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1.
Brief Bioinform ; 25(4)2024 May 23.
Article in English | MEDLINE | ID: mdl-38980370

ABSTRACT

RepurposeDrugs (https://repurposedrugs.org/) is a comprehensive web-portal that combines a unique drug indication database with a machine learning (ML) predictor to discover new drug-indication associations for approved as well as investigational mono and combination therapies. The platform provides detailed information on treatment status, disease indications and clinical trials across 25 indication categories, including neoplasms and cardiovascular conditions. The current version comprises 4314 compounds (approved, terminated or investigational) and 161 drug combinations linked to 1756 indications/conditions, totaling 28 148 drug-disease pairs. By leveraging data on both approved and failed indications, RepurposeDrugs provides ML-based predictions for the approval potential of new drug-disease indications, both for mono- and combinatorial therapies, demonstrating high predictive accuracy in cross-validation. The validity of the ML predictor is validated through a number of real-world case studies, demonstrating its predictive power to accurately identify repurposing candidates with a high likelihood of future approval. To our knowledge, RepurposeDrugs web-portal is the first integrative database and ML-based predictor for interactive exploration and prediction of both single-drug and combination approval likelihood across indications. Given its broad coverage of indication areas and therapeutic options, we expect it accelerates many future drug repurposing projects.


Subject(s)
Drug Repositioning , Machine Learning , Drug Repositioning/methods , Humans , Internet , Drug Therapy, Combination , Databases, Pharmaceutical , Databases, Factual
2.
Database (Oxford) ; 20242024 Jul 11.
Article in English | MEDLINE | ID: mdl-38994794

ABSTRACT

In recent years, drug repositioning has emerged as a promising alternative to the time-consuming, expensive and risky process of developing new drugs for diseases. However, the current database for drug repositioning faces several issues, including insufficient data volume, restricted data types, algorithm inaccuracies resulting from the neglect of multidimensional or heterogeneous data, a lack of systematic organization of literature data associated with drug repositioning, limited analytical capabilities and user-unfriendly webpage interfaces. Hence, we have established the first all-encompassing database called DrugRepoBank, consisting of two main modules: the 'Literature' module and the 'Prediction' module. The 'Literature' module serves as the largest repository of literature-supported drug repositioning data with experimental evidence, encompassing 169 repositioned drugs from 134 articles from 1 January 2000 to 1 July 2023. The 'Prediction' module employs 18 efficient algorithms, including similarity-based, artificial-intelligence-based, signature-based and network-based methods to predict repositioned drug candidates. The DrugRepoBank features an interactive and user-friendly web interface and offers comprehensive functionalities such as bioinformatics analysis of disease signatures. When users provide information about a drug, target or disease of interest, DrugRepoBank offers new indications and targets for the drug, proposes new drugs that bind to the target or suggests potential drugs for the queried disease. Additionally, it provides basic information about drugs, targets or diseases, along with supporting literature. We utilize three case studies to demonstrate the feasibility and effectiveness of predictively repositioned drugs within DrugRepoBank. The establishment of the DrugRepoBank database will significantly accelerate the pace of drug repositioning. Database URL:  https://awi.cuhk.edu.cn/DrugRepoBank.


Subject(s)
Drug Repositioning , Drug Repositioning/methods , Humans , Databases, Pharmaceutical , User-Computer Interface , Drug Discovery/methods , Algorithms , Databases, Factual
3.
Database (Oxford) ; 20242024 Jun 29.
Article in English | MEDLINE | ID: mdl-38943608

ABSTRACT

Drug transporters, integral membrane proteins found throughout the human body, play critical roles in physiological and biochemical processes through interactions with ligands, such as substrates and inhibitors. The extensive and disparate data on drug transporters complicate understanding their complex relationships with ligands. To address this challenge, it is essential to gather and summarize information on drug transporters, inhibitors and substrates, and simultaneously develop a comprehensive and user-friendly database. Current online resources often provide fragmented information and have limited coverage of drug transporter substrates and inhibitors, highlighting the need for a specialized, comprehensive and openly accessible database. ISTransbase addresses this gap by amassing a substantial amount of data from literature, government documents and open databases. It includes 16 528 inhibitors and 4465 substrates of 163 drug transporters from 18 different species, resulting in a total of 93 841 inhibitor records and 51 053 substrate records. ISTransbase provides detailed insights into drug transporters and their inhibitors/substrates, encompassing transporter and molecule structure, transporter function and distribution, as well as experimental methods and results from transport or inhibition experiments. Furthermore, ISTransbase offers three search strategies that allow users to retrieve drugs and transporters based on multiple selectable constraints, as well as perform checks for drug-drug interactions. Users can also browse and download data. In summary, ISTransbase (https://istransbase.scbdd.com/) serves as a valuable resource for accurately and efficiently accessing information on drug transporter inhibitors and substrates, aiding researchers in exploring drug transporter mechanisms and assisting clinicians in mitigating adverse drug reactions Database URL: https://istransbase.scbdd.com/.


Subject(s)
Membrane Transport Proteins , Humans , Membrane Transport Proteins/metabolism , Internet , Databases, Protein , Databases, Factual , Animals , Databases, Pharmaceutical
4.
Future Med Chem ; 16(10): 1029-1051, 2024.
Article in English | MEDLINE | ID: mdl-38910575

ABSTRACT

Compound databases (DBs) are essential tools for drug discovery. The number of DBs in public domain is increasing, so it is important to analyze these DBs. In this article, the main characteristics of 64 DBs will be presented. The methodological strategy used was a literature search. To analyze the characteristics obtained in the review, the DBs were categorized into two subsections: Open Access and Commercial DBs. Open access includes generalist DBs (containing compounds of diverse origins), DBs with specific applicability, DBs exclusive to natural products and those containing compounds with specific pharmacological action. The literature review showed that there are challenges to making these repositories available, such as standardizing information curation practices and funding to maintain and sustain them.


[Box: see text].


Subject(s)
Biological Products , Drug Discovery , Biological Products/chemistry , Biological Products/pharmacology , Humans , Databases, Chemical , Databases, Factual , Databases, Pharmaceutical
5.
Pharmacoepidemiol Drug Saf ; 33(5): e5804, 2024 May.
Article in English | MEDLINE | ID: mdl-38741353

ABSTRACT

PURPOSE: To evaluate the real-world rates of non-adherence and non-persistence to antiretroviral therapy (ART) among treatment-naïve adult patients with HIV after a 12-month follow-up period in Belgium. METHODS: A retrospective analysis of longitudinal pharmacy claims was conducted using the Pharmanet database from January 1, 2018, to December 31, 2021. Non-adherence was assessed over 12 months and reported as the proportion of days covered below the 80% threshold. Non-persistence was defined as the first 90-day gap in treatment between the two types of ART dispensed. Poisson regression with robust standard error and Cox proportional hazard models were used to assess the factors associated with non-adherence and non-persistence, respectively. RESULTS: Overall, 2999 patients were initiated on ART between 2018 and 2021. After a 12-month follow-up, the proportions of non-adherence and non-persistence were 35.6% and 15.9%, respectively in 2018, and decreased to 18.7% and 6.8%, respectively in 2021. Non-adherence was higher among women, Brussels residents, and those receiving multiple-tablet regimens (MTRs). Similarly, the prevalence of non-persistence was higher among women and MTR recipients. CONCLUSION: Among treatment-naïve adults with HIV in Belgium, non-adherence, and non-persistence to ART showed improvement over the study period but remained at high levels. Disparities were observed by sex and between geographical regions. Prioritizing strategies targeting women in Brussels and facilitating the transition from MTRs to single-tablet regimens should be emphasized optimize adherence to ART in Belgium.


Subject(s)
Anti-HIV Agents , HIV Infections , Medication Adherence , Humans , Belgium/epidemiology , Female , Male , Medication Adherence/statistics & numerical data , HIV Infections/drug therapy , HIV Infections/epidemiology , Adult , Retrospective Studies , Middle Aged , Anti-HIV Agents/therapeutic use , Anti-HIV Agents/administration & dosage , Databases, Factual , Young Adult , Databases, Pharmaceutical/statistics & numerical data , Follow-Up Studies , Adolescent , Longitudinal Studies
6.
Comput Biol Med ; 175: 108536, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38701592

ABSTRACT

In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.


Subject(s)
Mental Disorders , Nervous System Diseases , Humans , Mental Disorders/drug therapy , Mental Disorders/metabolism , Nervous System Diseases/drug therapy , Databases, Pharmaceutical , Databases, Factual
7.
J Chem Inf Model ; 64(10): 4334-4347, 2024 May 27.
Article in English | MEDLINE | ID: mdl-38709204

ABSTRACT

Drug synergy therapy is a promising strategy for cancer treatment. However, the extensive variety of available drugs and the time-intensive process of determining effective drug combinations through clinical trials pose significant challenges. It requires a reliable method for the rapid and precise selection of drug synergies. In response, various computational strategies have been developed for predicting drug synergies, yet the exploitation of heterogeneous biological network features remains underexplored. In this study, we construct a heterogeneous graph that encompasses diverse biological entities and interactions, utilizing rich data sets from sources, such as DrugCombDB, PubChem, UniProt, and cancer cell line encyclopedia (CCLE). We initialize node feature representations and introduce a novel virtual node to enhance drug representation. Our proposed method, the heterogeneous graph attention network for drug-drug synergy prediction (HANSynergy), has been experimentally validated to demonstrate that the heterogeneous graph attention network can extract key node features, efficiently harness the diversity of information, and further enhance network functionality through the incorporation of a multihead attention mechanism. In the comparative experiment, the highest accuracy (Acc) and area under the curve (AUC) are 0.877 and 0.947, respectively, in DrugCombDB_early data set, demonstrating the superiority of HANSynergy over the competing methods. Moreover, protein-protein interactions are important in understanding the mechanism of action of drugs. The heterogeneous attention mechanism facilitates protein-protein interaction analysis. By analyzing the changes of attention weight before and after heterogeneous network training, we investigated proteins that may be associated with drug combinations. Additionally, case studies align our findings with existing research, underscoring the potential of HANSynergy in drug synergy prediction. This advancement not only contributes to the burgeoning field of drug synergy prediction but also holds the potential to provide valuable insights and uncover new drug synergies for combating cancer.


Subject(s)
Drug Synergism , Humans , Databases, Pharmaceutical , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemistry , Computational Biology/methods
8.
J Pharmacol Toxicol Methods ; 127: 107507, 2024.
Article in English | MEDLINE | ID: mdl-38636673

ABSTRACT

The Health and Environmental Sciences Institute (HESI) Cardiac Safety Committee designed and created a publicly accessible database with an initial set of 128 pharmacologically defined pharmaceutical agents, many with known cardiotoxic properties. The database includes specific information about each compound that could be useful in evaluating hypotheses around mechanisms of drug-induced cardiac toxicity or for development of novel cardiovascular safety assays. Data on each of the compounds was obtained from published literature and online sources (e.g., DrugBank.ca and International Union of Basic and Clinical Pharmacology (IUPHAR) / British Pharmacological Society (BPS) Guide to PHARMACOLOGY) and was curated by 10 subject matter experts. The database includes information such as compound name, pharmacological mode of action, characterized cardiac mode of action, type of cardiac toxicity, known clinical cardiac toxicity profile, animal models used to evaluate the cardiotoxicity profile, routes of administration, and toxicokinetic parameters (i.e., Cmax). Data from both nonclinical and clinical studies are included for each compound. The user-friendly web interface allows for multiple approaches to search the database and is also intended to provide a means for the submission of new data/compounds from relevant users. This will ensure that the database is constantly updated and remains current. Such a data repository will not only aid the HESI working groups in defining drugs for use in any future studies, but safety scientists can also use the database as a vehicle of support for broader cardiovascular safety studies or exploring mechanisms of toxicity associated with certain pharmacological modes of action.


Subject(s)
Cardiotoxicity , Databases, Pharmaceutical , Drug-Related Side Effects and Adverse Reactions , Animals , Humans , Cardiotoxicity/etiology , Drug-Related Side Effects and Adverse Reactions/diagnosis , Drug Evaluation, Preclinical/methods , Databases, Factual , Pharmaceutical Preparations
9.
Methods ; 225: 44-51, 2024 May.
Article in English | MEDLINE | ID: mdl-38518843

ABSTRACT

The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells to learn the properties of drug compounds in the DrugBank, aiming to obtain a new and virtual screening compounds database with drug-like properties. Ultimately, a compounds database consisting of 26,316 compounds is obtained by this method. To evaluate the potential of this compounds database, a series of tests are performed, including chemical space, ADME properties, compound fragmentation, and synthesizability analysis. As a result, it is proved that the database is equipped with good drug-like properties and a relatively new backbone, its potential in virtual screening is further tested. Finally, a series of seedling compounds with completely new backbones are obtained through docking and binding free energy calculations.


Subject(s)
Deep Learning , Molecular Docking Simulation , Molecular Docking Simulation/methods , Enzyme Inhibitors/chemistry , Enzyme Inhibitors/pharmacology , Drug Evaluation, Preclinical/methods , Humans , Databases, Pharmaceutical , Neural Networks, Computer , Databases, Chemical
10.
Clin Pharmacol Ther ; 116(3): 716-723, 2024 Sep.
Article in English | MEDLINE | ID: mdl-38493367

ABSTRACT

Pediatric drug dosing is challenged by the heterogeneity of developing physiology and ethical considerations surrounding a vulnerable population. Often, pediatric drug dosing leverages findings from the adult population; however, recent regulatory efforts have motivated drug sponsors to pursue pediatric-specific programs to meet an unmet medical need and improve pediatric drug labeling. This paradigm is further complicated by the pathophysiological implications of obesity on drug distribution and metabolism and the roles that body composition and body size play in drug dosing. Therefore, we sought to understand the landscape of pediatric drug dosing by characterizing the dosing strategies from drug products recently approved for pediatric indications identified using FDA Drug Databases and analyze the impact of body size descriptors (age, body surface area, weight) on drug pharmacokinetics for several selected antipsychotics approved in pediatric patients. Our review of these pediatric databases revealed a dependence on body size-guided dosing, with 68% of dosing in pediatric drug labelings being dependent on knowing either the age, body surface area, or weight of the patient to guide dosing for pediatric patients. This dependence on body size-guided dosing drives the need for special consideration when dosing a drug in overweight and obese patients. Exploratory pharmacokinetic analyses in antipsychotics illustrate possible effects of drug exposure when applying different dosing strategies for this class of drugs. Future efforts should aim to further understand the pediatric drug dosing and obesity paradigm across pediatric age ranges and drug classes to optimize drug development and clinical care for this patient population.


Subject(s)
Antipsychotic Agents , Humans , Child , Antipsychotic Agents/administration & dosage , Antipsychotic Agents/pharmacokinetics , Drug Dosage Calculations , Age Factors , Drug Labeling , Child, Preschool , United States , Adolescent , Infant , Body Surface Area , Body Weight , United States Food and Drug Administration , Dose-Response Relationship, Drug , Databases, Pharmaceutical
11.
Rev. saúde pública (Online) ; 58: 20, 2024. tab, graf
Article in English | LILACS | ID: biblio-1560449

ABSTRACT

ABSTRACT OBJECTIVE To assess regional and national mortality and years of life lost (YLL) related to adverse drug events in Brazil. METHODS This is an ecological study in which death records from 2009 to 2018 from the Mortality Information System were analyzed. Codes from the International Classification of Diseases 10th revision (ICD-10) that indicated drugs as the cause of death were identified. The number of deaths and the YLL due to adverse drug events were obtained. Crude, age- and gender-specific, and age-adjusted mortality rates and YLL rates per 100,000 inhabitants were formed by year, age group, gender, and Brazilian Federative Unit. Rate ratios were calculated by comparing rates from 2009 to 2018. A joinpoint regression model was applied for temporal analysis. RESULTS For the selected ICD-10 codes, a total of 95,231 deaths and 2,843,413 YLL were recorded. Mortality rates from adverse drug events increased by a mean of 2.5% per year, and YLL rates increased by 3.7%. Increases in rates were observed in almost all age groups for both genders. Variations in rates were found between Federative Units, with the highest age-adjusted mortality and YLL rates occurring in the Distrito Federal. CONCLUSIONS The numbers and rates of deaths and YLL increased during the study period, and variations in rates of deaths and YLL were observed between Brazilian Federative Units. Information on multiple causes of death from death certificates can be useful for quantifying adverse drug events and analyzing them geographically, by age and by gender.


Subject(s)
Humans , Male , Female , Cause of Death , Pharmacoepidemiology , Drug-Related Side Effects and Adverse Reactions , Databases, Pharmaceutical
12.
Br J Pharmacol ; 180 Suppl 2: S223-S240, 2023 10.
Article in English | MEDLINE | ID: mdl-38123152

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and nearly 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16179. Nuclear hormone receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Pharmacology , Humans , Ligands , Membrane Transport Proteins , Receptors, G-Protein-Coupled , Receptors, Cytoplasmic and Nuclear
13.
Br J Pharmacol ; 180 Suppl 2: S289-S373, 2023 10.
Article in English | MEDLINE | ID: mdl-38123154

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16176. In addition to this overview, in which are identified 'Other protein targets' which fall outside of the subsequent categorisation, there are six areas of focus: G protein-coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Ion Channels , Humans , Ligands , Receptors, Cytoplasmic and Nuclear , Receptors, G-Protein-Coupled
14.
Br J Pharmacol ; 180 Suppl 2: S1-S22, 2023 10.
Article in English | MEDLINE | ID: mdl-38123153

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16176. In addition to this overview, in which are identified 'Other protein targets' which fall outside of the subsequent categorisation, there are six areas of focus: G protein-coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Pharmacology , Humans , Databases, Factual , Ion Channels , Ligands , Receptors, Cytoplasmic and Nuclear
15.
Br J Pharmacol ; 180 Suppl 2: S23-S144, 2023 10.
Article in English | MEDLINE | ID: mdl-38123151

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.16177. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Receptors, G-Protein-Coupled , Humans , Ligands , Ion Channels/chemistry , Receptors, Cytoplasmic and Nuclear
16.
Br J Pharmacol ; 180 Suppl 2: S374-S469, 2023 10.
Article in English | MEDLINE | ID: mdl-38123156

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and over 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16182. Transporters are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors and enzymes. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Pharmacology , Humans , Ligands , Ion Channels/chemistry , Receptors, G-Protein-Coupled , Receptors, Cytoplasmic and Nuclear
17.
Br J Pharmacol ; 180 Suppl 2: S241-S288, 2023 10.
Article in English | MEDLINE | ID: mdl-38123155

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and nearly 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16180. Catalytic receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, ion channels, nuclear hormone receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Pharmacology , Humans , Ligands , Receptors, G-Protein-Coupled , Ion Channels/chemistry , Receptors, Cytoplasmic and Nuclear
18.
Br J Pharmacol ; 180 Suppl 2: S145-S222, 2023 10.
Article in English | MEDLINE | ID: mdl-38123150

ABSTRACT

The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and over 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16178. Ion channels are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein-coupled receptors, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.


Subject(s)
Databases, Pharmaceutical , Pharmacology , Humans , Ion Channels/chemistry , Ligands , Receptors, G-Protein-Coupled , Databases, Factual
19.
Pharm. care Esp ; 25(4): 22-37, 14-08-2023. tab, graf
Article in Spanish | IBECS | ID: ibc-224036

ABSTRACT

Introducción: La fenilcetonuria es el trastorno hereditario más frecuente del metabolismo de los aminoácidos y su abordaje suele centrarse en die-tas restringidas en fenilalanina, un aminoácido presente en el edulcorante aspartamo habitualmente usado como excipiente en tecnología farmacéutica. Objetivo: El objetivo principal es la revisión de los medicamentos sin receta comercializados en España hasta marzo de 2023 y que contienen aspartamo en su composición. Método: Se realizó una revisión en la base de datos BOT plus de todos los medicamentos comercializados en España que contienen aspartamo. Se seleccionaron solo los MSR. Se consultaron las fichas técnicas en el Centro de información online de medicamentos de la AEMPS (CIMA), y los datos obtenidos se registraron en una tabla. Resultados: Se obtuvieron 570 medicamentos; 58 eran MSR. Cuando exista petición de MSR con aspartamo en pacientes con fenilcetonuria, en el SIF, tras su evaluación, en el 100% de los casos, el farmacéutico aplicando el Servicio de Indicación Farmacéutica podría indicar un MSR alternativo, con el mismo principio activo pero sin aspartamo como excipiente. Conclusiones: La actuación del farmacéutico comunitario para aplicar el SIF es muy importante en pacientes con fenilcetonuria. Existen medicamentos que no requieren prescripción y se pueden indicar en estos pacientes. El farmacéutico debe tener a su disposición las herramientas necesarias que le faciliten el SIF con este tipo de enfermos. (AU)


Introduction: Phenylketonuria is the most common inherited disorder of amino acid metabolism and its management usually focuses on diets restricted in phenylalanine, an amino acid present in the sweet-ener aspartame commonly used as an excipient in pharmaceutical technology. Objective: The main objective is the review of non-prescription medicines marketed in Spain until March 2023 and that contain aspartame in their composition.Methods: A review of all medicines marketed in Spain containing aspartame was carried out in the BOT plus database. Only MSRs were selected. The data sheets were consulted at the AEMPS online medicines information centre (CIMA), and the data obtained were recorded in a table.Results: 570 medicines were obtained; 58 were MSRs. When there is a request for MSRs with aspartame in patients with phenylketonuria, in the SIF, after evaluation, in 100% of the cases, the pharmacist applying the Pharmaceutical Indication Service could indicate an alternative MSR, with the same active ingredient but without aspartame as an excipient.Conclusions: The action of the community phar-macist to apply the SIF is very important in patients with phenylketonuria. There are medicines that do not require a prescription and can be prescribed for these patients. Pharmacists should have the necessary tools at their disposal to facilitate the SIF with this type of patient. (AU)


Subject(s)
Humans , Drug Approval , Databases, Pharmaceutical/classification , Nonprescription Drugs/analysis , Nonprescription Drugs/pharmacology , Phenylketonurias/drug therapy , Aspartame/pharmacology , Pharmaceutic Aids/analysis , Pharmaceutic Aids/pharmacology , Patient Safety , Spain
20.
Galicia clin ; 83(1): 1-6, Jan-Feb-Mar. 2022. graf, tab
Article in Spanish | IBECS | ID: ibc-203998

ABSTRACT

Introduction: The high prevalence of inappropriate medication use andits important health consequences for health require specific and agiletools to detect and avoid it.The objective of this work was to elaborate a list of medications toavoid in Primary Care and to apply it on the polymedicated patients ofa Primary Care assistance service.Methods: In the Database of the Spanish General Council of OfficialAssociations of Pharmacists (BOT-Plus) the status and availability ofeach of the 93 MAE of the Prescrire 2019 List was checked. The list ofmedications to be avoided in Primary Care was drawn up with thosethat were marketed in Spain and excluded those that were not financedand those for exclusive hospital use.With the list of medicines to avoid in Primary Care, a retrospectiveanalysis was made of all the prescription reports of polimedicated >10medications for 2017 in a Primary Care services (N=262) in 5 healthcenters. Frequency analysis, central tendency measures and dispersionwere carried out; they were estimated [CI: 95%] and X or Fisher’s exactwas used to determine the association between variables and logisticregression analysis.Results: A prevalence of polymedicated drugs of 1.2% was observed,with a mean age of 71.7 years (DT± 12.4) and a mean prescription of12 drugs (DT±1.7).The list of medications to be avoided in PC included 45 active ingredients. The 50.4% of the polymedicated had at least one drug to avoidand an average age of 68.5 years (DT±11.8). Sex was a risk factor forinappropriate prescription, the fact of being a woman increases withan OR=1.8 (IC95%=1, 3-3.0) the probability of having some medicinesto avoid. The most commonly used drugs to avoid were: duloxetine,sitagliptin and olmesartan. ...


Introduction: La alta prevalencia del uso de medicación inadecuada ysus importantes consecuencias para la salud requieren herramientasespecíficas y ágiles que ayuden a detectarla y evitarla.Objetivo de este trabajo fue elaborar un listado de medicamentos aevitar en AP y aplicarlo en pacientes polimedicados de un servicio asistencial de Atención Primaria (AP).Métodos: En la Base de datos del Consejo General de Colegios Oficialesde Farmacéuticos español (BOT-Plus) se comprobó el estado y disponibilidad de cada uno de los 93 medicamentos del Listado Prescrire2019. Se elaboró el Listado de medicamentos a evitar en AP con aquellos que estaban comercializados en España y se excluyeron los que noestaban financiados y los de uso exclusivo hospitalario.Con el listado de medicamentos a evitar en AP se hizo un análisis retrospectivo de todos (N=262) los informes de prescripción de polimedicados >10 medicamentos del año 2017 en un servicio asistencial deAP (5 centros de salud). Se realizó análisis de frecuencias, medidasde tendencia central y dispersión; se estimaron (IC 95%) y se utilizóX o exacta de Fisher para determinar la asociación entre variables yanálisis de regresión logística.Resultados: Se observó una prevalencia de polimedicados de 1,2%, conuna media de edad de 71,7 ± 12,4 años y una media de prescripcionesde 12 ±1,7 medicamentos.El listado de medicamentos a evitar en AP incluyó 45 principios activos.Los fármacos a evitar más usados han sido: duloxetina, sitagliptina yolmesartán. El 50,4% de los polimedicados tenían al menos un medicamento a evitar y una edad media de 68,5±11,8 años. El sexo fue unfactor de riesgo de prescripción inadecuada, el hecho de ser mujerincrementa con un OR=1,8 (IC 95%=1,3-3,0) la probabilidad de medicamentos a evitar. ...


Subject(s)
Humans , Primary Health Care , Polypharmacy , Drug Utilization/statistics & numerical data , Databases, Pharmaceutical , Alternism
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