Muromonab-CD3 solution for injection 5mg/5ml ampoules
Requires a prescription from a doctor or prescriber
Murine monoclonal antibody specific to CD3 T-cell lymphocyte antigens.
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1 branded products available
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.
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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 12 studies.
Reviews & meta-analyses: 5 · 1989–2026
Showing all 12 studies, sorted by most relevant.
Yang Y, Song Y, Liu F, et al.
2025
- Carcinoma, Basal Cell
- Basal Cell Carcinoma
- Carcinoma, Squamous Cell
Studies have shown that patients who undergo heart transplantation (HTx) are at an increased risk for developing skin cancer. This condition can add physiological and psychological burden to patients. Therefore, assessing the incidence and identifying risk factors for skin cancer are crucial steps in its prevention. The purpose of this skin study is to systematically evaluate the incidence and risk factors of skin cancer in HTx. Two researchers independently conducted literature searches across 8 databases. The search covered publications from the establishment of the database through October 1, 2024. After screening title, abstract, and the full text, 34 eligible cohort studies were included. The studies were evaluated using the New castle-Ottawa Scale (NOS) for non-randomized studies, and papers selection followed PRISMA guidelines. The meta-analysis was conducted using the Stata 15.0 software. Among 34 cohort studies on HTx, the pooled incidence of skin cancer was 16% (95% CI: 14-19%). The incidences by type were 10% (95% CI: 8-12%) for squamous cell carcinoma and 8% (95% CI: 6-9%) for basal cell carcinoma. Regionally, the highest incidence was observed in the USA 22% (95% CI: 18-27%). Risk factors significantly associated with skin cancer included age (RR: 1.08, 95% CI: 1.04-1.11), male (RR: 1.53, 95% CI:1.11-2.12), white race (RR: 10.23, 95% CI: 7.32-14.30), smoking history (RR:1.26, 95% CI:1.05-1.51), prolonged sunlight exposure (≥ 2500 h) (RR:3.66, 95% CI: 2.11-6.36), pre-transplant cancer (RR: 1.61, 95% CI: 1.43-1.82), muromonab-CD3 (OKT3) (RR: 2.61, 95% CI: 2.11-3.24). The higher incidence of skin cancer observed in this study highlights the urgent need for follow-up care in heart transplant recipients. To address this, tailored skin cancer prevention strategies should be implemented, focusing on modifiable risk factors. Our findings provide a theoretical foundation to help healthcare professionals prevent and manage skin cancer in heart transplant patients.Patient or Public Contribution: YY, and HPY, were responsible for the conception and design of the study. YYS, FYL, and HPY, were responsible for the acquisition, analysis and interpretation of the data. All of the authors drafted the article or revised it critically for important intellectual content and provided final approval of the version to be submitted.
Abstract licence: CC BY-NC-ND
C. Sgro
Toxicology, 1995
- Binding, Competitive
- Blood Coagulation Disorders
- Communicable Diseases
S. L. Smith
Journal of transplant coordination : official publication of the North American Transplant Coordinators Organization, 1996
- Clinical Protocols
- Graft Rejection
- Immunosuppressive Agents
M. Wilde, K. Goa
Drugs, 1996
Muriel L Burk, K. Matuszewski
Annals of Pharmacotherapy, 1997
- Kidney Transplantation
- Antilymphocyte Serum
- Immunosuppressive Agents
Pasupuleti R, Rosato F, Kolanovic D, et al.
2023
- Neoplasms
- Immunoconjugates
- Azides
Antibody-based cancer therapies have been evolving at a rapid pace in the pharmaceutical market. Bispecific antibody-drug conjugates that engage immune cells to target and kill cancer cells with precision have inspired the development of immunotherapy. Miniaturized antibody fragments such as diabodies, nanobodies, or single-chain variable fragments (scFvs) hold great promise as antibody-drug conjugates as they specifically target tumor tissue and can penetrate it. Here, we optimized the soluble periplasmic expression of the scFv OKT3 comprising the variable VH and VL domains of the mouse anti-human CD3 antibody muromonab-CD3 (trade name Orthoclone OKT3) in E. coli. By an expansion of the genetic code, we site-specifically incorporated the reactive non-canonical amino acid Nε-((2-azidoethoxy)carbonyl)-L-lysine (AzK) into scFv OKT3 using an orthogonal pyrrolysyl-tRNA synthetase/tRNACUA pair. To confirm the AzK incorporation and to demonstrate the accessibility of the reactive azide group, we conjugated a fluorophore to scFv OKT3 AzK variants by copper-free strain-promoted alkyne-azide cycloaddition (‘click chemistry’). The scFv OKT3 wild type and the AzK variants bound T cells at nanomolar concentrations. In this study, a ‘ready-to-click’ scFv OKT3 was successfully developed for future applications, e.g. as controlled anti-T cell antibody-drug conjugate or bispecific T cell engager and for imaging immune T cell migration in cancers.
Abstract licence: CC BY
Chen C, Zhang H, Lin Y, et al.
2023
- COVID-19
- Lupus Erythematosus, Systemic
- MicroRNAs
OBJECTIVE: Systemic lupus erythematosus (SLE) patients are at risk during the COVID-19 pandemic, yet the underlying molecular mechanisms remain incompletely understood. This study sought to analyze the potential molecular connections between COVID-19 and SLE, employing a bioinformatics approach to identify effective drugs for both conditions. METHODS: The data sets GSE100163 and GSE183071 were utilized to determine share differentially expressed genes (DEGs). These DEGs were later analyzed by various bioinformatic methods, including functional enrichment, protein-protein interaction (PPI) network analysis, regulatory network construction, and gene-drug interaction construction. RESULTS: A total of 50 common DEGs were found between COVID-19 and SLE. Gene ontology (GO) functional annotation revealed that "immune response," "innate immune response," "plasma membrane," and "protein binding" were most enriched in. Additionally, the pathways that were enriched include "Th1 and Th2 cell differentiation." The study identified 48 genes/nodes enriched with 292 edges in the PPI network, of which the top 10 hub genes were CD4, IL7R, CD3E, CD5, CD247, KLRB1, CD40LG, CD7, CR2, and GZMK. Furthermore, the study found 48 transcription factors and 8 microRNAs regulating these hub genes. Finally, four drugs namely ibalizumab (targeted to CD4), blinatumomab (targeted to CD3E), muromonab-CD3 (targeted to CD3E), and catumaxomab (targeted to CD3E) were found in gene-drug interaction. CONCLUSION: Four possible drugs that targeted two specific genes, which may be beneficial for COVID-19 patients with SLE.
Abstract licence: CC BY
B. Weinshenker, Brenda H. Bass, G. Ebers, et al.
Journal of the American Academy of Dermatology, 1989
- Antibodies, Monoclonal
- Extremities
- Psoriasis
Yang HR, Kim JW, Choi HL, et al.
2025
- Antibodies, Monoclonal
- Antibody Specificity
- Lymphocyte Activation
Rajagopal D, Ieong KS, Mate R, et al.
2026
- Antibodies, Monoclonal
- Cytokines
- Disease Models, Animal
Introduction A diverse range of innovative biological therapies is being developed to treat various human diseases. The safety assessment of these biologics is a critical factor determining clinical success. Enhanced humanised mouse models have the potential to revolutionise immunotoxicological profiling by refining procedures for effective in vivo safety assessments. Methods We evaluated a novel reference panel of recombinant monoclonal antibodies (mAbs), 19/156, with varying cytokine release (CR) potential to assess the sensitivity of specific humanised mouse models. The in vitro CR capacity of the reference panel has previously been evaluated in an international collaborative study. We present here the in vivo assessment of the reference Ab panel using NOD-scid-gamma (NSG) mice reconstituted with either umbilical cord-derived hematopoietic human (CD34 + ) stem cells (HSC) or human peripheral blood mononuclear cells (PBMC) from healthy donors. Results Our manuscript discusses a comparative evaluation of both forms of engraftment and the CR patterns in response to the reference panel. The in vivo CR pattern is discussed in relation to in vitro assays using the same PBMC donor cohort. The manuscript discusses the utility of these humanised mice as a model for translational use in hazard identification and preclinical safety assessment. Discussion The results highlight the importance of incorporating standardised reference materials to evaluate, qualify, and harmonise preclinical models for translational use. This approach aims to enhance the predictability and reliability of both in vitro and in vivo safety assessments, thereby supporting the development of safe and effective biological therapies.
Abstract licence: CC BY
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
0.8 hours
Mechanism
Muromonab binds to the T-cell surface glycoprotein CD3 epsilon chain.
Food interactions
None known
Human targets
5 targets
Data: DrugBank · CC BY-NC 4.0
Pharmacokinetics at a glance
Half-life
0.8 hours
Metabolism
Pharmacokinetic data: DrugBank · CC BY-NC 4.0
Known interactions with other medications. Always consult a healthcare professional.
Showing 50 of 681 interactions
How the body processes this drug — absorption, distribution, metabolism, and elimination
Proteins and enzymes this drug interacts with in the body
Upon TCR engagement, these motifs become phosphorylated by Src family protein tyrosine kinases LCK and FYN, resulting in the activation of downstream signaling pathways .
PMID:2470098
In addition of this role of signal transduction in T-cell activation, CD3D plays an essential role in thymocyte differentiation. Indeed, participates in correct intracellular TCR-CD3 complex assembly and surface expression. In absence of a functional TCR-CD3 complex, thymocytes are unable to differentiate properly.
Interacts with CD4 and CD8 and thus serves to establish a functional link between the TCR and coreceptors CD4 and CD8, which is needed for activation and positive selection of CD4 or CD8 T-cells PMID:12215456
Upon TCR engagement, these motifs become phosphorylated by Src family protein tyrosine kinases LCK and FYN, resulting in the activation of downstream signaling pathways .
PMID:2470098
In addition of this role of signal transduction in T-cell activation, CD3E plays an essential role in correct T-cell development. Initiates the TCR-CD3 complex assembly by forming the two heterodimers CD3D/CD3E and CD3G/CD3E. Also participates in internalization and cell surface down-regulation of TCR-CD3 complexes via endocytosis sequences present in CD3E cytosolic region .
PMID:10384095 PMID:26507128
In addition to its role as a TCR coreceptor, it serves as a receptor for ITPRIPL1.
Ligand recognition inhibits T-cell activation by promoting interaction with NCK1, which prevents CD3E-ZAP70 interaction and blocks the ERK-NFkB signaling cascade and calcium influx PMID:38614099
Upon TCR engagement, these motifs become phosphorylated by Src family protein tyrosine kinases LCK and FYN, resulting in the activation of downstream signaling pathways .
PMID:2470098
In addition to this role of signal transduction in T-cell activation, CD3G plays an essential role in the dynamic regulation of TCR expression at the cell surface .
PMID:8187769
Indeed, constitutive TCR cycling is dependent on the di-leucine-based (diL) receptor-sorting motif present in CD3G
Upon TCR engagement, these motifs become phosphorylated by Src family protein tyrosine kinases LCK and FYN, resulting in the activation of downstream signaling pathways .
PMID:1384049 PMID:1385158 PMID:2470098 PMID:7509083
CD3Z ITAMs phosphorylation creates multiple docking sites for the protein kinase ZAP70 leading to ZAP70 phosphorylation and its conversion into a catalytically active enzyme .
PMID:7509083
Plays an important role in intrathymic T-cell differentiation. Additionally, participates in the activity-dependent synapse formation of retinal ganglion cells (RGCs) in both the retina and dorsal lateral geniculate nucleus (dLGN) (By similarity)
Contrary to III-A, is not capable to mediate antibody-dependent cytotoxicity and phagocytosis. May serve as a trap for immune complexes in the peripheral circulation which does not activate neutrophils
ATC L04AG01
Chemical identifiers
CAS, UNII, InChI Key and database cross-references
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Chemical identifiers
CAS, UNII, InChI Key and database cross-references
Linked compound data from DrugBank Open Data (CC BY-NC 4.0)
Muromonab
Matched from: Muromonab-CD3
Additional database identifiers
Drugs Product Database (DPD)
7680
HUGO Gene Nomenclature Committee (HGNC)
HGNC:1673
GenAtlas
CD3D
GeneCards
CD3D
GenBank Gene Database
X01451
UniProt Accession
CD3D_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:1674
GenAtlas
CD3E
GeneCards
CD3E
GenBank Gene Database
X03884
GenBank Protein Database
469945
Guide to Pharmacology
2742
UniProt Accession
CD3E_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:1675
GenAtlas
CD3G
GeneCards
CD3G
GenBank Gene Database
BC113830
UniProt Accession
CD3G_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:1677
GenAtlas
CD247
GeneCards
CD247
GenBank Gene Database
BC025703
UniProt Accession
CD3Z_HUMAN
HUGO Gene Nomenclature Committee (HGNC)
HGNC:3620
GenAtlas
FCGR3B
GeneCards
FCGR3B
GenBank Gene Database
X16863
GenBank Protein Database
31322
UniProt Accession
FCG3B_HUMAN
DrugBank citations
If you use DrugBank data in your research, please cite the following publications:
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Structured knowledge from the free knowledge base
ATC classifications (Wikidata)
Linked open data from Wikidata (Q416494), 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.