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1 w wz 19«1y Kor. J. Clin. Pharm., Vol. 19, No ƒ j (highly variable drug w x w x sƒ y B Á x B Á«Ÿ B B û w w w w ( Á Á Bioequivalence Approaches for Highly Variable Drugs: Issue and Solution In-hwan Baek a, Soo-hyeon Seong a, and Kwang-il Kwon a, * a College of Pharmacy, Chungnam National University, Daejeon, Korea (Received May 15, 2009ÁRevised June 12, 2009ÁAccepted June 15, 2009 Highly variable drugs (within-subject variability greater than 30% have been difficult to meet current regulatory acceptance criteria using a reasonable number of study subjects. In this study, we reviewed previous studies presenting alternative approaches for bioequivalence evaluation of highly variable drugs, and focused on an approach for widening the bioequivalence acceptance limits using within-subject variability. We discussed the suggested five solutions for highly variable drug including the deletion of C max of the bioequivalence criteria, direct expansion of bioequivalence limit, multiple dose studies in steady state, bioequivalence assessment on the metabolite, add-on study, and widening the bioequivalence acceptance limits based on reference variability. The methods for widening of bioequivalence limits based on reference variability are scaled average bioequivalence containing within-subject variability on reference drug (σ WR, population bioequivalence derived from total variability on reference drug (σ TR and test drug (σ TT, and individual bioequivalence derived from subject by formulation interaction variability (σ D and within subject variability on reference drug (σ WR and test drug (σ TR. To apply these methods, the switching variability (σ 0 will have to be set by the regulatory authorities. The proposals of bioequivalence evaluation approach for the highly variable in Korea are presented for both of new drug and reevaluation drug. Key words - Highly variable drug, bioequivalence, within-subject variability, switching variability ü KFDA (Korea Food and Drug Administration, t t w w ( x w w ü x, yx z ùkü t w w w n ƒ m w w w» w w x w. 1 x 12 e w p ƒ w, x w z, 2 2 x œ k x n 1z n w e wš. w ƒ x š, 1 Correspondence to : «Ÿ Ÿ w 79 û w w w 406y w Tel: , Fax: kwon@cnu.ac.kr z n w sƒw x š w (area under the concentration-time curve, AUC t š x (the peak or maximum concentration, C max yw m w, yw s³e 90% log 0.8 log 1.25 ü w. 1 ü x» ƒ» w j ƒ. 2,3 NIHS (the National Institute of Health Sciences x» ü» w wš, 4 FDA (Food and Drug Administration» ü» w AUC t C max m w yw s³e 90% log 0.8 log 1.25 ü w, FDA average bioequivalence (ABE š w. 5 w FDA ABE population bioequivalence (PBE individual bioequivalence (IBE wš, ƒ bioequivalence w x ww PBE IBE w. 6 50

2 ƒ j (highly variable drug w x w x sƒ 51 EMEA (European Medicines Agency ü» w AUC t C max m w yw s ³e 90% log 0.8 log 1.25 ü ³ wš., C max ƒ z w e 90% log 0.75 log 1.33 ü w y w. 7 eù HFPB sƒ w AUC t x yw s³e 90% log 0.8 log 1.25 ü ³ wù, C max 90% w ³ x yw s³e (the Geometric Mean Ratio, GMR 80% 125% ü ƒ w q wš. 8 ù» w x» w., x v w, ƒ j (highly variable drug, HVD x w wš, x» w m w w š ù ƒ j. p w x p y š w ³ p» x w w. x FDA p w w» sww w x» 15ƒ w ƒ w š š,»k w w 15ƒ ƒ ƒ wš. 9,10 EMEA w x» 7 ù 40 ƒ œ x œwš. 9,11 eù HPFB w x» p w š w 17ƒ ù ƒ œwš. 9,12 p» v w ƒ j (highly variable drug, HVD š HVD w Áü ³ š HVD w p» ( w» wš w. w» ( ƒ š z scaled average bioequivalence (SABE, population bioequivalence (PBE individual bioequivalence (IBE w š, ü y š w w HVD p» w wš w. wš ù, 16 x FDAƒ w wz American Association of Pharmaceutical Scientists (AAPS sww w z t ƒ ù t ƒ» ww ƒ AUC t C max within-subject variabilityƒ 30% HVD w. 7,17-19 FDAƒ ANDAs (Abbreviated New Drug Applications FDA m t AUC t C max within-subject variabilityƒ 30% w,» w 32% (180 57, t» w 19% (524 t 101 t, x œ x sww x z» w 11% (1010 x 111 ƒ HVD š 2008 tw. 20 t HVDƒ w y w, HVD w ƒ p ƒ dw. dw HVD p wù x vx sww w x y HVD q, p HVD w. x š HVD j v (chlorpromazine, v qr (propafenone, q (verapamil, ù (nadolol kp (simvastatin ù, 18,19,37,42,59 x ww ù v x x w w HVD š, HVD ƒ, HVD w üá x w t x ¾ w. FDA tw t HVDƒ w y w wù» HVD w t» w HVD û, œ x x sww x z» w HVDƒ w û w» ³ x vx, BE limit w HVD w qw y. ƒj IJHIMZWBSJBCMFESVH ƒ j (highly variable drug, HVD w x k w q l AUC t C max ü (withinsubject variability intra-subject variabilityƒ 30% w. 13,14,15 x AUC t C max within-subject variabilityƒ 25% HVD š w x WBSJBUJPO w x (variation j x ƒvw w (inescapable variation x w w j» w (controllable variation ù. x ƒvw w vx w w

3 52 Kor. J. Clin. Pharm., Vol. 19, No. 1, 2009 Table 1. Source of variation in bioequivalence studies Inescapable variation Controllable variation Subject differences - Between-subject variation - Within-subject variation Genetic polymorphism Formulation differences Subject-by formulation interactions Random error (between-subject variability inter-subject variability ü (within-subject variability intra-subject variability (Table 1. 21,22 ü mp (total variance w, HVD» within-subject variability x (replicated w z mw w (eq.1. σ 8M = ( χ ( O + O JML χ ML L = J = n k = k n i = vx (i=1, 2,, n k l= drug (l=test drug reference drug O L Carryover effects - Drug metabolite residue - Induction or inhibition Time factor - Sampling time - Storage factors Physiological factors - Gastric emptying - Food fluid and other drugs - Diurnal variation (eq.1 Within-subject variability x w, w, n ù (BCS class IV, x sww x, y,, x (genetic polymorphism x w. 20,23-26 w x 2 2 x w vx ƒ x ( x 1z n w x (non-replicated eq. 1 mw within-subject variability w.»k (residual variance mw w ANOVA-CV withinsubject variability w (eq.2. 18,21,27 Within subject variability ANOVA CV = ANOVA CV = residual variance 100% (eq x residual variance kw ùkù ü wš, ü variation x w»e w w (unexplained random variation sww. 18,28,29 x residual variance mw ANOVA-CV ƒw ü t t w œ w sƒ v K-BE test 2007 (ver w x w ANOVA- CV y w. ü l w w HVD HVD» w wš y w z ƒ. JHIMZWBSJBCMFESVH» w» wv w ƒ j (HVD» ƒ j x ƒ w m w» w vx ƒ v w. 14,30, within-subject variabilityƒ 35% HVD x ƒ 100% w š ƒ w x ³ AUC t C max 90% ƒ ü» w 54 ƒ v w, ƒ 5% ƒw HVD w vx»w ƒw (Table üá IJHIMZWBSJBCMFESVH» ƒ j (HVD w» w w Áü HVD w ƒ x wš. ü t t œw w» (š y, HVD w y ù ƒ j Table 2. The needed number of subjects to conclude average bioequivalence (2 2 non-replication Within subject Relative bioavailability (real difference variability (ANOVA-CV%

4 ƒ j (highly variable drug w x w x sƒ 53 n w k (steady-state g x w. 1» y w» w ƒ j w ƒ yw v ƒ, w» HVD w» k w, w š mw w. ü w HVD w x w š š wš, v» vx mw ƒ x (add-on study, n x (multiple dose study, study w š wš. 4 wz FDA t x mw HVD w» w w, HVD w» w ü xk. ƒ mw wš» average bioequivalence wš, ƒ population bioequivalence (PBE individual bioequivalence (IBE wš. PBE IBE» (BE limit w ƒƒ w reference-scaled method ƒ» w w constant-scaled method ù, ƒ j reference-scaled method constant-scaled method w z,» ƒ ( w kw w (mixed-scaled method. 6 m mw 2 2 x 4» x (replicated mw HVD w. 32 scaled average bioequivalence (SABE m wš, SABE ƒ ƒ z š w ƒ m. 33, BA/BE for HVDs/HVDPs ƒ mw HVD AUC t C max within-subject variabilityƒ 30% w, 35 z ƒ w C max ƒ z w š, x mw within-subject variabilityƒ 30%, x z C max š w 90% 75~133% y w w š š wš. 7 eù ³ C max w 90% ³ w š,»ws³ (GMR 80~125% ³ w q wš HVD w p» š w š. 8, ƒ w HVD w discussion w w variability, HVD», HVD (chloropromazine HVD p Table 3. Alternative approaches bioequivalence evaluation of highly variable drugs Method Reasonability Efficiency Deletion of C max Low High Direct expansion of BE limit Low High Multiple dose studies for steady state High Low Assessment bioequivalence on the metabolite Medium Medium Add-on study Medium Low The widening of BE limits based on reference variability High High» ( wš. 18 IJHIMZWBSJBCMFESVHp» x HVD ƒw w ƒ mw p» ù w HVD ƒ w p» ( FDA, EMEA, eù HFPB x w t mw š. HVD w p» ( j 6ƒ w (Table 3. w sƒw $ NBY ƒ j (HVD w sƒw C max ƒ AUC t j (variability ƒ. 36,37 C max ƒ HVD w q w» š ƒ w AUC t ƒ š HVD w q w p» (. AUC t» (BE limit ³ ƒ 90% ü w w» w. 38 w sƒw $ NBY» #& MJNJU y p» ( ƒ j (HVD w sƒw C max ƒ AUC t j (variability ƒ wš. 36,37 AUC t w BE limit 90% ü wš, C max w BE limit w x v w v x w» ww. 39,40 p» ( x EMEA wš, EMEA HVD w p» C max w 90%

5 54 Kor. J. Clin. Pharm., Vol. 19, No. 1, ü ³ wš. 7 n mw k TUFBEZTUBUF x n w k k HVD ü ƒ k HVD w w w ƒ w š. 41,42 x ü ƒ w š. 1 ù p» ( HVD w» š. t el-tahtawy AA n w s HVD C max monte carlo simulation mw dw., z n w n w s C max x, C max z n w n w. 41 n mw k x HVD w p» ( w ƒ š. NFUBCPMJUFd mw x ü xk w parent w y ù ƒ HVD parent d w w q w» š. 43 p terfenadine parent terfenadine AUC t C max within-subject variabilityƒ 48.3%, AUC t C max within-subject variability 14.7% j, d mw HVD t y š. 43,44 ù p» ( w» š., ƒ HVD w, w p z m z ƒ j w e d mw ƒ. 40,43 d mw HVD w» w ƒ š w w. ƒ x BEEPOTUVEZ mw x ü w, eù ƒ j (HVD w ³ w ww mw x w w within-subject variability. p» ( ƒ x mw w. x mw ƒ x ww w vx ƒ ƒw within-subject variability w p» (. 40,45 w vx ƒw HVD w» w vx v w z, Table 2 mw» w. WBSJBCJMJUZ š w» #&MJNJU y FDA EMEA, eù HFPB š HVD p» variability mw BE limit 90% ,27,39,40 variability š w BE limit y w scaled average bioequivalence (SABE, population bioequivalence (PBE, individual bioequivalence (IBEƒ, 3ƒ œm variability š Table 4. Variance and study for average bioequivalence, scaled average bioequivalence, population bioequivalence, and individual bioequivalence Bioequivalence Variation Study Average bioequivalence No variation 2 2 non-replication Scaled average bioequivalence Population bioequivalence Individual bioequivalence Within-subject variability on reference drug or residual variance Switching variance Within-subject variability on reference drug or residual variance Total variance Switching variance Within-subject variability on reference drug Within-subject variability on test drug Subject by formulation interaction variance Switching variance 2 2 non-replication 2 3, 2 4 replication 2 2 non-replication 2 3, 2 4 replication 2 3, 2 4 replication

6 ƒ j (highly variable drug w x w x sƒ 55 w switching variance ( ƒ» w w BE limit w (Table 4. 38,40,47» y w m p» ( w š z, ƒ š l w x w. 6,16,46 Scaled average bioequivalence (SABE 2 2 x mw AUC t C max s³ mw» (BE limit ü ³ w average bioequivalence š w, ùký (eq.3. 6, mean T meanr (eq. 3 yw txw txw (eq ( µ T µ R µ T : x y sƒw s³ µ R : y sƒw s³ (eq. 4 SABE ABE within-subject variability (σ WR ƒ w switching variance (σ W0 š w xw, (eq x (nonreplication study x (replication study ƒ w., 2 2 x w within-subject variability (σ WR residual variance mw w ANOVA-CV w. 46,49, σ WR µ T µ R σ W 0 ( σ W σ WR σ W0 : ƒ» w (switching variance σ WR : within-subject variability µ T : x y sƒw s³ µ R : y sƒw s³ (eq. 5 Population bioequivalence (PBE PBE s³ š w w m x total variance (σ TR, σ TT m w BE limit w. 6,51,52 Total variance ü (within-subject variability (between-subject variability ww yw w» w x (replication study w, 2 2 x (nonreplication study within-subject variability residual variance mw total variance w. PBE ³ w BE limit (θ P w eq. 6. 6,53 θ 1 (*O + ε 1 = , ε 1 = ( σ 55 σ 53 σ 5 θ P :» (BE limit σ TT : x total variance σ TR : total variance σ T0 : ƒ» w (switching variance (eq. 6 w BE limit w» w 90% eq. 7 w w. σ TR w ùkü reference-scaled method š σ T0 w ùkü constant-scaled method, ƒ j (HVD σ TR σ T0 j w 90% w (mixed-scaled method. µ 5 µ ( 3 + ( σ 55 σ 53 σ θ 1 PS µ 5 µ ( 3 + ( σ 55 σ θ 1 σ 5 θ P =» (BE limit µ T : x y sƒw s³ µ R : y sƒw s³ σ TT = x total variance σ TR = total variance σ T0 : ƒ» w (switching variance (eq. 7 x total variance w BE limit ³ w PBE x (2 2 x x ( x ƒ w x w x w f š, x w x w ƒ. Individual bioequivalence (IBE IBE x y s³ (µ T - µ R w vx formulation n w ùkú x vx y (σ D x within-subject variability (σ R σ T š w BE limit w. 2 2 x (non-replication study mw š, x

7 56 Kor. J. Clin. Pharm., Vol. 19, No. 1, 2009 x (replication study w. 6,54-56 IBE ³ w BE limit (θ I w eq. 8. θ * (*O + ε * = , ε * = σ % + ( σ 85 σ 83 σ 8 θ I :» (BE limit σ D : x vx y variance σ WT : x within-subject variability σ WR : within-subject variability σ W0 : ƒ» w (switching variance (eq. 8 w BE limit w» w 90% eq. 9 w w. PBE ƒ σ TR w ùkü reference-scaled method š σ T0 w ùkü constant-scaled method, ƒ j (HVD σ TR σ T0 j w 90% w (mixed-scaling method. µ 5 µ ( 3 + σ % + ( σ 85 σ 83 σ θ * PS µ 5 µ ( 3 + σ % + ( σ 85 σ 83 σ θ * θ I =» (BE limit µ T : x y sƒw s³ µ R : y sƒw s³ σ D : x vx y variance σ WT : x within-subject variability σ WR : within-subject variability σ W0 : ƒ» w (switching variance ƒ w TXJUDIJOHWBSJBODF σ (eq. 7 Switching variance ƒ j (HVD Table 5. Types of switching variance (σ 0 Switching variance» (BE limit w w σ D t»w, m SABE IBE σ W0, PBE σ T0 t»w. 6,50 σ D BE limit ³ w» y, switching variance 0.2, 0.223, 0.25, ƒ ƒ (Table 5. p individual bioequivalence criterion (IBC mw w 0.2 Health Canada Therapeutic Products Directotate (TPD w 0.25ƒ š. 8,16,38,47 switching variance ƒ j w xƒ» ƒ ³ w j ƒ. #&MJNJUy x w SABE, PBE, IBE within-subject variability š w BE limit y w HVD p» ( w š w, BE limit w w 1x (type I error 2x (type II error x. 15, 1x (type I error x t w x w q w, 2x (type II error t w x w q w w. 1x (type I error 2x (type II error, 1x (type I errorƒ w y ƒ w š, 2x (type II error ƒ w z ƒ w, w x w w w wù. 57,58 SABE, PBE IBE w BE limit y w 1x (type I errorƒ w ƒ f. w w y 90% wì x yw s³e (the Geometric Mean Ratio, GMR 80% 125% ³ w Calculated base The constant was calculated by individual bioequivalence criteria. 0.2 It can be most widen bioequivalence limit. The constant was calculated by = σ 0 It is useful for application to scaled average bioequivalence (SABE The constant was suggested by Health Canada The constant was calculated by 0.3= FYQ ( σ The most strict constant for establishment BE limit.

8 ƒ j (highly variable drug w x w x sƒ 57. w monte carlo simulation mw y w. Within-subject variabilityƒ 35% HVD v x 24 mw w ƒ w wš» w w y 42.6% w,» (BE limit 70% 143% ü y w p» w w y 94.1% ƒw. w 35%ƒ ƒ û wš y p» w w y 14.9% ƒ.» x yw s³e (the Geometric Mean Ratio, GMR 80% 125% ³ w, ƒ w 94% w, ƒ 35% ƒ ú w y 6.8% û. x yw s³e (GMR 80% 125% ³ w 90% y w HVD w w 1x (type I error (Table ü w IJHIMZWBSJBCMFESVH p» mw ƒ j w ƒ š w, p» ( scaled average bioequivalence (SABE, population bioequivalence (PBE, individual bioequivalence mw w» (BE limit k w y w, x yw s³e (GMR 80% 125% ³ w. w ƒ w switching variance (σ w. ü w w» ù w w z sƒ ƒ, ü p w y š w HVD w p» ( ü ü q» z z sƒw ù w. Table 6. Comparisons of bioequivalence pass rate (% by geometric mean ratio (GMR and 90% confidence interval (C.I.. Bioequivalence rate (% (within subject variability=35%, n=24 True ratio GMR 80~125% 90% C.I. 80~125% No constraint GMR. 90% C.I. 70~143% GMR 80~125% 90% C.I. 70~143% xƒ w7%p» HVD HVD withinsubject variability y q w v ƒ, ³ ƒ w v ƒ x (replicated ww withinsubject variability wš, w» (BE limit scaled average bioequivalence (SABE population bioequivalence (PBE individual bioequivalence (IBE wù kw HVD w k w. ƒ ³ w switching variance w ³ w 0.25 kw w, ³ w ƒ j (HVD within-subject variabilityƒ 25% ³ Table 7. Bioequivalence study suggested for HVD of new drug and re-evaluation drug system in Korea New drug Re-evaluation drug Biostatistics SABE PBE IBE SABE PBE IBE Study Variability 2 3 reference replicated or 2 4 replicated Within subject variability of reference drug 2 3 reference replicated or 2 4 replicated Total variance (within subject variability + between subject variability 2 4 replicated 2 2 non-replicated Within subject variability of reference drug and test Residual variance drug 2 2 non-replicated Total variance (residual variability + between subject variability 2 4 replicated Within subject variability of reference drug and test drug Switching variance

9 58 Kor. J. Clin. Pharm., Vol. 19, No. 1, 2009 w w (Table 7. z sƒ w7%p» z sƒ HVD ƒ y w, x ƒ ³ y ³ w x (replicated mw within-subject variability 2 2 x (nonreplicated mw residual variance y w w. w» (BE limit residual variance w scaled average bioequivalence (SABE population bioequivalence (PBE w. w ƒ ³ w switching variance y ³ w 0.2 kw w, p» ( w ƒ j within-subject variability ANOVA-CV (residual variance mw w within-subject variability 20% ³ w. w z ƒ w x mw SABE PBE IBE w (Table 7. ƒ j (HVD p» v š HVD p» ( wš w ƒ j w w w. 6ƒ HVD p» ( ƒ w š ü (within-subject variability mw 90% y w, w scaled average bioequivalence (SABE, population bioequivalence (PBE individual bioequivalence (IBE 3ƒ ƒ.» w» w x (replicated mw w ü (within-subject variability w š, 2 2 x (non-replicated mw»k (residual variance w ANOVA-CV (withinsubject variability w y w. w w» w ƒ w (switching variance ³ w w, ƒ ƒ. ü z sƒ p w y, ƒ j w p» ( w ³ w xƒw w w w. ƒ j x v w x, p x w x, z x w x š w x p» v w wì w w, mw ü t w w» mw ƒ y w t t ( w w. š x 1. t t. w x» (š y. : t t, Hauschke D, Steinijans VW, Diletti E. A distribution-free procedure for the statistical analysis of bioequivalence studies. Int J Clin Pharmacol Ther Toxicol 1990; 28: Schulz HU, Steinijans VW. Striving for standards in bioequivalence assessment: a review. Int J Clin Pharmacol Ther Toxicol 1992; 30: S1-S6. 4. The National Institute of Health Sciences (NIHS. Guideline for Bioequivalence Studies of Generic Product. Tokyo: The National Institute of Health Sciences (NIHS, The U.S. Food and Drug Administration (FDA. Guidance for industry: bioavailability and bioequivalence studies for orally administered drug products- general considerations. Rockville: The U.S. Food and Drug Administration (FDA, The U.S. Food and Drug Administration (FDA. Guidance for industry: statistical Approaches Establishing Bioequivalence. Rockville: The U.S. Food and Drug Administration (FDA, The Committee for Medicinal Products for Human Use (CHMP. Guidance on the Investigation of Bioequivalence. Rondon: The European Medicines Agency (EMEA, Health Canada. Guidance for Industry, Conduct and Analysis of Bioavailability and Bioequivalence Studies- Part A. Minister of Public Works and Government Services Canada,

10 ƒ j (highly variable drug w x w x sƒ Blume HH, Midha KK. Bio-international 92 Conference on Bioavailability, Bioequivalence and Pharmacokinetic Studies. Pharm Res 1993; 10: Haidar SH, Davit B, Chen ML, et al. Bioequivalence approaches for highly variable drugs and drugs products. Pharm Res 2008; 25(1: Tothfalusi L, Endrenyi L, Midha KK, et al. Evaluation of the bioequivalence of highly-variable drugs and drug products. Pharm Res 2001; 18(6: Boddy AW, Snikeri FC, Kringle RO, et al. An approach for widening the bioequivalence acceptance limits in the case of highly variable drugs. Pharm Res 1995; 12: Health Canada, Therapeutic Products Directorate (TPD. Discussion paper on Bioequivalence requirements - highly variable drugs and highly variable drug products: issues and options. Expert Advisory Committee on Bioavailability and Bioequivalence (EAC-BB Meeting, June 26-27, Buice RG, Subramanian VS, Duchin KL, et al. Bioequivalence of a highly variable drug: an experience with nadolol. Pharm Res 1996; 13(7: Davit BM, Conner DP, Fabian-Fritsch B, et al. Highly Variable Drugs: Observations from Bioequivalence Data Submitted to the FDA for New Generic Drug Applications, The AAPS Journal 2008; 10(1: Salmon S. Statistical and evaluation of bioequivalence studies average bioequivalence. WHO Prequalification program workshop, Kiev, Ukraine, June 25-27, Tothfalusi L, Endrenyi L. Evaluation of some properties of individual bioequivalence (IBE from replicate- studies. Int J Clin Pharmacol Ther 2001; 39(4: Welling PG, Tse FL. Factors contributing to variability in drug pharmacokinetics. I. Absorption. J Clin Hosp Pharm 1984; 9(3: Routledge PA. Factors contributing to variability in drug pharmacokinetics. II. Drug distribution. J Clin Hosp Pharm 1985; 10(1: Jack DB. Factors contributing to variability in drug pharmacokinetics. III. Metabolism. J Clin Hosp Pharm 1985; 10( Regårdh CG. Factors contributing to variability in drug pharmacokinetics. IV. Renal excretion. J Clin Hosp Pharm 1985; 10(4: Midha KK, Shah VP, Singh GJ, et al. Conference report: Bio-International J Pharm Sci 2007; 96(4: Patnaik R. Highly Variable Drugs and Drug Products: A Rationale for Solution of a Persistent Problem. In: AAPS Workshop on BE, BCS and Beyond, Bethesda, USA, May 21, Schuirmann DJ. A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. J. Pharmacokinet. Biopharm 1987; 15: Patterson SD, Zariffa NM, Montague TH, et al. Nontraditional study s to demonstrate average bioequivalence for highly variable drug products. Eur J Clin Pharmacol 2001; 57(9: García-Arieta A. Highly Variable Drugs. In; Understanding Bioequivalence of Generic Drugs, A Worldwide Review, Monte Carlo, June 18, Davit BM, highly variable drugs-bioequivalence issues: FDA proposal under consideration. In; Advisory Committee for Pharmaceutical Science, October 6, ohrms/dockets/ac/06/slides/ s2_5.htm 33. Haidar SH, Evaluation of a scaling approach for highly variable drugs. In: Advisory Committee for Pharmaceutical Science, Rockville, USA, October 6, Paul Fackler, Bioequivalence for highly variable drugs: session III. American Association of Pharmaceutical Scientists, San Diego, USA, November 11-15, Committee for medicinal products for human use (CHMP, Concept paper for an addendum to the note for guidance on the investigation of bioavailability and bioequivalence: evaluation of bioequivalence of highly variable drugs and drug products. European Medicines Agency (EMEA, London, April 27, Hauck WW, Parekh A, Lesko LJ, et al. Limits of 80%- 125% for AUC and 70%-143% for Cmax. What is the impact on bioequivalence studies? Int J Clin Pharmacol Ther 2001; 39(8 : Tsang YC, Pop R, Gordon P, et al. High variability in drug pharmacokinetics complicates determination of bioequivalence: experience with verapamil. Pharm Res 1996; 13(6: Midha KK, Rawson MJ, Hubbard JW. The bioequivalence of highly variable drugs and drug products. Int J Clin Pharmacol Ther 2005; 43(10 : Haidar SH, Davit B, Chen ML, et al. Bioequivalence approaches for highly variable drugs and drug products.

11 60 Kor. J. Clin. Pharm., Vol. 19, No. 1, 2009 Pharm Res 2008; 25(1: Bélisle M, Highly Variable Drugs and Drug Products (HVD/HVDP Overview. SFBC Anapharm Symposium, Newark, April 22, el-tahtawy AA, Tozer TN, Harrison F, et al. Evaluation of bioequivalence of highly variable drugs using clinical trial simulations. II: Comparison of single and multiple-dose trials using AUC and Cmax. Pharm Res. 1998; 15(1: Blume H, Zhong D, Elze M. Advantages of a steady-state crossover in assessment of bioequivalence of highly variable drugs: propafenone. European journal of pharmaceutical sciences 1994; 2(5: Jackson AJ. The role of metabolites in bioequivalency assessment. III. Highly variable drugs with linear kinetics and first-pass effect. Pharm Res 2000; 17(11: Lalonde RL, Lessard D, Gaudreault J. Population pharmacokinetics of terfenadine. Pharm Res 1996; 13(6: Patterson SD, Zariffa NM, Montague TH, et al. Nontraditional study s to demonstrate average bioequivalence for highly variable drug products. Eur J Clin Pharmacol 2001; 57(9: Karalis V, Symillides M, Macheras P. Novel scaled average bioequivalence limits based on GMR and variability considerations. Pharm Res 2004; 21(10: Tothfalusi, L ; Endrenyi, L ; Midha, K K. Scaling or wider bioequivalence limits for highly variable drugs and for the special case of Cmax. International journal of clinical pharmacology and therapeutics 2003; 41(5: Pan G, Wang Y. Average bioequivalence evaluation: general methods for pilot trials. J Biopharm Stat. 2006; 16(2: Stavchansky S, Interchangeability of Multisource Drug Products Containing Highly Variable Drugs. Kiev, Ukraine, June 25-27, Tothfalusi, Laszlo ; Endrenyi, Laszlo, Limits for the Scaled Average Bioequivalence of Highly Variable Drugs and Drug Products. Pharm Res, 2003; 20(3: Wijnand HP. Assessment of average, population and individual bioequivalence in two- and four-period crossover studies. Comput Methods Programs Biomed 2003; 70(1: Nakai K, Fujita M, Tomita M. Comparison of average and population bioequivalence approach. Int J Clin Pharmacol Ther 2002; 40(9: Chervoneva I, Hyslop T, Hauck WW. A multivariate test for population bioequivalence. Stat Med 2007; 26(6: Canafax DM, Irish WD, Moran HB, et al. An individual bioequivalence approach to compare the intrasubject variability of two ciclosporin formulations, SangCya and Neoral. Pharmacology 1999; 59(2: Endrenyi L, Tothfalusi L. Subject-by-formulation interaction in determinations of individual bioequivalence: bias and prevalence. Pharm Res 1999; 16(2: Chow SC, Shao J, Wang H. Individual bioequivalence testing under 2x3 s. Stat Med 2002; 21(5: Potvin D, DiLiberti CE, Hauck WW, et al. Sequential approaches for bioequivalence studies with crossover s. Pharm Stat 2008; 7(4: Mathew T, Paul G, A p-value for testing the equivalence of the variances of a bivariate normal distribution. J Stat Plan Inference 2008 ;138(12: Sunkara G, Reynolds CV, Pommier F, et al. Evaluation of a pharmacokinetic interaction between valsartan and simvastatin in healthy subjects. Curr Med Res Opin 2007; 23(3: