PhRMA perspective on population and individual bioequivalence

The Food and Drug Administration (FDA) issued a second-draft guidance in August 1999 on the subject of in vivo bioequivalence, which is based on the concepts of individual and population bioequivalence (IBE and PBE, respectively). The intention of this guidance is to replace the 1992 guidance that requires that in vivo bioequivalence be demonstrated by average bioequivalence (ABE). Although the concepts of population and individual bioequivalence are intuitively reasonable, a detailed review of the literature has not uncovered clinical evidence to justify the additional burden to the innovator and generic companies as well as the consumer that the new guidelines would impose. The criteria for bioequivalence described in the draft guidance employ aggregate statistics that combine information about differences in bioavailability between formulation means and differences in bioavailability variation of formulations between and within subjects. The purely technical aspects of the statistical approach are reasonably sound. However, PhRMA believes that important operational issues remain that need to be resolved before any changes to current practice are implemented. PhRMA believes that the ideals of prescribability and switchability are intuitively reasonable, but it is uncertain of the extent to which the proposed guidance can achieve these goals. It is not clear whether the attainment of such goals is necessary in the evaluation of bioequivalence given the role this plays in drug development, and the lack of clinical evidence argues against a pressing need to change current practice. PhRMA is concerned that the trade-off offered by the aggregate criteria may ultimately represent more harm than good to the public interest. PhRMA recommends more rigorous evaluation of methods based on two-way crossover designs before moving to methods that require more complex designs. One such method is identified herein and contains procedures for estimating prescribability and switchability. The possibility of a phase-in or trial period to collect replicate crossover data to further evaluate IBE and PBE and possibly allow market access based on these criteria as they are being evaluated has been proposed. PhRMA believes this is unprecedented and will offer little additional information beyond that which can be obtained by simulation or has already been collected by the FDA. Simulation studies have the advantage of allowing evaluation of the sensitivity of various procedures to represent the data patterns as created within the simulation. Operating characteristics by which proposed criteria can be adequately judged have not yet been defined. The limitations of ABE for highly variable drugs and narrow therapeutic drugs are well appreciated and may be addressed by means other than a wholesale change in the current criteria.     

Population and individual bioequivalence: lessons from real data and simulation studies

The Food and Drug Administration (FDA) has proposed replacing the 1992 average bioequivalence (ABE) with population and individual bioequivalence (PBE & IBE), as outlined in the preliminary draft guidance of December 1997, which was subsequently replaced by the draft guidances of August 1999 and resolved in the final guidance of October 2000. This has led to considerable public debate among regulatory, academic, and industry experts at numerous conferences (e.g., FDA/AAPS March 1998, FDA/AAPS August-September 1999, FDA Pharmaceutical Sciences Advisory Committee September 1999) and in the literature. The final guidance calls for ABE to remain as the primary criterion by which new formulations may be judged ready for access to the marketplace. In addition, the FDA recommends the use of replicate study designs for the specific drug classes of controlled-release formulations and highly variable drugs. The final guidance also alludes to the possibility of a sponsor requesting alternative criteria such as PBE and IBE following consultation with the FDA. This procedure amounts to a data collection period during which data suitable to evaluate the operating characteristics of PBE and IBE would be generated, analyzed, and discussed among interested parties. A comprehensive review of currently available databases is useful in determining the ultimate value of this data collection period. This report provides an update to the previous publication by the authors. In all, 28 data sets from 20 replicate cross-over bioequivalence studies have been analyzed (n = 12-96) using the statistical methodology in the most recent FDA draft guidance. The results are presented below. ABE Pass: ABE Fail: Total: AUC/Cmax AUC/Cmax AUC/Cmax AUC/Cmax Pass PBE & IBE 20/14 1/3 21/17 Pass IBE only 1/0 0/0 1/0 Fail PBE and IBE 0/2 0/1 0/3 Fail IBE only 2/3 4/5 6/8 Total 23/19 5/9 28/28 Review of the database reveals many interesting features, most notably the lack of consistent results within a given data set across all three criteria. The sensitivity of subject-by-formulation interaction to sample size and inherent variability of the compounds is further explored through simulation studies. It is concluded that additional simulation assessments must be considered when evaluating the value of a data collection period for PBE and IBE assessment. It will be shown that definitive conclusions regarding some of the operating characteristics of PBE and IBE can be achieved through a combination of data-driven hypotheses followed by simulation studies to further evaluate the hypotheses. Some recommendations for further data collection will be made.     

Consideration of individual bioequivalence

Current procedures for assessing the bioequivalence of two formulations are based on the concept of average bioequivalence. That is, they assess whether the average responses between individuals on the two formulations are similar. Average bioequivalence, however, is not sufficient to guarantee that an individual patient could be expected to respond similarly to the two formulations. To have reasonable assurance that an individual patient could be switched from a therapeutically successful formulation to a different formulation (e.g., a generic substitute) requires a different notion of bioequivalence. We propose a simple, valid statistical procedure for assessing individual bioequivalence. The decision rule, TIER (Test of Individual Equivalence Ratios), requires the specification of the minimum proportion of subjects in the applicable population for which the two formulations being tested must be bioequivalent (a regulatory decision). The TIER rule is summarized in terms of the minimum number of subjects with bioavailability ratios falling within the specified equivalence interval necessary to be able to claim bioequivalence for given sample size and Type I (alpha) error. We recommend that the corresponding lower bounds (one-sided confidence intervals) for the proportion of bioequivalent subjects be calculated. TIER is partly motivated by the U.S. FDA's 75/75 Rule (at least 75% of the individual subject bioavailability ratios must be within 75-125%). TIER retains the sensible idea of considering the individual ratios but, unlike the 75/75 rule, is a statistically valid procedure.     

Consideration of individual bioequivalence

Current procedures for assessing the bioequivatence of two formulations are based on the concept of average bioequivalence. That is, they assess whether the average responses between individuals on the two formulations are similar. Average bioequivalence, however, is not sufficient to guarantee that an individual patient could be expected to respond similarly to the two formulations. To have reasonable assurance that an individual patient could be switched from a therapeutically successful formulation to a different formulation (e.g., a generic substitute) requires a different notion of bioequivalence, which we refer to as individual (or within-subject) bioequivalence. We propose a simple, valid statistical procedure for assessing individual bioequivalence. The decision rule, TIER (Test of Individual Equivalence Ratios), requires the specification of the minimum proportion of subjects in the applicable population for which the two formulations being tested must be bioequivalent (a regulatory decision). The TIER rule is summarized in terms of the minimum number of subjects with bioavailability ratios falling within the specified equivalence interval necessary to be able to claim bioequivalence for given sample size and Type I () error. We recommend that the corresponding lower bounds (one-sided confidence intervals) for the proportion of bioequivalent subjects be calculated. TIER is partly motivated by the U.S. FDA's 75/75 Rule (at least 75% of the individual subject bioavailability ratios must be within 75–125%). TIER retains the sensible idea of considering the individual ratios but, unlike the 75/75 rule, is a statistically valid procedure.     

Bridging bioequivalence studies

In some new regions, an innovative drug of the original region was not marketed. However, after the patent of the innovative drug is expired, a generic copy of the innovative drug from the original region was introduced and approved for marketing in the new region. Another generic copy manufactured by the local sponsor of the new region is seeking for approval in the new region. Despite unavailability of the innovative drug, the regulatory authority of the new region still wants to approve the local generic copy based on assessment of bioequivalence between the local generic drug and the innovative drug. Following the bridging concept suggested by the ICH E5 guidance, we propose a method to evaluate average bioequivalence between the generic copy of the new region and the innovative drug of the original region using the generic copy of the original region as the bridging reference formulation. Sample size required by the bioequivalence study in the new region is also provided. Numerical examples illustrate the proposed method.     

Evaluation of some properties of individual bioequivalence (IBE) from replicate-design studies

BACKGROUND: One of the claimed benefits of the individual bioequivalence (IBE) approach has been that the aggregate regulatory model rewards a test formulation when it has a within-subject variation smaller than the reference product. Hauck et al. [1996] demonstrated that, in the absence of random variations, this property of IBE was due to the tradeoff between the difference of the means and the deviation between the intrasubject variances of the two formulations. The tradeoff was a consequence of the aggregate regulatory model. However, calculations of Endrenyi and Hao [1998] showed that, in the presence of random variations, not only rewards but also penalties can arise due to chance alone. METHODS: A data set of 55 investigations made public by the FDA in 1999 and containing replicate crossover designs was analyzed. Two parameters, AUC and Cmax, were determined in each investigation. RESULTS: The analyses of the FDA data indicate that: rewards and penalties occur at similar frequencies, large rewards and penalties are recorded quite often, and the aggregate IBE model is rather insensitive to the difference between the estimated means and is compatible with the frequent occurrence of large deviations. CONCLUSION: Rewards and penalties, apparently arising from random variations, can affect regulatory decisions on the acceptance of IBE and can lead to incorrect conclusions.     

个体生物等效性检验的样本含量估计

目的:对两种设计方法、三种检验方法的个体生物等效性的检验效能进行比较,并估计样本含量。方法:采用Monte-Carlo模拟研究。结果:2×4交叉设计所需的样本含量低于2×3设计。在个体内变异小于0.2时,可以采用估计法进行样本含量的估计;在个体内变异接近0.2时,可以采用检验法进行样本含量的估计;在个体内变异大于0.3时,可以选任一方法(估计法和检验法)估计样本含量,并选择合适的方法进行样本含量的估计。结论:个体生物等效性的样本含量因不同的个体内变异和个体与药物间的交互作用、设计而不同。     

Comparison of average and population bioequivalence approach

AIMS: We investigated the comparison of average bioequivalence approach and population approach using bioequivalence study data which have been reported. MATERIALS: On MEDLINE, "bioequivalence" was entered as a key word to search in the 3 journals which were published between 1980 and 1989. Consequently, a total of 17 data sets on AUC and 12 data sets on Cmax were obtained and analyzed in this review. METHOD: Assessment of average bioequivalence, assessment of population bioequivalence and assessment of inequality of variance (F-test) were conducted after all data were subjected to logarithmic conversion. RESULTS: Of the data sets which were analyzed in this review, 11 data sets on AUC and 3 data sets on Cmax passed the average bioequivalence criterion, and 13 data sets on AUC and 8 data sets on Cmax passed the population bioequivalence criterion. Two data sets on AUC and 1 data set on Cmax passed the average bioequivalence criterion, but not the population bioequivalence criterion. Four data sets on AUC and 6 data sets on Cmax passed the population bioequivalence criterion, but not the average bioequivalence criterion. The correlation coefficient (r) for the population bioequivalence value and difference in the average bioavailability was 0.412, while the correlation coefficient for the population bioequivalence value and the difference in bioavailability variances was 0.708. CONCLUSIONS: In this review using bioequivalence study papers which have been reported in references, the episodes to judge that the test formulation is bioequivalent to the reference formulation occurred more predominantly in the population bioequivalence approach than in the average bioequivalence approach, and population bioequivalence approach might be affected more extensively by the bioavailability variance rather than by the average bioavailability.     

On tier method for assessment of individual bioequivalence

The bioavailability and bioequivalence between drug products has become an important subject in drug development. The average bioavailability of the test (T) and the reference (R) products is currently specified in the FDA guidelines to be used for assessing the bioequivalence of the drug products. However, it has been recognized that the safety for the substitution of a reference drug product with a test drug product in patients, whose concentration may have been titrated to a steady efficacious and safe level, could be a concern. Therefore, it is suggested that individual bioequivalence within each subject be assessed to assure the safety of the drug switchability. This paper examines the statistical properties of TIER procedure that Anderson and Hauck (1) proposed to assess individual bioequivalence. It is shown that Anderson and Hauck's procedure could be improved by imposing some distribution assumption such as lognormal distribution for assessment of individual bioequivalence. This paper also compares the relative performance of the individual bioequivalence based on TIER procedure and the average bioequivalence based on two one-sided tests procedure suggested by Schuirmann (2). The relationship between equivalence limits for the improved TIER procedure and average bioequivalence is also examined.     

Towards a practical strategy for assessing individual bioequivalence

Bioequivalence of two drug formulations is currently defined by drug regulatory authorities in terms of the mean responses following administration of the test and reference formulations (average bioequivalence). However, the various potential shortcomings of average bioequivalence are now understood, and switchability, and thus individual bioequivalence, has become a reasonable expectation when changing from one pharmaceutically equivalent drug product to another. Progress has been made in developing criteria for individual bioequivalence, and an overview and classification of most of the different approaches to the assessment of individual bioequivalence have been achieved. As a consequence of this classification, the different character of scaled and unscaled bioequivalence measures has been recognized and, in turn, this leads to the proposal, made in this paper, of using both scaled and unscaled criteria for bioequivalence assessment of different classes of drugs, depending on their within-subject variability and therapeutic range. This strategy addresses the shortcomings of average bioequivalence, and, when applied to data sets from bioequivalence studies with four-period replicate crossover designs, turns out to have some satisfactory properties. Open questions and areas for further research are discussed. Members of the working group: Mei-Ling Chen and Rabi Patnaik (Co-chairmen), Fred Balch, Keith Chan, Larry Lesko, Tom Ludden, Stella Machado, Donald Schuirmann, and Roger Williams.     

The bootstrap in bioequivalence studies

In 1997, the U.S. Food and Drug Administration (FDA) suggested in its draft guidance the use of new concepts for assessing the bioequivalence of two drug formulations, namely, the concepts of population and individual bioequivalence. Aggregate moment-based and probability-based measures of bioequivalence were introduced to derive criteria in order to decide whether two formulations should be regarded as bioequivalent or not. The statistical decision may be made via a nonparametric bootstrap percentile interval. In this article, we review the history of population and individual bioequivalence with special focus on the role of the bootstrap in this context.     

Percutaneous ibuprofen therapy with Trauma-Dolgit gel: bioequivalence studies

The plasma and tissue kinetics of ibuprofen after topical application of 5% Trauma-Dolgit gel were determined in two bioequivalence studies. In eight patients, high ibuprofen concentrations, largely within the therapeutic range, were found in subcutaneous tissue, tendon, muscles and joint capsule. In plasma, however, very low concentrations (decimal exponents below the therapeutically relevant plasma ibuprofen level even after repeated application) were found in nine volunteers. Based upon the comparison of oral and topical ibuprofen forms, the test preparation was found to be bioequivalent and, from a kinetic viewpoint, safe and effective.     

Carry-over effects in bioequivalence studies.

Carry-over effects are often considered to be one of the main problems of the cross-over design: should we adjust for carry-over or not? We attempt to answer this question by examining the observed frequency of carry-over effects in actual bioequivalence studies. A total of 96 six-sequence, three-period, three-treatment fed-fasted studies are analyzed for carry-over effects and 324 two-sequence, two-period, two-treatment fasted studies are analyzed indirectly for carry-over effects via sequence effects. Two log-transformed pharmacokinetic variables, Cmax and AUC0-t, are modeled in an analysis of variance. The impact of statistically significant carry-over effects on bioequivalence results is examined and the rationale behind not adjusting for carry-over in bioequivalence studies is discussed.     

人体生物等效性试验设计的伦理思考

药物临床试验首先要符合伦理学原则，伦理学原则要求受试者最大程度受益和尽可能避免伤害。依据此原则，本文对一些特殊药品人体生物等效性试验设计中的伦理问题进行了思考。     

盐酸曲美他嗪片在健康人体内的药代动力学研究及生物等效性评价

目的:建立人血浆中盐酸曲美他嗪浓度的LC-MS/MS法,并用于盐酸曲美他嗪片的药代动力学和生物等效性研究。方法:采用自身双交叉试验设计,20名男性受试者随机分成2组,分别单剂量口服20 mg受试制剂或参比制剂,0～24 h间隔采集血样。以LC-MS/MS内标法(盐酸丁咯地尔)测定盐酸曲美他嗪血药浓度,采用Inertsil ODS-2色谱柱(250 mm×4.6 mm,5μm),流动相为甲醇-含0.1%甲酸、0.2%醋酸铵的水溶液(55∶45,v/v);多反应监测[M+H]+离子通道分别为m/z 267→181(曲美他嗪)和m/z 308→237(丁咯地尔)。DAS 2.1计算药代动力学参数。结果:建立的LC-MS/MS法在0.5～200μg.L-1范围内线性关系良好,最低检测限为0.05μg.L-1,批内及批间精密度RSD均小于15%。受试制剂与参比制剂的Tmax分别为(1.8±0.7)h和(1.8±0.8)h,Cmax分别为(60.1±10.7)μg.L-1和(59.6±10.5)μg.L-1,t1/2分别为(6.1±1.1)h和(6.1±1.0)h,AUC0-24 h分别为(518±126)h.μg.L-1和(518±120)h.μg.L-1。结论:建立的LC-MS/MS法准确可靠,可用于盐酸曲美他嗪片的药代动力学和生物等效性评价。