Is Cmax/AUC useful for bioequivalence testing?

Evaluation of bioequivalence for highly variable drugs with scaled average bioequivalence

Bioequivalence studies are performed to demonstrate in vivo that two pharmaceutically equivalent products (in the US) or alternative pharmaceutical products (in the EU) are comparable in their rate and extent of absorption. By definition, for highly variable drugs (HVDs), the estimated within-subject variability is >30%. HVDs often fail to meet current regulatory acceptance criteria for average bioequivalence (ABE). The determination of the bioequivalence of HVDs has been a vexing problem since the inception of the current regulations. It is of concern not only to the generic industry but also to the innovator industry. This article reviews the definition of HVDs, the present regulatory recommendations and the approaches proposed in the literature to deal with the bioequivalence problems of HVDs. The approach of scaled ABE (SABE) is proposed as the most adequate procedure to solve the problem. It is demonstrated that SABE has firm theoretical foundations. In fact, statistical tests similar to SABE are used in various fields, such as psychology and quality control. Algorithms and numerical examples are presented to calculate SABE from the data in conventional two-period and replicate-design studies. The most important feature of SABE is that a fixed sample size is adequate to demonstrate bioequivalence regardless of within-subject variability. The conditions for reaching consistent regulatory decisions with SABE are discussed. The required sample size, for a given statistical power, depends on the regulatory criteria. Sample sizes with different criteria are demonstrated and compared with those arising from a recent informal US FDA proposal. Pragmatic considerations lead to modifications of the theoretical concept of SABE. Several modifications are proposed, including reference scaling, restriction on the estimated geometric mean ratios and possibly limiting SABE to only secondary bioequivalence metrics such as the maximum concentration. Each proposal has its own merit but is also a source of new controversy. Overall, the statistical evaluation of SABE is more complex than that of ABE, which means higher regulatory burden. Standardized open software could be very useful in this regard. A small program script is presented to calculate SABE confidence limits.

Bioequivalence testing by statistical shape analysis

Bioequivalence testing has been traditionally centered in summary variables such as AUC, C (max) and t (max) which filter out the intrinsic information conveyed by discrete sequential concentration-time observations. Comparing entire concentration-time profiles between test and reference formulations for bioequivalence purposes provides stronger evidence about either their similarity or their discrepancy. The Kullback-Leibler information criterion (KLIC) may be computed for each concentration-time across all subjects between formulations of the same drug, with a standard crossover study design. It has been shown that if properly scaled it follow a chi-squared distribution and dependent p-values may be computed in order to construct a bioequivalence criterion. Extensive simulations and real data were used to compare it with the current standard procedures. This statistical shape analysis method may provide important clinical and regulatory advantages.

Novel direct curve comparison metrics for bioequivalence

PURPOSE

The object of this work was to devise four new direct curve comparison (DCC) metrics and examine each metric's distribution properties and performance characteristics.

METHODS

DCC metrics, Cmax, and AUCi were calculated from two bioequivalence studies of three sustained release carbamazepine formulations, where a range of profile similarity was observed. DCC metric values and their confidence intervals were compared to Cmax and AUCi.

RESULTS

The DCC metrics rho, rhom, deltaa, and deltas, exhibited more favorable distributions than Cmax and AUCi ratios, which were frequently skewed. The DCC metrics performed differently than Cmax and AUCi ratios in profile comparisons due to the nature of the DCC metrics. Unlike Cmax and AUCi, the DCC metrics utilize all data points to directly compare entire profiles. Each DCC metric appears to measure "exposure" in a single assessment. Possible bioequivalence acceptance criteria are: p < or =1.40, rhom, < or =0.35, deltaa, < or =0.27, and deltas < or =0.102.

CONCLUSIONS

These DCC metrics, particularly rhom, are promising bioequivalence metrics for "exposure."

The role of metabolites in bioequivalency assessment. III. Highly variable drugs with linear kinetics and first-pass effect

PURPOSE

Simulated pharmacokinetic (PK) studies were done to determine the effect of intrinsic clearance (CL(INT)) on the probability of meeting bioequivalence criteria for extent (AUC) and rate (Cmax) of drug absorption when the absorption rate and fraction absorbed (F) were formulated either to be equivalent or to differ by 25%.

METHODS

Simulated PK studies were done using a linear first-pass model with CL(INT) values ranging from 15 L/HR to 900 L/HR. Test/Reference absorption rate constants (Ka) and fraction absorbed (Fa) ratios of 1.0 or 1.25 were used for all simulations. The impact of the value of CL(INT) and its intrasubject variation upon the probability of concluding bioequivalence at the two different Ka and F ratios was studied. Additionally, the effect of fraction metabolized i.v., (Fm) on the probabilities of concluding equivalence was studied at values of 0.25 and 0.75.

RESULTS

When CL(INT) values were raised above those for liver blood flow, the frequency of trials in which bioequivalence was correctly declared decreased when parent AUC was used as a bioequivalence criterion. Only when CL(INT) exceeded liver blood flow did the metabolite become important in assessing extent of absorption.

CONCLUSIONS

The Cmax for the parent drug provided the most accurate assessment of bioequivalence. The Cmax for the metabolite was insensitive to changes related to rate of input, and when CL(INT) exceeded liver blood flow, evaluation of the metabolite Cmax data may lead to a conclusion of bioequivalence for products that were not.

Bioavailability of carbamazepine from four different products and the occurrence of side effects

The relative bioavailability of four different carbamazepine products, showing large differences in in vitro dissolution profiles, was studied in healthy volunteers to correlate the occurrence of side effects with a measure of the rate of absorption in vivo for bioequivalence testing. Two of the three generic products investigated showed bioequivalence with respect to the extent of absorption with Tegretol. In vivo, the differences found in absorption rate were reflected in the occurrence of side effects, especially dizziness. As a measure for the rate of absorption, the partial AUC did not seem to be a good characteristic to test bioequivalence, as the variability is very high and dependent on the AUC taken. The Cmax/AUCpart seems more promising, especially the partial AUC directly after completion of the absorption process. The variability is low in the case of carbamazepine after a single dose. However, as long as no consensus on the use of other metrics and the objective (clinical or quality control aspects) of bioequivalence testing is reached, and no other pharmacokinetic characteristic is validated, Cmax should be the characteristic of choice for the rate of absorption in single-dose studies with carbamazepine products.