Methylated N-(4-N,N-dimethylaminobenzyl) chitosan coated liposomes for oral protein drug delivery

Kowapradit, Jariya; Apirakaramwong, Auayporn; Ngawhirunpat, Tanasait; Rojanarata, Theerasak; Sajomsang, Warayuth; Opanasopit, Praneet

doi:10.1016/j.ejps.2012.06.020

Cited by 39 publications

(26 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to this strategy, liposomes can be readily coated either with CS, or HA or their derivatives based upon the ion-pair formation between the lipid's groups and the polysaccharide's groups. [95][96][97][98] Therefore, the formation of the HA or CS-coated liposomes can be easily achieved upon incubation of liposomes in an aqueous solution of the polysaccharide. The resulting system enables the association of hydrophilic molecules (in the aqueous core) or hydrophobic drugs (within the lipid bilayer).…”

Section: Ha and Cs-coated Liposomesmentioning

confidence: 99%

Polysaccharide-Based Nanocarriers for Drug Delivery

Teijeiro¹,

McGlone²,

Csaba³

et al. 2014

Frontiers in Nanobiomedical Research

View full text Add to dashboard Cite

Section: Ha and Cs-coated Liposomesmentioning

confidence: 99%

Polysaccharide-Based Nanocarriers for Drug Delivery

Teijeiro¹,

McGlone²,

Csaba³

et al. 2014

Frontiers in Nanobiomedical Research

View full text Add to dashboard Cite

“…A crosslinked gel composed of enzymatically degradable hyaluronic acid (HA) was attached on the surface of liposome. [99] Recently, Salmaso and co-workers designed a pH-sensitive stearoyl-PEGpoly(methacryloyl sulfadimethoxine)-decorated liposome system with BSA loading for bladder cancer treatment. The hyaluronidase (HAase) is highly overexpressed at the tumor microenvironment, which could degrade the HA shell, thereby promoting the released TRAIL to bind with the death receptors of the plasma membrane and facilitate the tumor cellular uptake of Dox-R8H3-liposomes.…”

Section: Liposomesmentioning

confidence: 99%

Rational Design of Nanocarriers for Intracellular Protein Delivery

et al. 2019

View full text Add to dashboard Cite

Protein/antibody therapeutics have exhibited the advantages of high specificity and activity even at an extremely low concentration compared to small molecule drugs. However, they are accompanied by unfavorable physicochemical properties such as fragile tertiary structure, large molecular size, and poor penetration of the membrane, and thus the clinical use of protein drugs is hindered by inefficient delivery of proteins into the host cells. To overcome the challenges associated with protein therapeutics and enhance their biopharmaceutical applications, various protein‐loaded nanocarriers with desired functions, such as lipid nanocapsules, polymeric nanoparticles, inorganic nanoparticles, and peptides, are developed. In this review, the different strategies for intracellular delivery of proteins are comprehensively summarized. Their designed routes, mechanisms of action, and potential therapeutics in live cells or in vivo are discussed in detail. Furthermore, the perspective on the new generation of delivery systems toward the emerging area of protein‐based therapeutics is presented as well.

show abstract

“…There are many methods found in the literature dealt with the increase of the oral bioavailability of proteins. Enteric coatings [5], enzyme inhibitors [6,7], hydrogels [8], solid in oil formulations [9], liposomes [10] or other polymer nano-or microparticles [11][12][13][14][15] are used to protect the API from the gastrointestinal conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Liposomes, or functionalized microparticles may also increase the intestinal absorption. However, despite the numerous advantages, the difficult production method, the stability issues and the poor entrapment efficiency are considerable drawbacks of these formulations [10]. Furthermore, the appropriate administration of these delivery systems requires further formulation into different dosage forms, which means extra stress on the protein containing systems.…”

Section: Introductionmentioning

confidence: 99%

Estimation of design space for an extrusion–spheronization process using response surface methodology and artificial neural network modelling

Sovány

Tislér

Kristó

et al. 2016

European Journal of Pharmaceutics and Biopharmaceutics

View full text Add to dashboard Cite

The application of the Quality by Design principles is one of the key issues of the recent pharmaceutical developments. In the past decade a lot of knowledge was collected about the practical realization of the concept, but there are still a lot of unanswered questions. The key requirement of the concept is the mathematical description of the effect of the critical factors and their interactions on the critical quality attributes (CQAs) of the product. The process design space (PDS) is usually determined by the use of design of experiment (DoE) based response surface methodologies (RSM), but inaccuracies in the applied polynomial models often resulted in the over/underestimation of the real trends and changes making the calculations uncertain, especially in the edge regions of the PDS. The completion of RSM with artificial neural network (ANN) based models is therefore a commonly used method to reduce the uncertainties. Nevertheless, since the different researches are focusing on the use of a given DoE, there is lack of comparative studies on different experimental layouts. Therefore, the aim of present study was to investigate the effect of the different DoE layouts (2 level full factorial, Central Composite, Box-Behnken, 3 level fractional and 3 level full factorial design) on the model predictability and to compare model sensitivities according to the organization of the experimental data set. It was revealed that the size of the design space could differ more than 40% calculated with different polynomial models, which was associated with a considerable shift in its position when higher level layouts were applied. The shift was more considerable when the calculation was based on RSM. The model predictability was also better with ANN based models. Nevertheless, both modelling methods exhibit considerable sensitivity to the organization of the experimental data set, and the use of design layouts is recommended, where the extreme values factors are more represented.

show abstract

Methylated N-(4-N,N-dimethylaminobenzyl) chitosan coated liposomes for oral protein drug delivery

Cited by 39 publications

References 22 publications

Polysaccharide-Based Nanocarriers for Drug Delivery

Polysaccharide-Based Nanocarriers for Drug Delivery

Rational Design of Nanocarriers for Intracellular Protein Delivery

Estimation of design space for an extrusion–spheronization process using response surface methodology and artificial neural network modelling

Contact Info

Product

Resources

About