Andre J. Jackson

The role of metabolites in bioequivalency assessment. I. Linear pharmacokinetics without first-pass effect.

The estimation of bioequivalency using metabolite data was investigated for immediate release formulations with drugs exhibiting linear pharmacokinetics and no first-pass effect. This was accomplished by generating parent drug and metabolite plasma level profiles assuming formation and excretion rate-limited pharmacokinetic models with absorption rate constants obtained from bivariate normal distributions and designated random errors. Simulation results indicated that bioequivalence determination using Cmaxof parent drug and metabolite was independent of the metabolite models as evaluated by confidence interval approach. However, a clear difference with respect to the outcome of bioequivalence evaluation arises depending upon the utilization of Cmax values for the parent drug and metabolite. The major reason for this disparity was attributed to the minimal effect of the absorption process for the parent drug on the formation of the metabolite. This phenomenon results in an apparent lower intrasubject variability for Cmax of the metabolite and, in turn, a tighter confidence interval for Cmax of the metabolite in comparison with the parent drug. The simulated results have been found to be in agreement with the bioequivalency data for acetohexamide, allopurinol, procainamide, and sulindac. In all cases, the interval of the 90% confidence limit for Cmax of the metabolite is always smaller than that of the parent drug, regardless of the drug pharmacokinetics and the level of error contained in the data.

Comparison of Single and Multiple Dose Pharmacokinetics Using Clinical Bioequivalence Data and Monte Carlo Simulations

The purpose of this study was to evaluate the relative performance and usefulness of single dose (SD) and multiple dose (MD) regimens for bioequivalence (BE) determination. Drugs such as indomethacin, procainamide, erythromycin, quinidine, nifedipine were tested for BE under SD and MD dose regimens. Drugs characterized by low accumulation indices (AI) showed virtually no change in the 90% confidence interval (CI) of AUC and CMAX upon multiple dosing. On the other hand, drugs with higher AI appeared to have smaller CI at steady-state. For example, the CI range of AUC and CMAX of quinidine (AI of 1.54) decreased from 26 to 12 and from 22 to 12, respectively, upon multiple dosing. A Monte Carlo simulation study of SD and MD bioequivalence trials was performed. The probability of failing the bioequivalence test was evaluated for several situations defined by different levels of variability and correlation in ka constants, presence or absence of inter- and/or intra-individual variability in clearance (CL) and volume of distribution (V), and different degrees of accumulation. All the possible combinations of these factors were tested with SD and MD study designs. All simulations used 1000 data sets with 30 subjects in each data set for a total of 144 unique designs (total of 144,000 simulations of bioequivalence trials). Upon multiple dosing, narrowing of CI ranges was observed for drugs simulated to have high AI, high variability and a large difference in absorption constants (ka) between test and reference formulations. The mean AUC and CMAX CI ranges for this situation decreased from 15 to 6 and from 16 to 10, respectively, in going from SD to MD design. Thus, there was concordance between simulated and experimental data. The probability of failing the bioequivalence test is shown to dramatically decrease upon multiple dosing due to the changes (range and shift) in the confidence interval.

Evaluation of Bioequivalence of Highly Variable Drugs Using Monte Carlo Simulations. I. Estimation of Rate of Absorption for Single and Multiple Dose Trials Using Cmax

AbstractPurpose. A Monte Carlo simulation study was done to investigate the effects of high intrasubject variation in clearance (CL), and volume of distribution (V) on the calculation of the 90% confidence interval (CI) for Cmax for single dose and multiple dose studies. Methods. Simulations were done for both immediate release and sustained release scenarios. The simulated data were compared with clinical data from bioequivalence studies performed on indomethacin and verapamil. Results. Previous reviews and simulations have shown that the probability of failure for the Cmax for single dose studies was always greater than that for multiple dose studies. However, the results for the simulated scenarios currently investigated indicate that if intrasubject (period-to-period) variation in CL and V is high (% CVs above 25%, and 12%, respectively), multiple dose studies can exhibit a higher probability of failure for Cmax than do single dose studies. Furthermore, Cmax values from studies performed with a sustained release scenario are more sensitive to changes in Ka, CL, and V than are results of studies on immediate release products. As an example, the probability of failure for immediate release products in simulated single dose studies is about 11% and 21% when the mean difference in Ka is 10% and 20%, respectively; while, the probability of failure for multiple dose studies is about 36% regardless of the difference in Ka. The corresponding values for the probability of failure for sustained release products were 25%, 53% for single dose studies and 39% for multiple dose studies. The simulations also indicate that changes in the fraction absorbed have a greater effect on the estimation of Cmax in multiple dose regimens than in single dose studies. Conclusions. The results from these investigations indicate that multiple dose studies do not necessarily always reduce variability in Cmax.

The role of metabolites in bioequivalency assessment. II. Drugs with linear pharmacokinetics and first-pass effect.

Simulations were conducted to address the question of whether metabolite data are required for bioequivalence evaluation of immediate release formulations with drugs exhibiting linear pharmacokinetics and first-pass effect. Plasma level-time profiles were generated for parent drug and metabolite using relevant rate constants obtained from a bivariate normal distribution and designated random error. Simulation results showed that the need for metabolite data (Cmax) in the assessment of bioequivalence depends on the relative variability between the absorption process of the drug and first-pass route for metabolite(s). The importance of metabolite Cmax data in the evaluation of rate of availability is clearly demonstrated for drugs with a high degree of intra-subject variation in the first-pass metabolism compared to the absorption process of the drug. Under such conditions, a wider confidence interval was found for the metabolite rather than parent drug. Opposite results were obtained when the intra-subject variance was high for drug absorption relative to first-pass effect. Discrepancies were observed for the scenarios in which the elimination pathway of the metabolite is more variable than the absorption process of the drug. The simulation results were in agreement with real bioequivalence data. It is thus recommended that, in the absence of the information on the relative variability of absorption and first-pass process, both parent drug and metabolite data be included for documentation of bioequivalence, should the metabolite(s) play an important role in the determination of efficacy and safety of the drug.

The Role of Metabolites in Bioequivalency Assessment. III. Highly Variable Drugs with Linear Kinetics and First-Pass Effect

AbstractPurpose. Simulated pharmacokinetic (PK) studies were done to determine the effect of intrinsic clearance (CLINT) 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 CLINT 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 CLINT 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 CLINT 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 CLINT 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 CLINT exceeded liver blood flow, evaluation of the metabolite Cmax data may lead to a conclusion of bioequivalence for products that were not.

Use of Partial AUC (PAUC) to Evaluate Bioequivalence—A Case Study with Complex Absorption: Methylphenidate

ABSTRACTPurposeMethylphenidate modified-release products produce early and late peak concentrations critical for treatment of morning and afternoon symptoms of attention deficit hyperactivity disorder (ADHD). Standard bioequivalence (BE) criteria cannot be applied to these products. The performance of partial area under the drug concentration-time curve (PAUC), Cmax and AUCINF to assess BE were independently evaluated for two products.MethodsA two-stage analysis was performed on plasma data for two methylphenidate modified-release products (Product 1 and 2). Simulations using the fitted parameters determined how changes in fast absorption rate constant (K0Fast) and fraction available (F1) affected curve shape and BE determination using Cmax, AUCINF and PAUC.ResultsThe sensitivity of the mean PAUC(test)/PAUC(reference) ratios to changes in K0Fast(test) are product dependent. Product 1 mean PAUC(test)/PAUC(reference) ratios for PAUC0-4h are more responsive to both decreases and increases in K0Fast(test) than Product 2. Product 2 showed a greater response in the mean PAUC(test)/PAUC(reference) ratio for PAUC0-4h when the K0Fast(test) is decreased and less response as the value is increased.ConclusionsPAUC estimated curve shape is sensitive to changes in absorption and are product specific, and may require a new PAUC metric for each drug. A non-product specific metric to assess curve shape is warranted.

Role of metabolites for drugs that undergo nonlinear first-pass effect: Impact on bioequivalency assessment using single-dose simulations

We investigated the effects of dose and intrasubject variability (ISV) on bioequivalence (BE) of a parent drug with a single metabolite formed by nonlinear first-pass. A BE simulation was done using a four-compartment model at doses of 17.5, 35.0, and 70.0 mg. ISV was set at either 10% or 20% for clearance and either 20% or 50% for the absorption rate constant, K(a). The ratio of Katest/Kreference was fixed at 1.00 while fraction available ratios, F(test)/F(reference), were varied from 1.00 to 1.25. Results showed the probability of passing the 90% confidence interval (CI) BE requirement for AUC(I), area-under-the-concentration curve to time infinity, and C(max), concentration maximum, were greater for the metabolite than the parent at all F(test)/F(reference) ratios. For the parent, the probability of meeting BE criteria for AUC(I) and C(max) declined from 100% to 60% at the 70 mg dose as the ISV for K(a) increased from 20% to 50% with an increased F(test)/F(reference) ratio. For the metabolite, the probability of meeting BE criteria was above 80% for all doses and ISV values and F(test)/F(reference) ratios less than 1.15. Results show that the parent, reflected absorption, is more informative for determining BE than the metabolite. Clinical data gave a similar result.

Use of Truncated Areas to Measure Extent of Drug Absorption in Bioequivalence Studies: Effects of Drug Absorption Rate and Elimination Rate Variability on this Metric

AbstractPurpose. To compare the applicability and accuracy of truncated area (AUCt; where t represents truncated time) versus area to the last quantifiable time point [AUC(O-T)] for assessing bioequivalence. Drugs with either very low or very high intra-subject variability in clearance (CL) were selected for study. Clearance variability was defined by the number of subjects with a quantifiable plasma value (Cp) at each collection time from 24 hrs to last collection time (T). Methods. Data for amiodarone and danazol, drugs with different distributions of subject CL were examined. For amiodarone, the number of subject samples observed (test + reference) at the time of the last quantifiable concentrations was 60 at 240 hrs(T), 16 at 144 hrs and 4 at 96 hrs; while danazol had 4 at 96 hr(T), 3 at 72 hrs, 16 at 60 hrs, 7 at 48 hrs, 14 at 36 hrs, 11 at 24 hrs, 13 and 2 at 16 and 12 hrs, respectively. Simulations (Scenarios A and B) were performed to obtain populations (N = 24) with CL patterns similar to those of amiodarone and danazol. For scenario A (CL pattern similar to amiodarone), log-normally distributed CL values (28.8 L/HR) with intra-subject coefficient of variation (CV) of 25%, 40% and 60% gave the desired CL pattern. Scenario B (CL pattern similar to danazol) required that a subpopulation with an increase in CL of 40% from baseline (i.e., 40.32 L/HR) in 5%, 10% and 20% of the population represent the desired distribution. Power was evaluated by the percentage of times the simulated trials were declared bioequivalent (i.e., the number of times the test vs. reference 90% CI was within 80−125%), while accuracy was determined when the true difference in fraction absorbed (i.e., 1.25) was within the CI. Each simulation was repeated 300 times. Results. The simulation results for Scenario A indicated that the statistical results using truncated area (AUCt) had power and accuracy equivalent to that obtained using the AUC(O-T) metric. However, results for Scenario B indicated that AUCt had less power and accuracy than that obtained using AUC(O-T). The confidence interval (CI) for amiodarone was the same whether AUC (0-T) or AUCt was used as the metric for extent, while for danazol, the AUC(O-T) and AUCt differed in the lower limit by 7%. Conclusions. The truncated area, AUCt, has the greatest power and accuracy when the population clearance is such that most subjects have measurable plasma concentrations at last collection time(T), resulting in a proportional loss of data from each subject.

Evaluation of a Cmin and a normalized Cmin method for the confirmation of steady-state in bioequivalence studies

AbstractPurpose. Two methods to confirm attainment of steady-state conditions in multiple-dose bioequivalence studies are described and evaluated: (1) the Cmin method and (2) the Area Below the Cmin plasma-concentration-versus-time-curve method (ABCM method). Methods. Cmin Method—After repetitive drug administration to presumed steady-state, successive trough, or Cmin, values are evaluated to determine if they are equal. ABCM Method—The ABCM of successive doses from dose two to presumed steady-state [ABCM(ss)] are divided by the ABCM for the first dose, ABCM(t), to give ABCM(ss)/ ABCM(t)=R, which describes the increase in ABCM(n) with successive doses. The quantity, R, is then divided by an accumulation ratio to render the value independent of intra-subject clearance differences. Monte Carlo simulations were done to test the effects of data error and slow-clearing subpopulations on the methods performance. Data from multiple-dose bioequivalence studies were evaluated using confidence intervals for both methods to determine how well each predicted steady-state for immediate-release and controlled-release drug products. Results/Conclusions. The Cmin method more accurately predicted the attainment of steady-state conditions for immediate-release formulations compared to the ABCM method. Conversely, the ABCM procedure more accurately predicted the attainment of steady-state conditions for controlled-release formulations compared to the Cmin method. The simulation results were further supported by the experimental data.

Determination of in Vivo Bioequivalence

The May and June 2001 issues of Pharmaceutical Research contained three articles related to the determination of in vivo Bioequivalence (1-3). The articles discussed: (a) the bioequivalence of highly variable drugs, (b) novel metrics for direct comparison of bioequivalence study plasma curves, and (c) the role of a microemulsion vehicle on cutaneous bioequivalence.An analysis of the relationship and potential impact of these articles on their respective areas of bioequivalence will be addressed in this commentory.