Atul J. Shukla

Application of artificial neural networks in the design of controlled release drug delivery systems

Controlled release drug delivery systems offer great advantages over the conventional dosage forms. However, there are great challenges to efficiently develop controlled release drug delivery systems due to the complexity of these delivery systems. Traditional statistic response surface methodology (RSM) is one of the techniques that has been employed to develop and formulate controlled release dosage forms. However, there are some limitations to the RSM technique. Hence, another technique called artificial neural networks (ANN) has recently gained wide popularity in the development of controlled release dosage forms. In this review, the basic ANN structure, the development of the ANN model and an explanation of how to use ANN to design and develop controlled release drug delivery systems are discussed. In addition, the applications of ANN in the design and development of controlled release dosage forms are also summarized in this review.

Controlled Release of a Contraceptive Steroid from Biodegradable and Injectable Gel Formulations: In Vitro Evaluation

AbstractPurpose. The purpose of this study was to investigate the effects of formulation factors including varying wax concentration, drug loading and drug particle size, on drug release characteristics from both pure oil and gel formulations prepared with a combination of derivatized vegetable oil (Labrafil 1944 CS) and glyceryl palmitostearate (Precirol ATO 5), using levonorgestrel as a model drug. Methods. The effects of varying drug loadings, different drug particle sizes, and wax (Precirol) concentrations on in-vitro drug release rates were evaluated, and the mechanisms of drug release from the gels were determined. Results. Zero-order drug release rates from the 10% Precirol gel formulations containing 0.25, 0.50 and 2.00% w/v drug loadings were lower than those observed for oil formulations containing identical drug loadings. Higher zero-order release rates were observed from formulations containing smaller drug particles suspended in both oil and gel formulations. The mechanism of drug release from gels containing less than 0.25% w/w drug was diffusion-controlled. Increasing the wax concentrations in the gels from 5% w/w to 20% w/w significantly decreased the diffusivity of the drug through the gel formulations and markedly increased the force required to inject the gels from two different sizes of needles. Conclusions. This study shows how modification of the physicochemical properties of the gel formulations by changing the drug particle size, wax concentration and drug loading, affects drug release characteristics from the system.

Prediction of Drug Content and Hardness of Intact Tablets Using Artificial Neural Network and Near-Infrared Spectroscopy

The purpose of this study was to predict drug content and hardness of intact tablets using artificial neural networks (ANN) and near-infrared spectroscopy (NIRS). Tablets for the drug content study were compressed from mixtures of Avicel® PH-101, 0.5% magnesium stearate, and varying concentrations (0%, 1%, 2%, 5%, 10%, 20%, and 40% w/w) of theophylline. Tablets for the hardness study were compressed from mixtures of Avicel PH-101 and 0.5% magnesium stearate at varying compression forces ranging from 0.4 to 1 ton. An Intact Analyzer™ was used to obtain near infrared spectra from the tablets with varying drug contents, whereas a Rapid Content Analyzer™ (RCA) was used to obtain spectral data from the tablets with varying hardness. Two sets of tablets from each batch (i.e., tablets with varying drug content and hardness) were randomly selected. One set of tablets was used to generate appropriate calibration models, while the other set was used as the unknown (test) set. A total of 10 ANN calibration models (5 each with 10 and 160 inputs at appropriate wavelengths) and five separate 4-factor partial least squares (PLS) calibration models were generated to predict drug contents of the test tablets from the spectral data. For the prediction of tablet hardness, two ANN calibration models (one each with 10 and 160 inputs) and two 4-factor PLS calibration models were generated and used to predict the hardness of test tablets. The PLS calibration models were generated using Vision® software. Prediction of drug contents of test tablets using the ANN calibration models generated with 10 inputs was significantly better than the prediction obtained with the ANN calibration models with 160 inputs. For tablets with low drug concentrations (less than or equal to 2%w/w), prediction of drug content was better with either of the two ANN calibration models than with the PLS calibration models. However, prediction of drug contents of tablets with greater than or equal to 5% w/w drug was better with the PLS calibration models than with the ANN calibration models. Prediction of tablet hardness was better with the ANN calibration models generated with either 10 or 160 inputs than with the PLS calibration models. This work demonstrated that a well-trained ANN model is a powerful alternative technique for analysis of NIRS data. Moreover, the technique could be used in instances when the conventional modeling of data does not work adequately.

Effect of Drug Loading and Molecular Weight of Cellulose Acetate Propionate on the Release Characteristics of Theophylline Microspheres

Microspheres with 40, 50, and 60% drug loading of anhydrous theophylline core material were prepared by the emulsion-solvent evaporation method. Three different molecular weights of cellulose acetate propionate were used as encapsulating polymers. The geometric mean diameter of the microspheres increased with drug loading for all polymers. Dissolution rate for a given particle size fraction also increased with drug loading for all polymers. Higuchi/Baker-Lonsdale spherical matrix dissolution kinetics were followed by narrow particle size fractions of the microspheres. A linear relationship between the T-50% (time required for 50% of the drug to be released) and the square of microsphere diameter was observed with all three molecular weights of the encapsulants. The slowest drug release was obtained with the high molecular weight polymer, which also produced the smoothest microspheres.

A Comparison of Reflectance and Transmittance Near-Infrared Spectroscopic Techniques in Determining Drug Content in Intact Tablets

Drug contents of intact tablets were determined using non-destructive near infrared (NIR) reflectance and transmittance spectroscopic techniques. Tablets were compressed from blends of Avicel® PH–101 and 0.5% w/w magnesium stearate with varying concentrations of anhydrous theophylline (0, 1, 2, 5, 10, 20 and 40% w/w). Ten tablets from each drug content batch were randomly selected for spectral analysis. Both reflectance and transmittance NIR spectra were obtained from these intact tablets. Actual drug contents of the tablets were then ascertained using a UV-spectrophotometer at 268 nm. Multiple linear regression (MLR) models at 1116 nm and partial least squares (PLS) calibration models were generated from the second derivative spectral data of the tablets in order to predict drug contents of intact tablets. Both the reflectance and the transmittance techniques were able to predict the drug contents inintact tablets over a wide range. However, a comparison ofthe results of the study indicated that the lowest percent errors of prediction were provided by the PLS calibration models generated from spectral data obtained using the transmittance technique.

Application of Near-Infrared Spectroscopy for Nondestructive Analysis of Avicel® Powders and Tablets

The purpose of this study was to use near-infrared spectroscopy (NIRS) as a nondestructive technique to (a) differentiate three Avicel products (microcrystalline cellulose [MCC] PH-101, PH-102, and PH-200) in powdered form and in compressed tablets with and without 0.5% w/w magnesium stearate as a lubricant; (b) determine the magnesium stearate concentrations in the tablets; and (c) measure hardness of tablets compressed at several compression forces. Diffuse reflectance NIR spectra from Avicel powders and tablets (compression forces ranging from 0.2 to 1.2 tons) were collected and distance scores calculated from the second-derivative spectra were used to distinguish the different Avicel products. A multiple linear regression model was generated to determine magnesium stearate concentrations (from 0.25 to 2% w/w), and partial least squares (PLS) models were generated to predict hardness of tablets. The NIRS technique could distinguish between the three different Avicel products, irrespective of lubricant concentration, in both the powdered form and in the compressed tablets because of the differences in the particle size of the Avicel products. The percent error for predicting the lubricant concentration of tablets ranged from 0.2 to 10% w/w. The maximum percent error of prediction of hardness of tablets compressed at the various compression forces was 8.8% for MCC PH-101, 5.3% for MCC PH-102, and 4.6% for MCC PH-200. The NIRS nondestructive technique can be used to predict the Avicel type in both powdered and tablet forms as well as to predict the lubricant concentration and hardness.

Use of FT-NIR transmission spectroscopy for the quantitative analysis of an active ingredient in a translucent pharmaceutical topical gel formulation

The objective of this study was to demonstrate the use of transmission Fourier transform near-infrared (FT-NIR) spectroscopy for quantitative analysis of an active ingredient in a translucent gel formulation. Gels were prepared using Carbopol 980 with 0%, 1%, 2%, 4%, 6%, and 8% ketoprofen and analyzed with an FT-NIR spectrophotometer operated in the transmission mode. The correlation coefficient of the calibration was 0.9996, and the root mean squared error of calibration was 0.0775%. The percent relative standard deviation for multiple measurements was 0.10%. The results prove that FT-NIR can be a good alternative to other, more time-consuming means of analysis for these types of formulations.

Effect of moisture content on compression properties of two dextrose-based directly compressible diluents.

Moisture sorption characteristics and the effect of moisture content on the compression properties of two dextrose-based directly compressible diluents, namely, Emdex (diluent A) and Sweetrex (diluent B) were studied. Both diluents sorbed moisture rapidly at relative humidities greater than 60%. For both the diluents, pressures required to compress tablets to the same relative density decreased with increasing moisture content. Yield pressures calculated from linear Heckel plots obtained from the compression data of both diluents reflected decreasing values with increasing moisture content. Three-way surface profile graphs of moisture content versus tablet parameters such as crushing force, relative density, and compression pressure give a unique overall picture of the compression properties of a diluent and offer the tablet formulator a useful tool for diluent comparison.

Effect of Moisture Content on Compression Properties of Directly Compressible High Beta-Content Anhydrous Lactose

Moisture sorption characteristics and the role of moisture on the compression properties of direct compression anhydrous lactose was investigated. Anhydrous lactose sorbed little moisture even when...

Release of Tolmetin from Carbomw Gel Systems

AbstractGel-formulations containing a nonsteroidal anti-inflammatory drug, tolmetin, were prepared using three different carbomers namely, Carbopol™ 934, 940 and 941. Effects of cosolvent composition, carbomer type, carbomer concentration and drug concentration on drug release from the gels were analyzed by factorial design. Gels with high aqueous content yielded significantly higher tolmetin release rates than gels with lower aqueous content. Although no significant differences in drug release characteristics were observed between the three carbomer gels, there was a trend in the release profiles; fastest drug release was observed from Carbopol™ 941 gels and the slowest drug release was observed from Carbopol™ 940 gels. Increasing the carbomer concentration from 1% w/w to 2% w/w had no significant effect on drug release from gel formulations prepared with all the three different types of carbomers. However, increasing the tolmetin concentration in the gels from 1% w/w to 4% w/w resulted in a dramatic inc...