The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Intraperitoneal Route of Drug Administration: Should it Be Used in Experimental Animal Studies?
Open accessAbstract
Intraperitoneal (IP) route of drug administration in laboratory animals is a common practice in many in vivo studies of disease models. While this route is an easy to master, quick, suitable for chronic treatments and with low impact of stress on laboratory rodents, there is a common concern that it may not be an acceptable route for drug administration in experimental studies. The latter is likely due to sparsity of information regarding pharmacokinetics of pharmacological agents and the mechanisms through which agents get systemic exposure after IP administration. In this review, we summarize the main mechanisms involved in bioavailability of IP administered drugs and provide examples of pharmacokinetic profiles for small and large molecules in comparison to other routes of administration. We conclude with a notion that IP administration of drugs in experimental studies involving rodents is a justifiable route for pharmacological and proof-of-concept studies where the goal is to evaluate the effect(s) of target engagement rather than properties of a drug formulation and/or its pharmacokinetics for clinical translation.
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(2024) · doi:10.1002/advs.202406305 · Cited by 55
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Metadata
- Authors
- Al Shoyaib, A., Archie, S. R., & Karamyan, V. T.
- Venue
- Pharmaceutical Research
- Published
- 2019-12-23
- Volume
- 37
- Issue
- 1
- Pages
- 12-12
- ISSN
- 0724-8741 (ISSN-L)
- 1573-904X
- OpenAlex
- W2997805831
- Cited by
- 631
- References
- 60
- FWCI
- 45.01
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Al Shoyaib, A., Archie, S. R., & Karamyan, V. T. (2020). Intraperitoneal Route of Drug Administration: Should it Be Used in Experimental Animal Studies? Pharmaceutical Research. https://doi.org/10.1007/s11095-019-2745-x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.