The Experts below are selected from a list of 240 Experts worldwide ranked by ideXlab platform
Chulaporn Limwattananon - One of the best experts on this subject based on the ideXlab platform.
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The Potential Use of Hospital Electronic Drug Database in Evaluating of Colon Cancer in Patients Receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs)
2020Co-Authors: Suphat Subonkgot, Nutjaree Pratheepawanit, Chulaporn LimwattananonAbstract:Abstract The study of utilizing hospital electronic Drug Database in evaluating of colon cancer in patients receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs) was conducted in retrospective observational design. The main objectives were to validate the accuracy of hospital electronic Drug Database by mean of patient medication profiles and patient diagnostic information according to international classification of diseases 10 th revision (ICD-10) prior to evaluation of colon cancer. During fiscal year 2000 to 2002, patients who met criteria were randomly assigned into 2 phases of validation. In phase I, the study was aimed to validate an accuracy of medication profiles in hospital electronic Drug Database comparing to conventional patient medication records. Patients were classified into 2 categories naming ever use and continued use. In ever use group, patients had to at least take one dose of NSAIDs in a calendar year period whereas those in continued use group had to take NSAIDs continuously for at least 6 months period. Standardized questionnaires were sent out to 243 of continued use patients and 500 of ever use patients. Upon analyzing data from standardized questionnaires comparing with data from electronic Database and conventional patient medication records, our results demonstrated that in continued use group 73.6% of Drug names were in concordance among questionnaires, electronic Database and patient medication records. In addition 72% of strength, 69.7% of administration methods and 68.2% of Drug quantity were in concordance among these Databases respectively. In ever used group the results showed that 76% of Drug names, 75.4% of strength, 74.6% of administration methods, and 72.8% of Drug quantity were in concordance among the three Databases. In phase II, we aimed to validate the accuracy of patient diagnostic information by comparing data retrieved from patient medical records with international classification of diseases 10 th revision (ICD-10) and gold standard or National Cancer Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology version 2003. From 64 of 80 evaluable patients, our study demonstrated that 59.4% of patients were classified as definite diagnosis, 25% of patients were in probable, 3.1% of patients were in possible and 1.6% of patients were in unlikely diagnosis respectively. In conclusion, the results of this 2 phases study demonstrated that there is a need to improve a reliability of hospital electronic Drug Database prior to utilize it as valuable resource to evaluate risk of colon cancer. The accuracy of medication profiles of approximately 70% and near 60% in diagnostic information will prompt the administrative authorities to aim improving the level of accuracy of electronic Drug Database to 80% benchmark before using them as a researching tool. Keywords: Nonsteroidal Anti-inflammatory Drugs (NSAIDs), Colon cancer, Electronic Database
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°"√»÷ìâââŸà'Á'å ¢Õß‚√ßæ¬"∫"≈"π°"√ª√-‡¡'——åÁâà "π°≈ÿŸÉ'ââ—'àà'å The Potential Use of Hospital Electronic Drug Database in Evaluating of Colon Cancer in Patients Receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs)
2020Co-Authors: Suphat Subonkgot, Nutjaree Pratheepawanit, Chulaporn LimwattananonAbstract:The study of utilizing hospital electronic Drug Database in evaluating of colon cancer in patients receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs) was conducted in retrospective observational design. The main objectives were to validate the accuracy of hospital electronic Drug Database by mean of patient medication profiles and patient diagnostic information according to international classification of diseases 10 th revision (ICD-10) prior to evaluation of colon cancer. During fiscal year 2000 to 2002, patients who met criteria were randomly assigned into 2 phases of validation. In phase I, the study was aimed to validate an accuracy of medication profiles in hospital electronic Drug Database comparing to conventional patient medication records. Patients were classified into 2 categories naming ever use and continued use. In ever use group, patients had to at least take one dose of NSAIDs in a calendar year period whereas those in continued use group had to take NSAIDs continuously for at least 6 months period. Standardized questionnaires were sent out to 243 of continued use patients and 500 of ever use patients. Upon analyzing data from standardized questionnaires comparing with data from electronic Database and conventional patient medication records, our results demonstrated that in continued use group 73.6% of Drug names were in concordance among questionnaires, electronic Database and patient medication records. In
Suphat Subonkgot - One of the best experts on this subject based on the ideXlab platform.
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The Potential Use of Hospital Electronic Drug Database in Evaluating of Colon Cancer in Patients Receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs)
2020Co-Authors: Suphat Subonkgot, Nutjaree Pratheepawanit, Chulaporn LimwattananonAbstract:Abstract The study of utilizing hospital electronic Drug Database in evaluating of colon cancer in patients receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs) was conducted in retrospective observational design. The main objectives were to validate the accuracy of hospital electronic Drug Database by mean of patient medication profiles and patient diagnostic information according to international classification of diseases 10 th revision (ICD-10) prior to evaluation of colon cancer. During fiscal year 2000 to 2002, patients who met criteria were randomly assigned into 2 phases of validation. In phase I, the study was aimed to validate an accuracy of medication profiles in hospital electronic Drug Database comparing to conventional patient medication records. Patients were classified into 2 categories naming ever use and continued use. In ever use group, patients had to at least take one dose of NSAIDs in a calendar year period whereas those in continued use group had to take NSAIDs continuously for at least 6 months period. Standardized questionnaires were sent out to 243 of continued use patients and 500 of ever use patients. Upon analyzing data from standardized questionnaires comparing with data from electronic Database and conventional patient medication records, our results demonstrated that in continued use group 73.6% of Drug names were in concordance among questionnaires, electronic Database and patient medication records. In addition 72% of strength, 69.7% of administration methods and 68.2% of Drug quantity were in concordance among these Databases respectively. In ever used group the results showed that 76% of Drug names, 75.4% of strength, 74.6% of administration methods, and 72.8% of Drug quantity were in concordance among the three Databases. In phase II, we aimed to validate the accuracy of patient diagnostic information by comparing data retrieved from patient medical records with international classification of diseases 10 th revision (ICD-10) and gold standard or National Cancer Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology version 2003. From 64 of 80 evaluable patients, our study demonstrated that 59.4% of patients were classified as definite diagnosis, 25% of patients were in probable, 3.1% of patients were in possible and 1.6% of patients were in unlikely diagnosis respectively. In conclusion, the results of this 2 phases study demonstrated that there is a need to improve a reliability of hospital electronic Drug Database prior to utilize it as valuable resource to evaluate risk of colon cancer. The accuracy of medication profiles of approximately 70% and near 60% in diagnostic information will prompt the administrative authorities to aim improving the level of accuracy of electronic Drug Database to 80% benchmark before using them as a researching tool. Keywords: Nonsteroidal Anti-inflammatory Drugs (NSAIDs), Colon cancer, Electronic Database
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°"√»÷ìâââŸà'Á'å ¢Õß‚√ßæ¬"∫"≈"π°"√ª√-‡¡'——åÁâà "π°≈ÿŸÉ'ââ—'àà'å The Potential Use of Hospital Electronic Drug Database in Evaluating of Colon Cancer in Patients Receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs)
2020Co-Authors: Suphat Subonkgot, Nutjaree Pratheepawanit, Chulaporn LimwattananonAbstract:The study of utilizing hospital electronic Drug Database in evaluating of colon cancer in patients receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs) was conducted in retrospective observational design. The main objectives were to validate the accuracy of hospital electronic Drug Database by mean of patient medication profiles and patient diagnostic information according to international classification of diseases 10 th revision (ICD-10) prior to evaluation of colon cancer. During fiscal year 2000 to 2002, patients who met criteria were randomly assigned into 2 phases of validation. In phase I, the study was aimed to validate an accuracy of medication profiles in hospital electronic Drug Database comparing to conventional patient medication records. Patients were classified into 2 categories naming ever use and continued use. In ever use group, patients had to at least take one dose of NSAIDs in a calendar year period whereas those in continued use group had to take NSAIDs continuously for at least 6 months period. Standardized questionnaires were sent out to 243 of continued use patients and 500 of ever use patients. Upon analyzing data from standardized questionnaires comparing with data from electronic Database and conventional patient medication records, our results demonstrated that in continued use group 73.6% of Drug names were in concordance among questionnaires, electronic Database and patient medication records. In
Kay Brune - One of the best experts on this subject based on the ideXlab platform.
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Identification of Adverse Drug Reactions in Geriatric Inpatients Using a Computerised Drug Database
Drugs & Aging, 2012Co-Authors: Tobias Egger, Harald Dormann, Gabi Ahne, Ulrich Runge, Antje Neubert, Manfred Criegee-rieck, Karl G. Gassmann, Kay BruneAbstract:Introduction and objective Geriatric patients with multiple comorbidities are at high risk of experiencing an adverse Drug reaction (ADR) during hospitalisation. The aim of the study was to compare the rate of ADRs as predicted by a computerised pharmacological Database to the actual rate determined by direct observation in a sample of geriatric patients.
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Identification of Adverse Drug Reactions in Geriatric Inpatients Using a Computerised Drug Database
Drugs & Aging, 2003Co-Authors: Tobias Egger, Harald Dormann, Gabi Ahne, Ulrich Runge, Antje Neubert, Manfred Criegee-rieck, Karl G. Gassmann, Kay BruneAbstract:Introduction and objective Geriatric patients with multiple comorbidities are at high risk of experiencing an adverse Drug reaction (ADR) during hospitalisation. The aim of the study was to compare the rate of ADRs as predicted by a computerised pharmacological Database to the actual rate determined by direct observation in a sample of geriatric patients. Study design During a 4-month period, geriatric patients were monitored using prospective observation. Patients were intensively screened for ADRs by a pharmacoepidemiological team (PET), consisting of two pharmacists and a physician. Actual ADRs detected by the PET were compared with those predicted by a computerised Drug Database. Furthermore, the set of actual ADRs, which resulted from Drug-Drug interactions (DDIs), were contrasted with potential DDIs signalled by the Database. The main outcome measures were the incidence of actual ADRs. For the detection rate of the Database we focused on frequent ADRs (>1% according to product information and Database) and all DDIs indicated automatically by the Database. Results 163 patients (121 female), mean age 79.8 ± 7.1 years (range 60–98), were included in the study which was conducted on a geriatric rehabilitation hospital ward. The mean duration of hospitalisation was 24.3 ± 8.4 days. Elderly patients received an average of 14.0 Drugs (range 2–35) during their hospital stay. Of all patients, 60.7% experienced at least one ADR. The PET detected a total of 153 ADRs, with a mean of 0.9 ADRs per patient (range 0–5). The computerised Drug Database predicted an average of 309 potential ADRs for each patient; however, only 21 ADRs per patient were of high frequency. In 48% of ADR-positive patients (defined by PET) at least one of these frequent ADRs occurred. DDIs were detected by the PET in 14.7% of patients. Our Database indicated a mean of 12 potential DDIs per patient. In 14 out of 24 DDI-positive patients, at least one signal indicated a real DDI. The Database sensitivity was consequently 58.3%. Conclusion In geriatric patients the incidence of ADRs is high. Computerised Drug Databases are a useful tool for detecting and avoiding ADRs. Our software, however, also produced a large number of signals that did not relate to actual ADRs found by the PET. The sheer number of these ‘false’ signals shows the need for refinement and optimisation of Databases for daily clinical use.
Nutjaree Pratheepawanit - One of the best experts on this subject based on the ideXlab platform.
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The Potential Use of Hospital Electronic Drug Database in Evaluating of Colon Cancer in Patients Receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs)
2020Co-Authors: Suphat Subonkgot, Nutjaree Pratheepawanit, Chulaporn LimwattananonAbstract:Abstract The study of utilizing hospital electronic Drug Database in evaluating of colon cancer in patients receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs) was conducted in retrospective observational design. The main objectives were to validate the accuracy of hospital electronic Drug Database by mean of patient medication profiles and patient diagnostic information according to international classification of diseases 10 th revision (ICD-10) prior to evaluation of colon cancer. During fiscal year 2000 to 2002, patients who met criteria were randomly assigned into 2 phases of validation. In phase I, the study was aimed to validate an accuracy of medication profiles in hospital electronic Drug Database comparing to conventional patient medication records. Patients were classified into 2 categories naming ever use and continued use. In ever use group, patients had to at least take one dose of NSAIDs in a calendar year period whereas those in continued use group had to take NSAIDs continuously for at least 6 months period. Standardized questionnaires were sent out to 243 of continued use patients and 500 of ever use patients. Upon analyzing data from standardized questionnaires comparing with data from electronic Database and conventional patient medication records, our results demonstrated that in continued use group 73.6% of Drug names were in concordance among questionnaires, electronic Database and patient medication records. In addition 72% of strength, 69.7% of administration methods and 68.2% of Drug quantity were in concordance among these Databases respectively. In ever used group the results showed that 76% of Drug names, 75.4% of strength, 74.6% of administration methods, and 72.8% of Drug quantity were in concordance among the three Databases. In phase II, we aimed to validate the accuracy of patient diagnostic information by comparing data retrieved from patient medical records with international classification of diseases 10 th revision (ICD-10) and gold standard or National Cancer Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology version 2003. From 64 of 80 evaluable patients, our study demonstrated that 59.4% of patients were classified as definite diagnosis, 25% of patients were in probable, 3.1% of patients were in possible and 1.6% of patients were in unlikely diagnosis respectively. In conclusion, the results of this 2 phases study demonstrated that there is a need to improve a reliability of hospital electronic Drug Database prior to utilize it as valuable resource to evaluate risk of colon cancer. The accuracy of medication profiles of approximately 70% and near 60% in diagnostic information will prompt the administrative authorities to aim improving the level of accuracy of electronic Drug Database to 80% benchmark before using them as a researching tool. Keywords: Nonsteroidal Anti-inflammatory Drugs (NSAIDs), Colon cancer, Electronic Database
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°"√»÷ìâââŸà'Á'å ¢Õß‚√ßæ¬"∫"≈"π°"√ª√-‡¡'——åÁâà "π°≈ÿŸÉ'ââ—'àà'å The Potential Use of Hospital Electronic Drug Database in Evaluating of Colon Cancer in Patients Receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs)
2020Co-Authors: Suphat Subonkgot, Nutjaree Pratheepawanit, Chulaporn LimwattananonAbstract:The study of utilizing hospital electronic Drug Database in evaluating of colon cancer in patients receiving Nonsteroidal Anti-inflammatory Drugs (NSAIDs) was conducted in retrospective observational design. The main objectives were to validate the accuracy of hospital electronic Drug Database by mean of patient medication profiles and patient diagnostic information according to international classification of diseases 10 th revision (ICD-10) prior to evaluation of colon cancer. During fiscal year 2000 to 2002, patients who met criteria were randomly assigned into 2 phases of validation. In phase I, the study was aimed to validate an accuracy of medication profiles in hospital electronic Drug Database comparing to conventional patient medication records. Patients were classified into 2 categories naming ever use and continued use. In ever use group, patients had to at least take one dose of NSAIDs in a calendar year period whereas those in continued use group had to take NSAIDs continuously for at least 6 months period. Standardized questionnaires were sent out to 243 of continued use patients and 500 of ever use patients. Upon analyzing data from standardized questionnaires comparing with data from electronic Database and conventional patient medication records, our results demonstrated that in continued use group 73.6% of Drug names were in concordance among questionnaires, electronic Database and patient medication records. In
Malcolm J. D’souza - One of the best experts on this subject based on the ideXlab platform.
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Manipulating In-House Designed Drug Databases For The Prediction Of pH-Dependent Aqueous Drug Solubility
American Journal of Health Sciences, 2013Co-Authors: Malcolm J. D’souza, Ghada J. Alabed, Melissa Earley, Natalia Roberts, Fady J. GergesAbstract:Chemical, pharmacokinetic, and pharmacodynamics properties are available in the package inserts of every Food and Drug Administration (FDA) approved prescription Drug, including all available chemotherapy Drugs. These inserts follow a specific format imposed by the FDA. Whether chemotherapy Drugs are administered via the parenteral route or alimentary tract, a significant factor affecting their bioavailability, elimination, and consequently, the Drug’s effectiveness and potency, is its state of aqueous solubility. Water solubility has always lent itself poorly to the different predictive and experimental measures employed in the determination of a useful quantitative assessment. In this project, we first built a chemical structure-based searchable Database for 85 FDA approved chemotherapy Drugs and then used Bio- Rad’s KnowItAll ® Informatics suite to focus on the Drugs pH-dependent water solubility prediction. We compared the predicted values for water solubility to the available values reported in the Drug inserts, testing the practical utility and the predictive ability of our model in reporting such a clinically relevant, underreported pharmacokinetic parameter. A relational cancer Drug Database (MySQL) was created to further facilitate analysis and/or prediction of a chemotherapy compound’s missing pharmacokinetic properties.
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Structure Activity Relationships (SARs) Using a Structurally Diverse Drug Database: Validating Success of Predictor Tools.
Pharmacological Reviews, 2009Co-Authors: Malcolm J. D’souza, Fumie Koyoshi, Lynn M. EverettAbstract:: ADME/Tox (absorption, distribution, metabolism, elimination and toxicity) technology is traditionally associated as a tool in the Drug discovery process which is often used to predict the efficiency of Drug adsorption, distribution, metabolic pathways, and elimination. For the past four years we have been involved in an effort to evaluate readily available Food and Drug Administration (FDA) consumer Drug profiles and pharmacological data. Portable Document Format (PDF) data from Drug profiles available on the FDA Drug Information website were used to create a searchable FDA Consumer Drug Database© using Bio-Rad's KnowItAll® platform which includes ADME/Tox in silico predictors. 14 pertinent pharmaceutical and pharmacological properties were collected for 75 structurally diverse consumer prescription Drugs, and for several Drugs, not all properties were completely populated. The major objective of this investigation was to validate the platforms prediction models for plasma protein binding (PPB) and bioavailability (BIO).
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Extracting Relevant Information from FDA Drug Files to Create a Structurally Diverse Drug Database Using KnowItAll
Pharmacological Reviews, 2009Co-Authors: Malcolm J. D’souza, Fumie KoyoshiAbstract:: Each Food and Drug Administration (FDA) consumer Drug information file contains an inordinate amount of useful chemical, pharmaceutical, and pharmacological data. These files profile approved Drugs by chemical structure, solubility, absorption, distribution, metabolism, elimination, toxicity (ADME/Tox), and possible adverse reactions. The ability to utilize this data in the classroom is a new approach to connect theory, technology, and reality. The KnowItAll® Informatics System available through Bio-Rad Laboratories, Philadelphia, PA, offers fully integrated software and/or Database desktop solutions. It holds a large collection of in silico ADME/Tox predictors and is a chemical informatics platform used to record experimental data. This project had three goals: (1) extract relevant information for 75 Drugs from their freely available FDA Drug files (limited to orally administrated Drugs, pro-Drugs, having a chemical structure), (2) build a Database so this extracted FDA information is indexed for search and analysis, and when completed, (3) undergraduates involved in such a project should be capable of harvesting useful chemical, pharmaceutical, and pharmacological information; be adept in computational chemistry software tools; and should gain an enhanced vocabulary and new insights into organic chemistry, molecular biology, and physiology.
