Statistical significance of polymeric physicochemical properties in the development of formulations containing a drug from neutral class

Transdermal Delivery of Glimepiride: A Novel Approach Using Nanomicelle-Embedded Microneedles

Glimepiride (GM) is a hydrophobic drug that dissolves slowly and yields inconsistent clinical responses after oral administration. Transdermal drug delivery (TDD) is an appropriate alternative to oral administration. Microneedles (MNs) offer a promising delivery system that penetrates the skin, while polymeric micelles can enhance the solubility; hence, the combination of both results in high drug bioavailability. This study aims to improve glimepiride's solubility, dissolution rate, and bioavailability by incorporating nanomicelles into MNs for TDD. The nanomicelles formulated with 10% Soluplus® (SP) and 40% GM had a mean particle size of 82.6 ± 0.54, PDI of 0.1 ± 0.01, -16.2 ± 0.18 zeta potential, and achieved a 250-fold increase in solubility. The fabricated pyramid shaped GM-dissolving MNs were thermally stable and had no formulation incompatibility, as confirmed by thermal and FTIR analysis. The in vitro dissolution profile revealed that the GM release from nanomicelles and nanomicelle-loaded DMN was concentration-independent following non-Fickian transport mechanism. Improved pharmacokinetic parameters were obtained with dose of 240 µg as compared to 1 mg of GM oral tablet, in healthy human volunteers. The observed Cmax, Tmax and MRT were 1.56 μg/mL ± 0.06, 4 h, and 40.04 h ± 3.37, respectively. The safety profile assessment indicated that microneedles are safe with no adverse effects on skin or health. This study provides an alternative delivery system for the administration of glimepiride, resulting in improved bioavailability, enhanced patient compliance, and reduced dosing frequency.

QSPR Modeling of Biopharmaceutical Properties of Hydroxypropyl Methylcellulose (Cellulose Ethers) Tablets Based on Its Degree of Polymerization

Quantitative structure-property relationship (QSPR) approach has been widely used in predicting physicochemical properties of compounds. However, its application in the estimation of formulation properties based on the polymer used in it to achieve desired formulation characteristics is an extremely challenging process. In the present research, predictive QSPR models were developed by correlating the physicochemical properties of varying grades of cellulose ethers (hydroxypropyl methylcellulose, HPMC) with those of nateglinide (NTG) containing tablets (in vitro and in vivo properties). Sustained release tablets of NTG were prepared by using different grades and concentrations of HPMC and subsequently characterized for in vitro as well as in vivo parameters. Further, QSPR models for individual formulation property were developed by correlating the polymeric physicochemical properties with the formulation characteristics. Subsequently, a true external validation method was used to validate the predictability of developed models. The dissolution study indicated Korsmeyer-Peppas as the best fit model following non-Fickian as drug transport mechanism extending the drug release up to 12 h. In vivo studies showed limited absorption of the NTG. Developed QSPR models showed promising validated predictability for formulation characteristics. The applicability of present work in formulation development could significantly reduce the time and cost expenditure on design trials without actually formulating a delivery system.

Quantitative Structure-Property Relationship Approach in Formulation Development: an Overview

Chemoinformatics is emerging as a new trend to set drug discovery which correlates the relationship between structure and biological functions. The main aim of chemoinformatics refers to analyzing the similarity among molecules, searching the molecules in the structural database, finding potential drug molecule and their property. One of the key fields in chemoinformatics is quantitative structure-property relationship (QSPR), which is an alternative process to predict the various physicochemical and biopharmaceutical properties. This methodology expresses molecules via various numerical values or properties (descriptors), which encodes the structural characteristics of molecules and further used to calculate physicochemical properties of the molecule. The established QSPR model could be used to predict the properties of compounds that have been measured or even have been unknown, which ultimately accelerates the development process of a new molecule or the product. The formulation characteristics (drug release, transportability, bioavailability) can be predicted with the integration of QSPR approach. Therefore, QSPR modeling is an emerging trend to skip conventional drug as well as formulation development process. The current review highlights the overall process involved in the application of the QSPR approach in formulation development.

Quantitative structure–property relationship modeling for the prediction of hydrophilic drug entrapment in liposomes for lung targeted delivery

A QSPR approach to the development of targeted formulation could save time and cost by early prediction of the most influential ingredient properties.