Sampling times and genotyping concerns in bioequivalence evaluation of branded and generic formulations

Dear editor

We read with great interest the study by Del Tacca et al,1 who performed a comparative pharmacokinetic (PK) and pharmacodynamic (PD) evaluation of branded and generic formulations of meloxicam in healthy male subjects, and concluded that the two products can be used interchangeably in clinical practice. We especially appreciate their exploratory study on the PD/PK relationship which provides an important reference for bioequivalence studies of analgesics. However, we found two points worthy of discussion and we would like to share our perspectives in the following paragraphs.

Sampling times

The design of the sampling times plays an important role in the reliability of the bioequivalence evaluation. A sufficient number of samples to adequately describe the plasma concentration-time profile should be collected. The sampling schedule should include frequent sampling around predicted time to maximal plasma concentration (T_max) to provide a reliable estimate of peak exposure, and it should also cover the plasma concentration time curve long enough to provide a reliable estimate of the extent of exposure which will be achieved if area under the plasma concentration-time curve (AUC) from time zero to the last measurable concentration (AUC_(0–t)) covers at least 80% of AUC from time zero to infinity (AUC_(0–inf)).2 Generally at least three to four samples are needed during the terminal log-linear phase.2 The total sampling points (not including predose) should not be less than twelve.3 However, only eight blood samples, after dosing, per subject were taken in the study by Del Tacca et al.1 The duration of sampling is usually at least three times the terminal half-life (t_1/2β) of the measured compound for immediate-release products.3 However, a sampling period longer than 72 hours is not considered necessary for any immediate release formulation irrespective of the half-life of the drug.2 Literature shows that t_1/2β of meloxicam is approximately 20 hours.4,5 Theoretically, the last sampling point should be at least 60 hours after ingestion of meloxicam instead of 24 hours after dosing as in Del Tacca et al’s study. The mean AUC_(0–24) and AUC_(0–inf) values of meloxicam derived from a single dose of 15 mg Mobic (Boehringer Ingelheim GmbH, Ingelheim, Germany) were 18.49 mg × h/L and 33.25 mg × h/L, respectively. Meloxicam AUC_(0–t) covered only 55.6% of the AUC_(0–inf), which was not in accordance with the criteria (≥80%) established by European Medicines Agency (EMA) guidelines. Although this article notes that the main study objective is not to investigate the complete PK profiles of meloxicam in healthy volunteers but rather to compare PK and PD patterns between branded and generic meloxicam, the results of bioequivalence evaluation would be more convincing if the industry guideline was well followed, especially regarding that the lower limit of quantification (LLOQ) for the analytical method established by Del Tacca et al1 has met the criteria of EMA (ie, higher than 1/20 of maximum concentration [C_max]).2

Genotyping of subjects

Potential sources of variability, such as genetic polymorphism, should be identified and taken into account when designing the bioequivalence study. Poor metabolizers (PMs) may be excluded from bioequivalence studies in order to minimize risk to subjects (ie, possible harm caused by prolonged exposure to high drug concentrations).6 EMA recommends that phenotyping and/or genotyping of subjects may be considered for safety or pharmacokinetic reasons.2 China’s State Food and Drug Administration (SFDA) and The Association of Southeast Asian Nations (ASEAN) guidelines for the conduct of bioequivalence studies specify that studies could be performed in subjects of known phenotype or genotype for the polymorphism in question if a drug is known to be subject to major genetic polymorphism.7,8 However, global consensus is unavailable with regard to the inclusion or exclusion of poor versus extensive metabolizers (EMs) as a method to decrease variability.

We performed a PubMed search covering the period from 1988 to 15 September 2013, using the search terms “bioequivalence” and “genetic polymorphism or phenotype or genotype” and additional filters (species: humans; languages: English). Forty-three articles were detected. Inclusion criteria included studies addressing the relationship of bioequivalence evaluation and genetic polymorphism in metabolizing enzyme or transporter. Four articles were finally included under this search strategy. The full text of each article was critically reviewed, and data interpretation was performed (Table 1).9–12

Table 1.

Relationship of bioequivalence evaluation and genetic polymorphism

Drug	Drug metabolizing enzyme	Relationship	Recommendations
Tenoxicam9	CYP2C9	The 90% confidence intervals of the treatment ratios for the ln-transformed values of Cmax and AUC(0–inf) were within the preset bioequivalence range of 80%–125%, regardless of all participants or either allelic variant subgroups. AUC(0–inf) and t1/2 were influenced by the presence of CYP2C9*3 allele resulting in a high variability. A non-parametric analysis indicated that the variability in AUC(0–inf) increased to 79%–117% in CYP2C9*2 and to 78%–177% in CYP2C9*3. Both groups were out of the accepted international bioequivalence range. The cause of this variability will be missed if genotyping is not performed.	CYP2C9 genotyping prior to a bioequivalence study is a useful approach.
Citalopram10	CYP2C19	CYP2C19 PMs were excluded, based on genotyping of genomic DNA from blood samples. Written informed consent regarding genotyping was given by each candidate before CYP2C19 genotype screening. Further written informed consent for bioequivalence study was obtained from twenty-four CYP2C19 EMs after screening. The 90% confidence intervals of the treatment ratios for the ln-transformed values of Cmax, AUC(0–t) and AUC(0–inf) were within the predetermined acceptance range.	Chinese have a higher incidence of CYP2C19 PMs compared with Caucasians (25% versus 2%–5%). To ensure the safety of PMs and exclude the influence of CYP2C19 genotype, CYP2C19 EMs should be chosen as subjects.
Tacrolimus11	CYP3A5	The intra-subject coefficient of variations of AUC(0–t) and Cmax in the CYP3A5*3/*3 group were about 41.1% and 52.4% greater than those in the CYP3A5*1*1 +*1/*3 group. The estimated total sample size for the bioequivalence study of tacrolimus with a 2×2 cross-over design was increased by 93.3% for AUC(0–t) (n=30 versus 58) and 121.4% for Cmax(n=28 versus 62) in the CYP3A5*3/*3 group compared with the CYP3A5*1/*1+*1/*3 group.	Genotyping for CYP3A5 will provide a more efficient approach for bioequivalence designs.
Mirtazapine12	CYP2D6	A 29.2% or 15.3% sample size reduction would be possible if the recruitment had been arranged for individuals carrying just 0 or 0 plus 1 CYP2D6 active genes (ie, PMs, intermediate metabolizers) due to the lower intra-individual variability.	In the design of bioequivalence studies of CYP2D6 substrates, screening and genotyping may play a role in reducing sample size and costs.

Abbreviations: AUC_(0–t), area under the plasma concentration-time curve from time zero to the last measurable concentration; AUC_(0–inf), area under the plasma concentration-time curve from time zero to infinity; C_max, maximum concentration; CYP, cytochrome P450; EMs, extensive metabolizers; PMs, poor metabolizers.

In bioequivalence studies, intra-individual variability is critical in determining sample size. Highly variable drugs are generally defined as those for which within-subject variability in AUC and/or C_max >30%.2 In order to conduct an acceptable bioequivalence study of a highly variable drug, higher numbers of subjects may be needed.13 With regard to the study by Del Tacca et al, coefficient of variation values were slightly above the recommended upper limit of 30% (34% for AUC_(0–24) and 33% for C_max). Genetic polymorphisms in CYP2C9 could be one of the major source of pharmacokinetic variation. CYP2C9 genotype is expected to impact the clearance of meloxicam.14 There are several allelic variants of CYP2C9, the most common are the CYP2C9*2 and CYP2C9*3, with an allele frequency in the Caucasian population respectively of 8%–18% and 4%–10%. CYP2C9*2 and CYP2C9*3 alleles show impaired activity. Subjects with genotype CYP2C9 *1/*1 (frequency of 70% in the Caucasian population) are considered normal metabolizers; individuals CYP2C9 *1/*2 (frequency of 16% in Caucasian populations), and *1/*3 (frequency of 10% in the Caucasian population) are considered poor metabolizers; subjects with genotype of *2/*2 (frequency of 1%), *2/*3 (frequency 1%) or *3/*3 (frequency of 0.3%) are very poor metabolizers.15,16 Meloxicam is primarily metabolized to a 5′-hydroxymethyl metabolite by CYP2C9 (major) and CYP3A4 (minor) and the fraction of total cytochrome P450 metabolism catalyzed by CYP2C9 in EM (wild type, CYP2C9*1/*1) subjects (f_m,CYP2C9(EM)) is ∼0.8. Tenoxicam is a cyclooxygenase (COX) inhibitor similar to meloxicam, with the same value of f_m,CYP2C9(EM).14 Salem et al recommended that CYP2C9 genotyping prior to a bioequivalence study of tenoxicam is a useful approach.9 So we postulate that it may also be applicable to meloxicam.

Furthermore, whether to perform pharmacogenetic screening prior to bioequivalence study also depends on population source. With regard to CYP2C9 genetic polymorphism, frequencies of CYP2C9*1/*3, CYP2C9*1/*2 in Chinese populations are 5.36% and 0.28%,17 respectively, obviously lower than those in Caucasians (ie, 10%, 16%, respectively). Therefore, genotyping prior to bioequivalence evaluation seems unnecessary for Chinese participants. On the contrary, with regard to CYP2C19 polymorphism, the situation is just the opposite. Incidence rate of CYP2C19 PMs in Chinese populations is far higher than that in Caucasians (25% versus 2%–5%), indicating that it is very necessary to perform genotyping or phenotyping of CYP2C19 prior to bioequivalence study of typical CYP2C19 substrates in Chinese subjects.

Del Tacca et al’s study along with our perspectives may introduce an interesting topic. As stated by Del Tacca et al, prescribing physicians cannot access any information on the preregistration development of generic drugs, and they can only trust that the regulatory authority approved a specific generic product in full accordance with recommended guidelines. Anyhow, bioequivalence study is a method of evaluating quality of generic formulations. For this purpose, both study design and variation factor control cannot be overestimated.