A simple mathematical method to express the deviation in release profile of a test product following Higuchi's kinetics from an ideal Higuchi release profile was developed. The method is based on calculation of area under the curve (AUC) by using the trapezoidal rule. The precision of prediction depends on the number of data points. The method is exemplified for 2 dosage forms (tablets of diltiazem HCl and microspheres of diclofenac sodium) that are designed to release the drug over a 12-hour period. The method can be adopted for the formulations where drug release is incomplete (<100%) or complete (100%) at last sampling time. To describe the kinetics of drug release from the test formulation, zero-order, first-order, Higuchi's, Hixson-Crowell's, and Weibull's models were used. The criterion for selecting the most appropriate model was based on the goodness-of-fit test. The release kinetics of the tablets and microspheres were explained by the Higuchi model. The release profiles of the test batches were slightly below the ideal Higuchi release profile. For the test products, observed percentage deviation from an ideal Higuchi profile is less than 16% for tablets and less than 11% for microspheres. The proposed method can be extended to the modified release formulations that are designed to release a drug over 6, 18, or 24 hours. If the data points are not evenly separated, the ideal drug release profile and AUC are calculated according to the specific sampling time. The proposed method may be used for comparing formulated products during the research and development stage, for quality control of the products, or for promoting products by comparing performance of the test product with that of the innovator's product.

The objective of this study was to develop modified-release tablets of diltiazem HCl using a direct compression technique. A 3(2) factorial design was employed using the amount of alkali-treated guar gum and cetyl alcohol as independent variables. This article proposes the use of a novel approach-f2 and Sd values as dependent variables-to evaluate the effect of selected independent variables along with other dependent variables (i.e., percentage drug released in x min, Yx; time required for z% drug release, tz; and mean dissolution time (MDT)). It is concluded that when a decision is to be made for the selection of a best batch, it is perhaps more realistic to use the f2 or Sd value which takes into account the dissolution profile as a whole, as opposed to Yx and tz values which use just one point from the dissolution plot. The batch showing the f2 value nearest to 100 or the Sd value nearest to zero is ranked as the best batch (diltiazem HCl 90 mg, alkali-treated guar gum 80 mg and cetyl alcohol 15 mg). The gel strength and matrix erosion of the formulated tablets were dependent on the type and amount of the adjuvants. The drug release rate is well correlated with matrix erosion. The kinetics of drug release fitted best to the Korsmeyer and Peppas model. It is concluded that by using a proper combination of the hydrophilic polymer and cetyl alcohol one can achieve a desirable drug release pattern.

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Dissolution testing has become an essential tool in the pharmaceutical industry at various stages of development, manufacturing and marketing. For the comparison of dissolution profiles, similarity factor f 2 is gaining popularity due to its recommendation by various regulatory committees. Dissolution profiles are considered similar if the calculated f 2 value is between 50 and 100.In our opinion,this acceptance limit might not be correctly defined. This article presents the reasons for the same and a new equation to define the lower acceptance limit for different data sets. It is proposed that regulatory agencies should actively consider the revision of the lower acceptance value for f 2 .

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