Background:
Glioma is one of the most commonly observed tumours, representing about
75% of brain tumours in adult population. Generally, glioma treatment includes surgical
resection followed by radiotherapy and chemotherapy. The current chemotherapy for glioma
involves use of temozolomide, doxorubicin, monoclonal antibodies, etc. however, the clinical
outcomes in patients are not satisfactory. Primarily, blood-brain barrier hinders these drugs
from reaching the target leading to the recurrence of glioma post-surgery. In addition, these
drugs are not target-specific and affect the healthy cells of the body. Therefore, gliomatargeted drug delivery is essential to reduce the rate of recurrence and treat the condition with
more reliable alternatives.
Method:
Literature search was conducted to understand glioma pathophysiology, its current
therapeutic approaches for targeted delivery using databases like Pub Med, Web of science,
Scopus, and Google Scholar, etc.
Results:
This review gives an insight to challenges associated with current treatments, factors
influencing drug delivery in glioma, and recent advancements in targeted drug delivery.
Conclusion:
The promising results could be seen with nanotechnology based approaches,
like polymeric, lipid-based and hybrid nanoparticles in treatment of glioma. Biotechnological
developments such as carrier peptides and gene therapy are future prospects in glioma
therapy. Therefore, these targeted delivery systems will be beneficial in clinical practices for
glioma treatment.
This research aims to develop and validate a bioanalytical method for simultaneous estimation of an antidiabetic combination using LC-MS/MS in rat plasma. Nateglinide and metformin hydrochloride are commonly used combination for clinical management of Type 2 diabetes. Hence, simultaneous determination in plasma is essential for the rapid analysis of samples from the pharmacokinetic studies. Statistical optimization was carried out for liquid chromatography (LC) parameters and mass spectroscopic (MS) parameters by design of experiment (DoE) (Design Expert Version 11, Stat Ease Inc., USA) approach. A 3 3 full factorial design was used for optimization of LC parameters; %methanol, %formic acid, and flow rate were selected as independent variables, whereas peak area and tailing factor were considered as dependent variables for both drugs. Box-Behnken design was used to optimize MS parameters including drying gas flow rate, nebulizing gas flow rate, DL temperature, heat block temperature, and positive voltage as independent factors, and responses selected were [M + H] + intensity of nateglinide and metformin hydrochloride. The [M + H] + intensity of the optimized method for nateglinide and metformin hydrochloride were 2,462,838 and 11,873,826, respectively. The model was found significant for optimizing LC and MS parameters with p < 0.05 for both nateglinide and metformin hydrochloride. The optimized method was validated as per the ICH-M10 guideline, which was accurate, precise, and selective. The method was cost-effective and capable of quantitating concentrations in picogram levels for nateglinide and metformin hydrochloride simultaneously.
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