Spectinomycin 2g powder and solvent for suspension for injection vials
Requires a prescription from a doctor or prescriber
An antibiotic produced by Streptomyces spectabilis.
Official documents, adverse reaction reporting, and safety monitoring
Report a side effect
Submit a Yellow Card report to the MHRA
Official medicine documents
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 Spectinomycin
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 Spectinomycin
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
MHRA licensed products
View all licensed products for Spectinomycin on the MHRA register
Trobicin 2g powder and solvent for suspension for injection vials
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.
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 all 21 studies.
Reviews & meta-analyses: 2 · 1999–2026
Showing all 21 studies, sorted by most relevant.
Mohammad Hosseini Hooshiar, Mohammad Sholeh, Masoumeh Beig, et al.
Frontiers in Pharmacology, 2024
Background: (NG) is a significant public health concern. Objective: The objective of our study was to assess global AMR rates and test them both temporally and geographically. Methods: We conducted a systematic search of relevant reports from international databases up to 2021. The R statistical package was used for all statistical analyses. Results: A total of 225 articles were analyzed, and 432,880 NG isolates were examined. The weighted pooled resistance (WPR) rate of different antibiotics was as follows: ciprofloxacin, 51.6%; tetracycline, 45.4%; trimethoprim/sulfamethoxazole, 42.4%; chloramphenicol, 4.1%; kanamycin, 2.1%; gentamicin, 0.6%; and spectinomycin, 0.3%. The resistance to spectinomycin, gentamicin, and kanamycin decreased over time. Significant differences in antibiotic resistance rates were found between the countries. Conclusion: Our findings reveal a continuous increase in resistance to some antibiotics (tetracycline and ciprofloxacin) historically used for gonorrhea, even after discontinuation. However, encouraging trends of decreasing resistance to spectinomycin, gentamicin, and kanamycin were observed. Continued global monitoring of AMR profiles in NG isolates is essential for informing appropriate treatment strategies and mitigating the threat of untreatable gonorrhea.
Abstract licence: CC BY
Mengistie Yirsaw Gobezie, Nuhamin Alemayehu Tesfaye, Tewodros Solomon, et al.
Frontiers in Microbiology, 2024
Introduction Neisseria gonorrhea ( N. gonorrhea ) represents a significant causative agent of sexually transmitted infections (STIs), posing considerable global health challenges. Despite the presence of diagnostic tools and empirically guided therapies, the escalating AMR of N. gonorrhea continues to pose a threat. This study aims to assess the prevalence of N. gonorrhea among STI suspected patients in Ethiopia and explore the patterns of AMR to common antimicrobials. Methods Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review and meta-analysis. A thorough search of electronic databases from July 11 to July 24, 2023, identified 10 eligible studies. Data were extracted and analyzed using a random-effects model. Heterogeneity was assessed using the I 2 statistic, and publication bias was evaluated through Egger’s regression test and funnel plots. Results The overall pooled prevalence of N. gonorrhea among STI suspected patients in Ethiopia was 20% (95% confidence interval (CI): 8–30, I 2 = 99.0%; p -value <0.001). Substantial regional variations were observed, with the highest prevalence in Addis Ababa (55, 95% CI: 45–65) and the lowest in the Southern Nations, Nationalities, and Peoples’ Region (SNNPR) (4, 95% CI: 2–8). The pooled prevalence of AMR to ciprofloxacin, ceftriaxone, azithromycin, benzylpenicillin, tetracycline, and spectinomycin was 37, 9, 10, 79, 93, and 2%, respectively. Significant heterogeneity existed between studies (I 2 = 99.0%; p value <0.001). Publication bias, identified through funnel plot examination and Egger’s regression test ( p < 0.001), execution of trim and fill analysis resulted in an adjusted pooled prevalence of (6.2, 95% CI: −6.8 to 19.3). Conclusion The prevalence of N. gonorrhea among STI suspected patients in Ethiopia is alarming, particularly in specific regions. The elevated AMR to ciprofloxacin underscores the immediate need for alternative treatment options and enhanced surveillance systems. Future initiatives should prioritize strengthening laboratory capacities and implementing targeted interventions to curtail N. gonorrhea transmission and prevent the emergence of AMR. Systematic Review Registration https://www.crd.york.ac.uk/prospero , identifier CRD42023459698.
Abstract licence: CC BY
N. Clark, Ø. Olsvik, J. Swenson, et al.
Antimicrobial Agents and Chemotherapy, 1999
- Amino Acid Sequence
- Base Sequence
- Drug Resistance, Microbial
M. A. Borovinskaya, S. Shoji, J. Holton, et al.
ACS chemical biology, 2007
- Spectinomycin
- Anti-Bacterial Agents
- Escherichia coli
G. Chalmers, Ashley C Cormier, M. Nadeau, et al.
Veterinary microbiology, 2017
- Spectinomycin
- Anti-Bacterial Agents
- Cephalosporins
Jena C, Deolankar S, Matange N
2025
- Spectinomycin
- Adaptation, Physiological
- Anti-Bacterial Agents
Tewolde R, Thombre R, Farley C, et al.
2025
Background: Antimicrobial resistance (AMR) in Legionella pneumophila is emerging as a concern, particularly with resistance to macrolides and fluoroquinolones. Although clinically significant resistance in Legionella pneumophila remains uncommon, systematic genomic surveillance using whole-genome sequencing (WGS) is needed to anticipate treatment failure as metagenomic diagnostics move toward routine use. Objectives: We assessed the UK Health Security Agency AMR pipeline for predicting resistance in L. pneumophila by analysing 522 L. pneumophila isolates from England and Wales (2020–2023) together with nine database sequences that carry confirmed 23S rRNA mutations conferring high-level azithromycin resistance. The objective of the present study was to examine the presence of antimicrobial resistance genes (ARGs) in L. pneumophila isolates and to determine whether they exhibited phenotypic resistance through minimum inhibitory concentration (MIC) testing. Methods: Serogroups (sgs) were determined using an in-house qPCR assay, and L. pneumophila non-sg1 isolates were serogrouped using the Dresden monoclonal antibody (mAb) typing method. Sequence types were determined using the standard sequence-based typing method by Sanger sequencing. WGS reads were screened against standard AMR databases to identify resistance genes and resistance-mediating mutations. Agar dilution measured MICs for azithromycin, erythromycin, ampicillin, levofloxacin, tetracycline and spectinomycin in isolates possessing the blaOXA-29, lpeAB or aph(9)-Ia gene. Results: AMR screening detected lpeAB, two allelic β-lactamase variants (blaOXA-29 and blaLoxA) and aph(9)-Ia in 165 of the 522 L. pneumophila isolates, while all high-azithromycin MIC reference sequences contained the expected 23S mutation. Only lpeAB was associated with a significant twofold elevation in macrolide MICs. Neither β-lactamase variant increased ampicillin MICs, and aph(9)-Ia carriage did not correlate with higher spectinomycin MICs. Conclusions: Advanced genomic analytics can now deliver timely therapeutic guidance, yet database-flagged genes may not translate into phenotypic resistance. Continuous pairing of curated mutation catalogues with confirmatory testing remains essential for distinguishing clinically actionable determinants such as 23S mutations and lpeAB from silent markers like blaOXA-29 and aph (9)-Ia.
Abstract licence: CC BY
Zhang R, Qi Y, Peng H, et al.
2025
Objective: Neisseria gonorrhoeae ( N . gonorrhoeae) is responsible for the sexually transmitted infection (STI) gonorrhea, which has an estimated global annual incidence of 82.4 million cases among adults. The recommended first-line treatment typically involves a single-dose systemic therapy, comprising injectable ceftriaxone and oral azithromycin. Nonetheless, the first-line treatment failures caused by antimicrobial resistance represent a major global public health concern, threatening the efficacy of current gonorrhea treatments and highlighting the urgent need for the development of alternative therapeutic approaches. Methods: A total of 54 clinical strains of N. gonorrhoeae were collected in Nanchang City, 2021. To assess the efficacy of antibiotics and chelerythrine chloride, we determined the minimum inhibitory concentrations (MICs) using agar dilution and broth microdilution methods, respectively. To explicitly evaluate the potential for resistance induction, the ATCC49226 strain was subjected to continuous passaging for 30 days in sub-MIC concentrations of chelerythrine chloride, with MIC assessments every 5 days. Results: In clinical samples, antimicrobial resistance was observed for penicillin (67.27%), tetracycline (81.82%), ciprofloxacin (98.18%), azithromycin (5.45%), and spectinomycin (0%), with decreased susceptibility for ceftriaxone (16.36%) and cefixime (20.00%). High-throughput screening of a natural product library identified chelerythrine chloride as exhibiting significant inhibitory activity against N. gonorrhoeae , including strains with decreased susceptibility to cephalosporins. The MIC range was 0.002– 8 mg/L, with both the MIC 50 and MIC 90 values at 8 mg/L. Furthermore, N. gonorrhoeae did not develop resistance, maintaining a stable MIC of 4 mg/L over a 30-day treatment period. Conclusion: In this study, we have established a novel association between chelerythrine chloride and N. gonorrhoeae , demonstrating for the first time its preliminary efficacy in eradicating multidrug-resistant strains of N. gonorrhoeae . Considering the significant resistance challenges posed by N. gonorrhoeae . chelerythrine chloride emerges as a promising antibacterial agent with substantial potential for clinical development. Keywords: N. gonorrhoeae , antimicrobial resistance, chelerythrine chloride, antimicrobial agent
Abstract licence: CC BY-NC
Xiangying Xiong, Ruifang Chen, Junxiang Lai
BMC Genomics, 2023
- Streptococcus iniae
- Streptococcal Infections
- Anti-Bacterial Agents
Abstract Background Streptococcus iniae is an important fish pathogen that cause significant economic losses to the global aquaculture industry every year. Although there have some reports on the genotype of S.iniae and its relationship with virulence, no genome-scale comparative analysis has been performed so far. In our previous work, we characterized 17 isolates of S.iniae from Trachinotus ovatus and divided them into two genotypes using RAPD and rep-PCR methods. Among them, BH15-2 was classified as designated genotype A (in RAPD) and genotype 1 (in rep-PCR), while BH16-24 was classified as genotype B and genotype 2. Herein, we compared the differences in growth, drug resistance, virulence, and genome between BH15-2 and BH16-24. Results The results showed that the growth ability of BH16-24 was significantly faster than that of BH15-2 at the exponential stage. Antimicrobial tests revealed that BH15-2 was susceptible to most of the tested antibiotics except neomycin and gentamycin. In contrast, BH16-24 was resistant to 7 antibiotics including penicillin, sulfasomizole, compound sulfamethoxazole tablets, polymyxin B, spectinomycin, rifampin and ceftazidime. Intraperitoneal challenge of T.ovatus , showed that the LD 50 value of BH15-2 was 4.0 × 10 2 CFU/g, while that of BH16-24 was 1.2 × 10 5 CFU/g. The genome of S.iniae BH15-2 was 2,175,659 bp with a GC content of 36.80%. Meanwhile, the genome of BH16-24 was 2,153,918 bp with a GC content of 36.83%. Comparative genome analysis indicated that compared with BH15-2, BH16-24 genome had a large-scale genomic inversion fragment, at the location from 502,513 bp to 1,788,813 bp, resulting in many of virulence and resistance genes differentially expression. In addition, there was a 46 kb length, intact phage sequence in BH15-2 genome, which was absent in BH16-24. Conclusion Comparative genomic studies of BH15-2 and BH16-24 showed that the main difference is a 1.28 Mbp inversion fragment. The inversion fragment may lead to abnormal expression of drug resistant and virulence genes, which is believed to be the main reason for the multiple resistance and weakened virulence of BH16-24. Our study revealed the potential mechanisms in underlying the differences of multidrug resistance and virulence among different genotypes of S.iniae .
Abstract licence: CC BY
Minglin Zhang, Tong Liu, Lijun Luo, et al.
Scientific Reports, 2025
- Necroptosis
- Inflammatory Bowel Diseases
- Pyroptosis
PANoptosis is one of several modes of programmed cell death (PCD) and plays an important role in many inflammatory and immune diseases. The role of PANoptosis in inflammatory bowel disease (IBD) is currently unknown. Differentially expressed PANoptosis-related genes (DE-PRGs) were identified, and pathway enrichment analyses were performed. LASSO regression model construction, a nomogram model, calibration curves, ROC and DCA curves were used to evaluate the predictive value of the model. Predicts transcription factors (TFs) and small-molecule drugs of DE-PRGs were analysed. Model genes and immuno-infiltration were analysed. The PANoptosis features of IBD include 12 genes: OGT, TLR2, GZMB, TLR4, PPIF, YBX3, CASP5, BCL2L1, CASP6, MEFV, GSDMB and BAX. The enrichment analysis suggested that these genes were related to TNF signalling, NF-κB, pyroptosis and necroptosis. Machine learning identified three model genes: OGT, GZMB and CASP5. The nomogram model, calibration curves, ROC and DCA curves have strong predictive value. Immuno-infiltration analysis revealed that immune cell infiltration was increased in patients with IBD, and the model genes were closely related to the infiltration of various immune cells. The TFs associated with DE-PRGs were RELA, NFKB1, HIF1A, TP53 and SP1. In addition, the Connectivity Map (CMap) database identified the top 10 small-molecule compounds, including buspirone, chloroquine, spectinomycin and chlortetracycline. This study indicate that DE-PRGs model genes have good predictive ability for IBD. Moreover, PANoptosis may mediate the process of IBD through TNF signalling, NF-κB, pyroptosis, necroptosis and immune mechanisms. These results present a new horizon for the research and treatment of IBD.
Abstract licence: CC BY-NC-ND
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
1 to 3 hours
Mechanism
Spectinomycin is an inhibitor of protein synthesis in the bacterial cell; the si…
Food interactions
None known
Human targets
None mapped
Data: DrugBank · CC BY-NC 4.0
Pharmacokinetics at a glance
Absorption
Half-life
1 to 3 hours
Protein binding
Pharmacokinetic data: DrugBank · CC BY-NC 4.0
Known interactions with other medications. Always consult a healthcare professional.
Showing 50 of 56 interactions
How the body processes this drug — absorption, distribution, metabolism, and elimination
ATC J01XX04
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)
Spectinomycin
Additional database identifiers
Drugs Product Database (DPD)
11211
Drugs Product Database (DPD)
8567
ChemSpider
14785
PDB
SCM
ZINC
ZINC000053006806
GenBank Gene Database
V00355
GenBank Protein Database
43010
UniProt Accession
RS12_ECOLI
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 (Q416154), 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.