse events were listed as warfarin-associated adverse events, and 147 of the 736 were bleeding complications, including haemorrhage and haematoma. Both aspirin and clopidogrel were associated with haemorrhage, but the association was more noteworthy for clopidogrel. As for bleeding complications related to the gastrointestinal system, e.g., melaena and haematochezia, the statistical metrics suggested a stronger association for aspirin than clopidogrel. The total number of co-occurrences was not large enough to compare the association with bleeding complications for the other 5 antiplatelets. Conclusions: The data strongly suggest the necessity of well-organized clinical studies with respect to antiplatelet-associated bleeding complications. © Ivyspring International Publisher. Source


Tamura T.,Kinki University | Sakaeda T.,Kyoto University | Kadoyama K.,Kyoto University | Okuno Y.,Kyoto University | Okuno Y.,Kyoto Constella Technologies Co.
International Journal of Medical Sciences | Year: 2012

Objective: Case reports showing that proton-pump inhibitors (PPIs), omeprazole and esomeprazole, can cause hypomagnesaemia have been accumulating since 2006. In this study, the reports submitted to the Adverse Event Reporting System (AERS) of the US Food and Drug Administration (FDA) were evaluated to assess omeprazole and esomeprazole in terms of susceptibility to hypomagnesaemia. Methods: After a revision of arbitrary drug names and the deletion of duplicated submissions, the reports involving omeprazole and esomeprazole were analyzed. Standardized official pharmacovigilance tools were used for the quantitative detection of a signal, i.e., an association between a drug and an adverse drug event, including the proportional reporting ratio, the reporting odds ratio, the information component given by a Bayesian confidence propagation neural network, and the empirical Bayes geometric mean. Results: A total of 22,017,956 co-occurrences were found in 1,644,220 reports from 2004 to 2009, where a co-occurrence was a pair of a drug and an adverse drug event. In total, 818 and 743 adverse drug events were listed as omeprazole- and esomeprazole-associated, with hypomagnesaemia ranking 85th and 135th, respectively. Although both PPIs were associated with hypomagnesaemia, the statistical metrics suggested that the association was more noteworthy for omeprazole. Conclusion: The data obtained in this study do not provide sufficient evidence to recommend systematic monitoring of magnesium levels in plasma, but chronic exposure to a PPI can lead to severe hypomagnesaemia. © Ivyspring International Publisher. Source


Sakaeda T.,Kyoto University | Tamon A.,Kyoto Constella Technologies Co. | Kadoyama K.,Kyoto University | Okuno Y.,Kyoto University
International Journal of Medical Sciences | Year: 2013

The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS, formerly AERS) is a database that contains information on adverse event and medication error reports submitted to the FDA. Besides those from manufacturers, reports can be submitted from health care professionals and the public. The original system was started in 1969, but since the last major revision in 1997, reporting has markedly increased. Data mining algorithms have been developed for the quantitative detection of signals from such a large database, where a signal means a statistical association between a drug and an adverse event or a drug-associated adverse event, including the proportional reporting ratio (PRR), the reporting odds ratio (ROR), the information component (IC), and the empirical Bayes geometric mean (EBGM). A survey of our previous reports suggested that the ROR provided the highest number of signals, and the EBGM the lowest. Additionally, an analysis of warfarin-, aspirin- and clopidogrel-associated adverse events suggested that all EBGM-based signals were included in the PRR-based signals, and also in the IC- or ROR-based ones, and that the PRR- and IC-based signals were in the ROR-based ones. In this article, the latest information on this area is summarized for future pharmacoepidemiological studies and/or pharmacovigilance analyses. © Ivyspring International Publisher. Source


Kadoyama K.,Kyoto University | Kuwahara A.,Mukogawa Womens University | Yamamori M.,Mukogawa Womens University | Brown J.B.,Kyoto University | And 3 more authors.
Journal of Experimental and Clinical Cancer Research | Year: 2011

Background: Previously, adverse event reports (AERs) submitted to the US Food and Drug Administration (FDA) database were reviewed to confirm platinum agent-associated hypersensitivity reactions. The present study was performed to confirm whether the database could suggest the hypersensitivity reactions caused by anticancer agents, paclitaxel, docetaxel, procarbazine, asparaginase, teniposide, and etoposide. Methods. After a revision of arbitrary drug names and the deletion of duplicated submissions, AERs involving candidate agents were analyzed. The National Cancer Institute Common Terminology Criteria for Adverse Events version 4.0 was applied to evaluate the susceptibility to hypersensitivity reactions, and standardized official pharmacovigilance tools were used for quantitative detection of signals, i.e., drug-associated adverse events, including the proportional reporting ratio, the reporting odds ratio, the information component given by a Bayesian confidence propagation neural network, and the empirical Bayes geometric mean. Results: Based on 1,644,220 AERs from 2004 to 2009, the signals were detected for paclitaxel-associated mild, severe, and lethal hypersensitivity reactions, and docetaxel-associated lethal reactions. However, the total number of adverse events occurring with procarbazine, asparaginase, teniposide, or etoposide was not large enough to detect signals. Conclusions: The FDA's adverse event reporting system, AERS, and the data mining methods used herein are useful for confirming drug-associated adverse events, but the number of co-occurrences is an important factor in signal detection. © 2011 Kadoyama et al; licensee BioMed Central Ltd. Source

Discover hidden collaborations