The Experts below are selected from a list of 183 Experts worldwide ranked by ideXlab platform
Juliane Fluck - One of the best experts on this subject based on the ideXlab platform.
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Identification of new Drug classification terms in textual resources.
Bioinformatics (Oxford England), 2007Co-Authors: Corinna Kolárik, Martin Hofmann-apitius, Marc Zimmermann, Juliane FluckAbstract:Knowledge about biological effects of small molecules helps in the understanding of biological processes and supports the development of new therapeutic agents. DrugBank is a high quality database providing such information about Drugs that contains annotation of Drug effects and classification of therapeutic effects. However, to broaden the scope of such a database in classifying and annotating Drugs, systems for automatic extraction of classification terms and the corresponding annotation of Drugs are needed. We have developed an approach for the identification of new terms used in unstructured text that provide information about Drug properties. It is based on the identification and extraction of phrases corresponding to lexico-syntactic patterns--so-called Hearst patterns that contain Drug names and directly related Drug annotation terms. Such phrases could be identified with a high performance in DrugBank text (0.89 F-score) and in Medline abstracts (0.83 F-score). In comparison to DrugBank annotation terminology, a huge amount of new Drug annotation terms could be found. The evaluation of terms extracted from Medline showed that 29-53% of them are new valid Drug Property terms. They could be assigned to existing and new Drug Property classes not provided by the DrugBank Drug annotation. We come to the conclusion that our system can support database content update by providing additionally Drug descriptions of pharmacological effects not yet found in databases like DrugBank. Moreover, we propose that automatic normalization of terms improves the annotation and the retrieval of relevant database entries. Supplementary data are available at Bioinformatics online.
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identification of new Drug classification terms in textual resources
Intelligent Systems in Molecular Biology, 2007Co-Authors: Corinna Kolařik, Marc Zimmermann, Martin Hofmannapitius, Juliane FluckAbstract:Knowledge about biological effects of small molecules helps in the understanding of biological processes and supports the development of new therapeutic agents. DrugBank is a high quality database providing such information about Drugs that contains annotation of Drug effects and classification of therapeutic effects. However, to broaden the scope of such a database in classifying and annotating Drugs, systems for automatic extraction of classification terms and the corresponding annotation of Drugs are needed. We have developed an approach for the identification of new terms used in unstructured text that provide information about Drug properties. It is based on the identification and extraction of phrases corresponding to lexico-syntactic patterns-so-called Hearst patterns that contain Drug names and directly related Drug annotation terms. Such phrases could be identified with a high performance in DrugBank text (0.89 F-score) and in Medline abstracts (0.83 F-score). In comparison to DrugBank annotation terminology, a huge amount of new Drug annotation terms could be found. The evaluation of terms extracted from Medline showed that 29–53% of them are new valid Drug Property terms. They could be assigned to existing and new Drug Property classes not provided by the DrugBank Drug annotation. We come to the conclusion that our system can support database content update by providing additionally Drug descriptions of pharmacological effects not yet found in databases like DrugBank. Moreover, we propose that automatic normalization of terms improves the annotation and the retrieval of relevant database entries. Contact: corinna.kolarik@scai.fraunhofer.de Supplementary information: Supplementary data are available at Bioinformatics online.
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ISMB/ECCB (Supplement of Bioinformatics) - Identification of new Drug classification terms in textual resources
2007Co-Authors: Corinna Kolařik, Martin Hofmann-apitius, Marc Zimmermann, Juliane FluckAbstract:Knowledge about biological effects of small molecules helps in the understanding of biological processes and supports the development of new therapeutic agents. DrugBank is a high quality database providing such information about Drugs that contains annotation of Drug effects and classification of therapeutic effects. However, to broaden the scope of such a database in classifying and annotating Drugs, systems for automatic extraction of classification terms and the corresponding annotation of Drugs are needed. We have developed an approach for the identification of new terms used in unstructured text that provide information about Drug properties. It is based on the identification and extraction of phrases corresponding to lexico-syntactic patterns-so-called Hearst patterns that contain Drug names and directly related Drug annotation terms. Such phrases could be identified with a high performance in DrugBank text (0.89 F-score) and in Medline abstracts (0.83 F-score). In comparison to DrugBank annotation terminology, a huge amount of new Drug annotation terms could be found. The evaluation of terms extracted from Medline showed that 29–53% of them are new valid Drug Property terms. They could be assigned to existing and new Drug Property classes not provided by the DrugBank Drug annotation. We come to the conclusion that our system can support database content update by providing additionally Drug descriptions of pharmacological effects not yet found in databases like DrugBank. Moreover, we propose that automatic normalization of terms improves the annotation and the retrieval of relevant database entries. Contact: corinna.kolarik@scai.fraunhofer.de Supplementary information: Supplementary data are available at Bioinformatics online.
Changhong Wang - One of the best experts on this subject based on the ideXlab platform.
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study on formability of solid nanosuspensions during nanodispersion and solidification i novel role of stabilizer Drug Property
International Journal of Pharmaceutics, 2013Co-Authors: Peng-fei Yue, Jing Wan, Ming Yang, Wei-feng Zhu, Changhong WangAbstract:Few or no attempts have been made so far to understand the feasibility of solid nanosuspension formulation during nanodispersion and solidification in terms of Drug properties and stabilizer characterizations. In order to establish a knowledge base about the effect of physicochemical Property of Drug compounds and stabilizers on solid nanosuspension production during nanodispersion and solidification, a comparative study was firstly performed on 10 different stabilizers at 3 concentrations for 8 structurally different Drug compounds. Synthetic polymers (HPMC, PVP K30, CMS-Na and MC) displayed a poor stabilizing performance (10% success rate on average) during nanodispersion, but polymers showed better potential when higher concentrations was applied during freezing and lyophilization. Meanwhile, an effect for the surfactants group was even more pronounced during nanodispersion. However, the solid nanosuspension stabilized by surfactants showed the worst formability potential when be applied in setted concentrations during freezing and lyophilization. From the point of view of Drug Property, it was found that the surface hydrophobicity and cohesive energy of Drug, were responsible for the formability of the solid nanosuspension during nanodispersion and solidification. Wetting index (k) and ΔE were concluded to have a direct correlation on the feasibility of formation of a stable solid nanosuspension, which can give a formulation design strategy from where candidate Drugs and stabilizers with a set of properties.
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Study on formability of solid nanosuspensions during nanodispersion and solidification: I. Novel role of stabilizer/Drug Property.
International journal of pharmaceutics, 2013Co-Authors: Peng-fei Yue, Jing Wan, Ming Yang, Wei-feng Zhu, Changhong WangAbstract:Few or no attempts have been made so far to understand the feasibility of solid nanosuspension formulation during nanodispersion and solidification in terms of Drug properties and stabilizer characterizations. In order to establish a knowledge base about the effect of physicochemical Property of Drug compounds and stabilizers on solid nanosuspension production during nanodispersion and solidification, a comparative study was firstly performed on 10 different stabilizers at 3 concentrations for 8 structurally different Drug compounds. Synthetic polymers (HPMC, PVP K30, CMS-Na and MC) displayed a poor stabilizing performance (10% success rate on average) during nanodispersion, but polymers showed better potential when higher concentrations was applied during freezing and lyophilization. Meanwhile, an effect for the surfactants group was even more pronounced during nanodispersion. However, the solid nanosuspension stabilized by surfactants showed the worst formability potential when be applied in setted concentrations during freezing and lyophilization. From the point of view of Drug Property, it was found that the surface hydrophobicity and cohesive energy of Drug, were responsible for the formability of the solid nanosuspension during nanodispersion and solidification. Wetting index (k) and ΔE were concluded to have a direct correlation on the feasibility of formation of a stable solid nanosuspension, which can give a formulation design strategy from where candidate Drugs and stabilizers with a set of properties.
Sanjay Kumar - One of the best experts on this subject based on the ideXlab platform.
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6. Cathepsin K inhibitors: their potential as anti-osteoporosis agents.
Progress in Medicinal Chemistry, 2004Co-Authors: David N Deaton, Sanjay KumarAbstract:Publisher Summary Since the discovery of cathepsin K, its critical role in the resorption of the organic matrix of bone has been established by the efforts of numerous research groups. The potential use of cathepsin K inhibitors to prevent and treat osteoporosis has spurred Drug discovery research at many pharmaceutical companies. Pathological roles in arthritis and atherosclerosis offer other potential therapeutic options. Many thiol reactive groups have been coupled with enzyme recognition sequences to devise potent cathepsin K inhibitors. Multiple cycles of design, synthesis, structure elucidation, and Drug Property profiling have proved fruitful. These efforts are paying off with cathepsin K inhibitors entering clinical studies. Early human data supports a promising future for this therapeutic class of osteoporosis Drugs.
Peng-fei Yue - One of the best experts on this subject based on the ideXlab platform.
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study on formability of solid nanosuspensions during nanodispersion and solidification i novel role of stabilizer Drug Property
International Journal of Pharmaceutics, 2013Co-Authors: Peng-fei Yue, Jing Wan, Ming Yang, Wei-feng Zhu, Changhong WangAbstract:Few or no attempts have been made so far to understand the feasibility of solid nanosuspension formulation during nanodispersion and solidification in terms of Drug properties and stabilizer characterizations. In order to establish a knowledge base about the effect of physicochemical Property of Drug compounds and stabilizers on solid nanosuspension production during nanodispersion and solidification, a comparative study was firstly performed on 10 different stabilizers at 3 concentrations for 8 structurally different Drug compounds. Synthetic polymers (HPMC, PVP K30, CMS-Na and MC) displayed a poor stabilizing performance (10% success rate on average) during nanodispersion, but polymers showed better potential when higher concentrations was applied during freezing and lyophilization. Meanwhile, an effect for the surfactants group was even more pronounced during nanodispersion. However, the solid nanosuspension stabilized by surfactants showed the worst formability potential when be applied in setted concentrations during freezing and lyophilization. From the point of view of Drug Property, it was found that the surface hydrophobicity and cohesive energy of Drug, were responsible for the formability of the solid nanosuspension during nanodispersion and solidification. Wetting index (k) and ΔE were concluded to have a direct correlation on the feasibility of formation of a stable solid nanosuspension, which can give a formulation design strategy from where candidate Drugs and stabilizers with a set of properties.
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Study on formability of solid nanosuspensions during nanodispersion and solidification: I. Novel role of stabilizer/Drug Property.
International journal of pharmaceutics, 2013Co-Authors: Peng-fei Yue, Jing Wan, Ming Yang, Wei-feng Zhu, Changhong WangAbstract:Few or no attempts have been made so far to understand the feasibility of solid nanosuspension formulation during nanodispersion and solidification in terms of Drug properties and stabilizer characterizations. In order to establish a knowledge base about the effect of physicochemical Property of Drug compounds and stabilizers on solid nanosuspension production during nanodispersion and solidification, a comparative study was firstly performed on 10 different stabilizers at 3 concentrations for 8 structurally different Drug compounds. Synthetic polymers (HPMC, PVP K30, CMS-Na and MC) displayed a poor stabilizing performance (10% success rate on average) during nanodispersion, but polymers showed better potential when higher concentrations was applied during freezing and lyophilization. Meanwhile, an effect for the surfactants group was even more pronounced during nanodispersion. However, the solid nanosuspension stabilized by surfactants showed the worst formability potential when be applied in setted concentrations during freezing and lyophilization. From the point of view of Drug Property, it was found that the surface hydrophobicity and cohesive energy of Drug, were responsible for the formability of the solid nanosuspension during nanodispersion and solidification. Wetting index (k) and ΔE were concluded to have a direct correlation on the feasibility of formation of a stable solid nanosuspension, which can give a formulation design strategy from where candidate Drugs and stabilizers with a set of properties.
Kitaw Negash - One of the best experts on this subject based on the ideXlab platform.
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interrogating the relationship between rat in vivo tissue distribution and Drug Property data for 200 structurally unrelated molecules
Pharmacology Research & Perspectives, 2015Co-Authors: Andrew W. Harrell, Caroline Sychterz, Andrew Weber, Klára Valkó, Kitaw NegashAbstract:The ability to explain distribution patterns from Drug physicochemical properties and binding characteristics has been explored for more than 200 compounds by interrogating data from quantitative whole body autoradiography studies (QWBA). These in vivo outcomes have been compared to in silico and in vitro Drug Property data to determine the most influential properties governing Drug distribution. Consistent with current knowledge, in vivo distribution was most influenced by ionization state and lipophilicity which in turn affected phospholipid and plasma protein binding. Basic and neutral molecules were generally better distributed than acidic counterparts demonstrating weaker plasma protein and stronger phospholipid binding. The influence of phospholipid binding was particularly evident in tissues with high phospholipid content like spleen and lung. Conversely, poorer distribution of acidic Drugs was associated with stronger plasma protein and weaker phospholipid binding. The distribution of a proportion of acidic Drugs was enhanced, however, in tissues known to express anionic uptake transporters such as the liver and kidney. Greatest distribution was observed into melanin containing tissues of the eye, most likely due to melanin binding. Basic molecules were consistently better distributed into parts of the eye and skin containing melanin than those without. The data, therefore, suggest that Drug binding to macromolecules strongly influences the distribution of total Drug for a large proportion of molecules in most tissues. Reducing lipophilicity, a strategy often used in discovery to optimize pharmacokinetic properties such as absorption and clearance, also decreased the influence of nonspecific binding on Drug distribution.
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Interrogating the relationship between rat in vivo tissue distribution and Drug Property data for >200 structurally unrelated molecules.
Pharmacology research & perspectives, 2015Co-Authors: Andrew W. Harrell, Caroline Sychterz, Andrew Weber, Klára Valkó, Kitaw NegashAbstract:The ability to explain distribution patterns from Drug physicochemical properties and binding characteristics has been explored for more than 200 compounds by interrogating data from quantitative whole body autoradiography studies (QWBA). These in vivo outcomes have been compared to in silico and in vitro Drug Property data to determine the most influential properties governing Drug distribution. Consistent with current knowledge, in vivo distribution was most influenced by ionization state and lipophilicity which in turn affected phospholipid and plasma protein binding. Basic and neutral molecules were generally better distributed than acidic counterparts demonstrating weaker plasma protein and stronger phospholipid binding. The influence of phospholipid binding was particularly evident in tissues with high phospholipid content like spleen and lung. Conversely, poorer distribution of acidic Drugs was associated with stronger plasma protein and weaker phospholipid binding. The distribution of a proportion of acidic Drugs was enhanced, however, in tissues known to express anionic uptake transporters such as the liver and kidney. Greatest distribution was observed into melanin containing tissues of the eye, most likely due to melanin binding. Basic molecules were consistently better distributed into parts of the eye and skin containing melanin than those without. The data, therefore, suggest that Drug binding to macromolecules strongly influences the distribution of total Drug for a large proportion of molecules in most tissues. Reducing lipophilicity, a strategy often used in discovery to optimize pharmacokinetic properties such as absorption and clearance, also decreased the influence of nonspecific binding on Drug distribution.
