Gliquidone 30mg tablets
Gliquidone is a sulfonylurea drug used to treat diabetes mellitus type 2.
Official documents, adverse reaction reporting, and safety monitoring
Report a side effect
Submit a Yellow Card report to the MHRA
Safety monitoring data
Yellow Card reports
The MHRA Yellow Card scheme collects reports of suspected side effects from healthcare professionals and patients. View the Drug Analysis Profile (iDAP) for real-world adverse reaction data.
View Drug Analysis Profile
Suspected adverse reactions reported for Gliquidone
Browse all iDAP reports
Interactive Drug Analysis Profiles for all medicines
Report a side effect
Submit a Yellow Card report to the MHRA
Data from the MHRA Yellow Card scheme. A reported reaction does not necessarily mean the medicine caused it. Contains public sector information licensed under the Open Government Licence v3.0.
EudraVigilance
The European Medicines Agency (EMA) collects suspected adverse reaction reports from across the EU/EEA through the EudraVigilance system. Search for safety data on this medicine.
View EudraVigilance report
Suspected adverse reactions reported for Gliquidone
About EudraVigilance
Learn about EU pharmacovigilance and safety monitoring
EudraVigilance data is published by the European Medicines Agency (EMA). A suspected adverse reaction is not necessarily caused by the medicine.
1 branded products available
WHO defined daily dose (DDD)
60 mg
Not a recommended dose. The DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults. It is a statistical measure used for research and comparison purposes only.
Source: WHO Collaborating Centre for Drug Statistics Methodology, distributed via the NHS dm+d supplementary BNF/ATC mapping files (NHSBSA). Contains public sector information licensed under the Open Government Licence v3.0.
Therapeutically similar medicines
Similarity is based on WHO Anatomical Therapeutic Chemical (ATC) classification and on a factual NHS dm+d therapeutic-grouping code prefix. Source data: NHS dm+d via TRUD (OGL v3.0), WHO ATC/DDD Index.
NHS prescribing volume and spending trends
Check stock at pharmacies and supply information
Pharmacy stock checkers
Search for this medicine at major UK pharmacy chains. These links open the retailer's own website — results depend on their current online catalogue.
Supply & safety information
Official UK regulator monitoring and safety alerts
Pharmacy links redirect to the retailer's own search and do not represent real-time stock levels. Shortage and safety information sourced from MHRA drug safety updates (gov.uk, Crown Copyright under OGL v3.0).
Codes for healthcare professionals and prescribing systems
These codes are used by healthcare IT systems and prescribers to identify this medicine.
NHS UK identifiers
Browse tools
SNOMED CT and dm+d codes from NHS TRUD (Technology Reference data Update Distribution), licensed under the Open Government Licence v3.0. BNF code shown is the factual mapping value distributed by NHS Business Services Authority (NHSBSA) in the dm+d supplementary file under OGL v3.0; it is not affiliated with, nor licensed from, the publishers of the British National Formulary. ATC codes from the WHO Collaborating Centre for Drug Statistics Methodology (whocc.no).
Active and completed clinical studies from ClinicalTrials.gov
Source: ClinicalTrials.gov, a database of the U.S. National Library of Medicine (NLM), National Institutes of Health (NIH). Data accessed via ClinicalTrials.gov API v2. Trial information is provided for research purposes and does not constitute medical advice.
Academic studies and reviews for this medicine's active substance
Showing the 50 most relevant studies.
Reviews & meta-analyses: 3 · 1992–2026
Showing the 50 most relevant studies, sorted by most relevant.
Altabas V, Marinković Radošević J
2025
Background/Objectives: Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder characterized by insulin resistance, impaired insulin secretion, and chronic hyperglycemia. Recent studies have identified microRNAs (miRNAs), a class of small non-coding RNAs that regulate gene expression at the post-transcriptional level, as modulators of pathways involved in T2DM pathophysiology. Dysregulated miRNA expression has been detected in various samples collected from patients with T2DM, implicating these molecules in disease onset and progression. Methods: We systematically searched PubMed, Scopus, and Web of Science for studies published from the earliest available records to 18 August 2025 using the following Boolean search terms: "miRNA AND gliclazide", "miRNA AND glibenclamide", "miRNA AND gliquidone", "miRNA AND glimepiride", "mirRNA AND metformin", "miRNA AND pioglitazone", "miRNA AND rosiglitazone", "miRNA AND sitagliptin", "miRNA AND vildagliptin", "miRNA AND alogliptin", "miRNA and saxagliptin", "miRNA AND linagliptin", "miRNA AND liraglutide", "miRNA and dulaglutide", "miRNA AND semaglutide", "miRNA AND tirzepatide", "miRNA AND lixisenatide", "miRNA AND empagliflozin", "miRNA AND dapagliflozin", miRNA AND insulin glargine", "miRNA AND insulin detemir", "miRNA AND insulin degludec", "miRNA AND insulin aspart", "miRNA AND insulin glulisine", and "miRNA AND insulin lispro". Additionally, gray literature was searched in ClinicalTrials.gov, the EU Clinical Trials Register (EudraCT), and the ISRCTN Registry to identify unpublished studies. Studies were eligible for inclusion if they were clinical interventional studies assessing the impact of currently available antidiabetic treatments on miRNA expression. Only articles published in English were considered. The risk of bias was evaluated using the RoB2 (Risk of Bias 2) and ROBINS-I (Risk Of Bias In Non-randomized Studies-of Interventions) tools. Study characteristics and major findings were tabulated. Results: A total of 1263 manuscripts was identified initially. After removing duplicates, 726 articles remained for further screening. Ultimately, 17 manuscripts reporting interventional clinical trials on the effects of antidiabetic treatment on miRNA were included, encompassing a total of 1093 patients. Key findings included treatment-associated changes in miRNA expression and their potential utility for the prediction of clinical outcomes. Conclusions: Current evidence supports the hypothesis that antidiabetic treatments modulate miRNA expression, with some findings showing predictive value for metabolic outcomes. However, the available data remain limited and of low grade of certainty, and further large-scale clinical studies are needed to provide deeper insights into these associations.
Abstract licence: CC BY
W. Malaisse
Drugs in R & D, 2006
Zeba A, Sekar K, Ganjiwale A
2023
The Dengue virus M protein is a 75 amino acid polypeptide with two helical transmembranes (TM). The TM domain oligomerizes to form an ion channel, facilitating viral release from the host cells. The M protein has a critical role in the virus entry and life cycle, making it a potent drug target. The oligomerization of the monomeric protein was studied using ab initio modeling and molecular dynamics (MD) simulation in an implicit membrane environment. The representative structures obtained showed pentamer as the most stable oligomeric state, resembling an ion channel. Glutamic acid, threonine, serine, tryptophan, alanine, isoleucine form the pore-lining residues of the pentameric channel, conferring an overall negative charge to the channel with approximate length of 51.9 Å. Residue interaction analysis (RIN) for M protein shows that Ala94, Leu95, Ser112, Glu124, and Phe155 are the central hub residues representing the physicochemical interactions between domains. The virtual screening with 165 different ion channel inhibitors from the ion channel library shows monovalent ion channel blockers, namely lumacaftor, glipizide, gliquidone, glisoxepide, and azelnidipine to be the inhibitors with high docking scores. Understanding the three-dimensional structure of M protein will help design therapeutics and vaccines for Dengue infection.
Abstract licence: CC BY
Mohamed El-Araby, Sanaa A. El-Gizawy, Shimaa M. Ashmawy, et al.
Journal of Drug Delivery Science and Technology, 2024
Tian Tang, Ying Zhang, Xinrui Xing, et al.
Journal of Pharmaceutical Analysis, 2025
Chenxia Yang, Qinqin Li, Fang Hu, et al.
Molecular Pharmacology, 2024
- Diabetes Mellitus, Type 2
- Sulfonylurea Compounds
- Brugada Syndrome
Citlali Vázquez, Rusely Encalada, Isabel Jiménez-Galicia, et al.
Pharmaceuticals, 2024
Infection with the protozoan parasite Trypanosoma cruzi causes human Chagas disease. Benznidazole (BNZ) and nifurtimox are the current drugs for the treatment; however, they induce severe adverse side effects in patients; therefore, there is a need to improve the treatment effectiveness and efficiency of these drugs for its safer use. Background/Objective: Glyburide, glipizide, and gliquidone, hypoglycemic drugs for diabetes treatment, were previously predicted to bind to dihydrofolate reductase-thymidylate synthase from T. cruzi by in silico docking analysis; they also showed antiproliferative effects against T. cruzi epimastigotes, the stage of the insect vector. In the present study, the potential parasiticidal effect of these antidiabetic drugs was tested in monotherapy and bi-therapy with BNZ in human cells in vitro and in animals. Methods: Evaluation was performed in (a) a model of in vitro infection of T. cruzi trypomastigotes using human fibroblasts as host cells and (b) in mice infected with T. cruzi. Results: The antidiabetic drugs in monotherapy showed antiparasitic effects in preventing infection progression (trypomastigotes release), with an IC50 of 8.4–14.3 µM in comparison to that of BNZ (0.26 µM) in vitro. However, in bi-therapy, the presence of just 0.5 or 1 µM of the antidiabetics decreased the BNZ IC50 by 5–10 times to 0.03–0.05 µM. Remarkably, the antidiabetic drugs in monotherapy decreased the infection in mice by 40–60% in a similar extent to BNZ (80%). In addition, the combination of BNZ plus antidiabetics perturbed the antioxidant metabolites in epimastigotes. Conclusions: These results identified antidiabetics as potential drugs in combination therapy with BNZ to treat T. cruzi infection.
Abstract licence: CC BY 4.0
Zhou J, Zhang Q, Guan J, et al.
2025
- Piperidines
- Pyrimidines
- Pyrroles
BackgroundTofacitinib is an orally administered Janus kinase (JAK) inhibitor that has demonstrated significant efficacy in the treatment of rheumatoid arthritis. This study aimed to investigate the effects of gliquidone and linagliptin, two hypoglycemic agents on the pharmacokinetics of tofacitinib in vitro and in vivo.MethodsThe mechanism of drug-drug interaction was studied in vitro using a murine liver microsome incubation system and in vivo by administering gliquidone and linagliptin orally to rats pretreated with various concentrations of tofacitinib. This study used waters ACQUITY UPLC I-Class/Xevo TQD ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometer. Furthermore, molecular docking was performed to simulate the interaction using computer simulations.ResultsGliquidone and linagliptin inhibited the metabolism of tofacitinib by heparanase in vitro with IC50 values of 1.140 μM and 4.064 μM, respectively. Co-administration of gliquidone significantly increased the AUC(0-t) of tofacitinib by approximately 43.3%, accompanied by a 45.1% increase in Cmax and a 27.5% reduction in clearance (CLz/F). In contrast, linagliptin exhibited a more potent inhibitory effect, raising the AUC(0-t) approximately 4.4-fold, enhancing the Cmax by 2.86-fold, and decreasing clearance to 25.8% of the control level. These findings suggest that while both gliquidone and linagliptin significantly enhance the systemic exposure of tofacitinib, linagliptin demonstrates a markedly more significant inhibitory effect on tofacitinib's metabolism and elimination.ConclusionGliquidone and linagliptin significantly altered the pharmacokinetics of tofacitinib in vitro and in vivo. This study demonstrated the drug-drug interactions between linagliptin, gliquidone, and tofacitinib, highlighting the need for clinical attention to this possibility.
Abstract licence: CC BY-NC
Xi-Hui Qiu, Bo Liu, Panpan Ye, et al.
Journal of Clinical Pharmacy and Therapeutics, 2024
Cisplatin (CDDP) can combat various types of cancers, employing a multifaceted approach against these malignant diseases. Despite its efficacy, resistance to CDDP remains a significant clinical challenge, often resulting in treatment failure and disease progression. Currently, efforts are underway to unravel the mechanisms of CDDP drug resistance in cancer treatment. The elevated presence of glutathione S‐transferase pi‐1 (GSTP1‐1) within tumor cells plays a pivotal role in the development of resistance toward the effects of CDDP. GSTP1‐1 contributes to detoxification by conjugating glutathione (GSH) to CDDP, reducing its accumulation and effectiveness in the tumor cells. In this study, the efficacy of gliquidone, an antidiabetic drug, demonstrated its capacity to impede tumor cell proliferation in both lung cancer A549 cell lines and A549/CDDP cell lines. This was achieved by suppressing the expression of GSTP1‐1 within tumor cells (IC50: 16.8 ± 0.8 μM). Furthermore, through the establishment of a nude mouse model featuring lung adenocarcinoma A549/CDDP cell transplantation tumors, gliquidone demonstrated a significant therapeutic effect on the mice tumors, while avoiding discernible side effects. These findings suggest that gliquidone could potentially be repurposed as an adjunct therapy in CDDP‐resistant lung cancer.
Abstract licence: CC BY 4.0
M. Shamona, C. James
Journal of Molecular Liquids, 2024
Sources: aggregated from Europe PMC (EMBL-EBI), OpenAlex, Crossref, PubMed and other open scholarly databases. Retracted articles are excluded. Study information is provided for research purposes and does not constitute medical advice.
Pharmacology and chemical data from DrugBank
Key facts
Drug status
Approved
Major interactions
None known
Half-life
8 hours
Mechanism
The mechanism of action of gliquidone in lowering blood glucose appears to be de…
Food interactions
None known
Human targets
3 targets
Data: DrugBank · CC BY-NC 4.0
Pharmacokinetics at a glance
Half-life
8 hours
Pharmacokinetic data: DrugBank · CC BY-NC 4.0
Known interactions with other medications. Always consult a healthcare professional.
Showing 50 of 1040 interactions
How the body processes this drug — absorption, distribution, metabolism, and elimination
Proteins and enzymes this drug interacts with in the body
PMID:20558321 PMID:21836131 PMID:24700710 PMID:28842488
Their voltage dependence is regulated by the concentration of extracellular potassium; as external potassium is raised, the voltage range of the channel opening shifts to more positive voltages .
PMID:20558321 PMID:21836131 PMID:24700710 PMID:28842488
The inward rectification is mainly due to the blockage of outward current by internal magnesium. This channel is activated by internal ATP and can be blocked by external barium .
PMID:20558321 PMID:21836131 PMID:24700710 PMID:28842488
Can form a sulfonylurea-sensitive but ATP-insensitive potassium channel with ABCC9 (By similarity)
PMID:8995301
Their voltage dependence is regulated by the concentration of extracellular potassium; as external potassium is raised, the voltage range of the channel opening shifts to more positive voltages .
PMID:8995301
The inward rectification is mainly due to the blockage of outward current by internal magnesium. Can be blocked by extracellular barium and cesium .
PMID:8995301
In the kidney, together with KCNJ16, mediates basolateral K(+) recycling in distal tubules; this process is critical for Na(+) reabsorption at the tubules PMID:24561201
Enzymes involved in drug metabolism — important for understanding drug interactions
ATC A10BB08
Chemical identifiers
CAS, UNII, InChI Key and database cross-references
Show
Chemical identifiers
CAS, UNII, InChI Key and database cross-references
Linked compound data from DrugBank Open Data (CC BY-NC 4.0)
Gliquidone
Additional database identifiers
ChemSpider
82719
BindingDB
50248247
ZINC
ZINC000001482077
HUGO Gene Nomenclature Committee (HGNC)
HGNC:59
GenAtlas
ABCC8
GeneCards
ABCC8
GenBank Gene Database
L78243
GenBank Protein Database
1374919
Guide to Pharmacology
2594
UniProt Accession
ABCC8_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:6269
GenAtlas
KCNJ8
GeneCards
KCNJ8
GenBank Gene Database
D50312
UniProt Accession
KCNJ8_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:6256
GeneCards
KCNJ10
Guide to Pharmacology
438
UniProt Accession
KCJ10_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:2623
GenAtlas
CYP2C9
GeneCards
CYP2C9
GenBank Gene Database
AY341248
Guide to Pharmacology
1326
UniProt Accession
CP2C9_HUMAN
DrugBank citations
If you use DrugBank data in your research, please cite the following publications:
Show earlier publications
Structured knowledge from the free knowledge base
ATC classifications (Wikidata)
Linked open data from Wikidata (Q5569924), a free and open knowledge base operated by the Wikimedia Foundation. Data is available under the Creative Commons CC0 1.0 Public Domain Dedication. WHO INN from the World Health Organization.