Chapter title |
In Vitro and In Vivo Methods for Analysis of Nanoparticle Potential to Induce Delayed-Type Hypersensitivity Reactions
|
---|---|
Chapter number | 17 |
Book title |
Characterization of Nanoparticles Intended for Drug Delivery
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7352-1_17 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7350-7, 978-1-4939-7352-1
|
Authors |
Timothy M. Potter, Barry W. Neun, Marina A. Dobrovolskaia, Potter, Timothy M., Neun, Barry W., Dobrovolskaia, Marina A. |
Abstract |
Delayed-type hypersensitivity (DTH) reactions are among the common reasons for drug withdrawal from clinical use during the post-marketing stage. Several in vivo methods have been developed to test DTH responses in animal models. They include the local lymph node assay (LLNA) and local lymph node proliferation assay (LLNP). While LLNA is instrumental in testing topically administered formulations (e.g., creams), the LLNP was proven to be predictive of drug-mediated DTH in response to small molecule pharmaceuticals. Global efforts in reducing the use of research animals lead to the development of in vitro models to predict test-material-mediated DTH. Two such models include analysis of surface marker expression in human cell lines THP-1 and U-937. These tests are known as the human cell line activation test (hCLAT) and myeloid U937 skin sensitization test (MUSST or U-SENS), respectively. Here we describe experimental procedures for all these methods, discuss their in vitro-in vivo correlation, and suggest a strategy for applying these tests to analyze engineered nanomaterials and nanotechnology-formulated drug products. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 9 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 2 | 22% |
Other | 2 | 22% |
Lecturer > Senior Lecturer | 1 | 11% |
Researcher | 1 | 11% |
Professor > Associate Professor | 1 | 11% |
Other | 0 | 0% |
Unknown | 2 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 2 | 22% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 11% |
Computer Science | 1 | 11% |
Biochemistry, Genetics and Molecular Biology | 1 | 11% |
Unknown | 4 | 44% |