ABSTRACT
Malignant tumor is a major disease affecting human health. The nano-delivery system itself has a unique size effect and it can achieve tumor-targeted distribution of drug molecules, improve the therapeutic effect, and reduce the toxic and side effects on normal tissues and cells after functional modification. Patient-derived xenografts (PDX) models can be established by transplanting patient-derived cancer cells or small tumor tissue into immunodeficient mice directly. Compared with the tumor cell line model, this model can preserve the key features of the primary tumor such as histomorphology, heterogeneity, and genetic abnormalities, and keep them stable between generations. PDX models are widely used in drug evaluation, target discovery and biomarker development, especially providing a reliable research platform for the diagnosis and treatment evaluation of nano-delivery systems. This review summarizes the application of several common cancer PDX models in the evaluation of nano-delivery systems, in order to provide references for researchers to perform related research.
ABSTRACT
In the research on cancer theranostics, most environment-sensitive drug delivery systems can only achieve unidirectional and irreversible responsive changes under pathological conditions, thereby improving the targeting effect and drug release performance of the delivery system. However, such irreversible changes pose potential safety hazards when the dynamically distributed delivery system returns to the blood circulation or transports to the normal physiological environment. Intelligent reversible drug delivery systems can respond to normal physiological and pathological microenvironments to achieve bidirectional and reversible structural changes. This feature will help to precisely control the drug release of the delivery system, prolong the blood circulation time, improve the targeting efficiency, and avoid the potential safety hazards of the irreversible drug delivery system. In this review, we describe the research progress of intelligent reversible drug delivery system from two main aspects: controlled drug release and prolonged blood circulation time/enhanced cellular internalization of drug.
ABSTRACT
OBJECTIVE: To investigate the taste-masking effect of montelukast sodium orally disintegrating tablets using electronic tongue technology and human sensory evaluation and determine the optimum formulation. METHODS: Orally disintegrating tablets were prepared with five different concentrations of flavoring agents or without flavoring agent.The tastes of those tablets were determined by electronic tongue, and principal component analysis and linear discriminant analysis were used to evaluate differences of different formulations. The taste-masking effect of the tablets was investigated combined with electronic tongue analysis and sensory evaluation of subjects. RESULTS: The taste of orally disintegrating tablet was the best when the total amount of flavoring agent was 1.6 mg, and the ratio of sweetening agent to aromatic agent was 5∶3. CONCLUSION: The combination of electronic tongue and human sensory assess can evaluate the taste-masking effect of orally disintegrating tablets and provide the basis for determining the optimum formulation.
ABSTRACT
OBJECTIVE: To prepare montelukast sodium orally disintegrating tablets and investigate the bioequivalence in Beagle dogs. METHODS: The orally disintegrating tablets were prepared by direct compression method,and the optimal formulation was screened by orthogonal test.HPLC-fluorescence method was developed for determination of montelukast sodium plasma concentration in Beagle dogs. RESULTS: The optimized formulation(1 000 tablets) was montelukast sodium 10.4 g, microcrystalline cellulose 60 g, cross linked povidone 30 g, mannitol 15 g, magnesium stearate 2 g, aerosil 1 g, aspartame 1 g, flavor 0.6 g. CONCLUSION: Montelukast sodium orally disintegrating tablets made of the optimized formulation could disintegrate rapidly. Relatively bioavailability of montelukast sodium orally disintegrating tablets is 90.7%.