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A Comparative Analysis of Biopharmaceutics Classification
System and Biopharmaceutics Drug Disposition Classification
System: A Cross-Sectional Survey with 500 Bioequivalence
Studies
RODRIGO CRISTOFOLETTI,1CHANG CHIANN,2JENNIFER B. DRESSMAN,3SILVIA STORPIRTIS4
1Division of Bioequivalence, Brazilian Health Surveillance Agency (ANVISA), Bras´
ılia, Brazil
2Institute of Mathematics and Statistics, University of S˜
ao Paulo, S˜
ao Paulo, Brazil
3Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany
4Faculty of Pharmaceutical Sciences, University of S˜
ao Paulo, S˜
ao Paulo, Brazil
Received 13 December 2012; accepted 4 March 2013
Published online 11 April 2013 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/jps.23515
ABSTRACT: Although policies of waiving bioequivalence studies are part of the legal frame-
work of various regulatory agencies, there is no harmonization with regard to extension of the
biowaiver to drugs other than those with high solubility and high permeability, nor is there
any consensus or official endorsement of the biopharmaceutics drug disposition classification
system (BDDCS). To better understand the applicability of the biowaiver, we carried out a
cross-sectional survey to estimate the relative risk of obtaining nonbioequivalent (non-BE) or
bioinequivalent (BIE) results for drug products containing drugs belonging to each of the bio-
pharmaceutics classification system (BCS) and BDDCS classes. Five hundred bioequivalence
studies were randomly sampled from a database of the Brazilian Health Surveillance Agency
(ANVISA). The drugs were classified according to the BCS and BDDCS, to evaluate how char-
acteristics related to drug and dosage form influence the outcome of bioequivalence studies.
The relative risk of obtaining a non-BE result was approximately four times lower for drugs in
classes 1 and 3 of BCS or BDDCS when compared with class 2 drugs. Thus, it seems that the
final outcome of a bioequivalence study is strongly influenced by the solubility of the drug, but
not by its intestinal permeability or extent of metabolism. © 2013 Wiley Periodicals, Inc. and
the American Pharmacists Association J Pharm Sci 102:3136–3144, 2013
Keywords: biowaiver; BCS; BDDCS; bioequivalence; dissolution; permeability; solubility
INTRODUCTION
In 1995, Amidon and coworkers1–4 published the fun-
damentals of the biopharmaceutics classification sys-
tem (BCS). These were based on the results from a
set of absorption models, which demonstrated that
oral drug absorption is chiefly controlled by two char-
acteristics of the drug substances, that is, solubility
under physiological conditions and intestinal perme-
This article reflects the scientific opinion of the authors and
not necessarily the policies of the Brazilian Health Surveillance
Agency (ANVISA).
Correspondence to: Rodrigo Cristofoletti (Telephone: +55-
61-81114955; Fax: +55-61-81598587; E-mail: rodrigocristofol@
gmail.com).
Journal of Pharmaceutical Sciences, Vol. 102, 3136–3144 (2013)
© 2013 Wiley Periodicals, Inc. and the American Pharmacists Association
ability, and by the dissolution rate of the drug from
the dosage form.1–4 According to the BCS, a drug could
be categorized under one of the four classes of BCS
depending on its solubility and intestinal permeabil-
ity, at which point it would be possible to define the
rate-limiting step in drug absorption: gastric empty-
ing time or intestinal permeability (for a rapid dis-
solving drug product containing a BCS class 1 or BCS
class 3 drug, respectively), in vivo dissolution and/or
solubility (BCS class 2), or a mix of all variables (BCS
class 4).4In the same year, the US Food and Drug Ad-
ministration (FDA) started using BCS in its guidance
related to scale-up and postapproval changes to de-
fine the tests needed to support each level of change.5
The application of BCS principles in setting regula-
tory boundaries for waiving in vivo bioequivalence
3136 JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013
A COMPARATIVE ANALYSIS OF BCS AND BDDCS 3137
studies in the approval of new generic drug products
was first implemented 5 years later in 2000.6In gen-
eral, the FDA has accepted biowaiver requests only
for immediate-release (IR) solid oral dosage form con-
taining a highly soluble and highly permeable drug.6
This policy has been challenged as too conservative
by some authors, who suggest extending biowaiver-
based decisions to drugs belonging to other BCS
categories.7–9 Currently, there is no harmonization
on this point among the various regulatory agencies
because some authorities accept biowaiver requests
for more than one BCS class and/or apply different
classification boundaries with regard to the defini-
tions of solubility and permeability.6,10–13 These dis-
crepancies have been summarized and discussed by
Potthast14 and Zheng et al.15
The European Medicines Agency (EMA) extended
the BCS-based biowaiver to highly soluble but poorly
permeable drugs (i.e., class 3), provided they are
formulated as very rapid dissolving dosage forms
whose compositions are qualitatively the same and
quantitatively very similar to the respective refer-
ence drug products. These restrictions were applied
to circumvent unpredictable effects on the membrane
transporters.12 This guideline is consistent with other
reports that had already suggested the extension of
biowaiver for BCS class 3 drugs. However, the concept
that a more stringent in vitro dissolution requirement
is needed to ensure that the oral drug absorption can
only be limited by its intestinal permeability lacks
consensus.7–9,16–21
In turn, the WHO recommends an even more flex-
ible approach because it not only embraces the con-
cepts of biowaiver based on BCS proposed by FDA
and EMA but also suggests its extension to certain
BCS class 2 drugs. According to WHO, weak acidic
drugs with high permeability and high solubility un-
der conditions of pH 6.8 could also be candidates for
biowaiver because such drugs would behave similarly
to BCS class 1 drugs in the small intestine, which is
the primary site of absorption.10 However, this regula-
tory approach has not found consensus among the sci-
entific community; despite being supported by some
authors,22–24 it has been questioned by others.25,26
In 2005, Wu and Benet27 reviewed the concepts of
BCS to resolve a possible ambiguity in the definition
of permeability. They recognized that highly perme-
able compounds are usually eliminated primarily by
metabolism, an observation that subsequently formed
the basis of the biopharmaceutics drug disposition
classification system (BDDCS), which classifies drugs
according to their solubility and extent of metabolism.
This concern about the ambiguity of the permeability
definition was further addressed in other reports, but
it does not seem to have been resolved as yet.28–30
Nonetheless, supporters of both the BCS and BDDCS
agree that the extent of drug metabolism, as charac-
terized by the fraction of metabolites formed by oxida-
tive (phase 1) or conjugative (phase 2) enzymes, would
add value to the present BCS requirements because
it would better reflect the fraction of drug absorbed.31
The EMA guidance was the first to mention metabo-
lites specifically as contributing to the overall fraction
of drug absorbed.12 As a caution, some authors have
noted that the polymorphism of genes related to drug
metabolism could generate divergent classifications
according to BDDCS because of variations in allelic
distribution among different populations.32
Given the lack of harmonization in the applica-
tion of BCS/BDDCS to allowing biowaiver-based drug
product approvals, a cross-sectional survey to eval-
uate the relative risk of obtaining nonbioequivalent
(non-BE) or bioinequivalent (BIE) results for each
class of BCS and BDDCS was conducted. The survey
also evaluated how well a partial set of in vitro dis-
solution profiles could predict the bioequivalence out-
come for both classification systems. The aim was to
use retrospective data to determine the feasibility of
biowaiver extensions to classes 2–4 drug substances.
EXPERIMENTAL
A cross-sectional survey was performed on a random
sample of bioequivalence studies collected from an in-
ternal database of the Brazilian Health Surveillance
Agency (ANVISA). This database, referred to as the
Brazilian System of Bioequivalence and Pharmaceu-
tical Equivalence (SINEB), is a computerized record
of all bioequivalence studies conducted in Brazil since
2008, including studies showing bioequivalent (BE),
non-BE, and BIE results (with BIE being defined
as when the point estimate is outside the range of
0.80–1.25 in a study with statistical power greater
than 80%). The sample size necessary to achieve a
priori statistical power of 80% at the 0.05 level of sig-
nificance (two sided) was calculated using OpenEpi R
version 2.3.133 by considering the prevalence of non-
BE results that has been reported for each class of
the BCS.34,35 Because of the very low difference in
the prevalence of non-BE results for drugs belonging
to BCS classes 1 and 3, the sample size required to cor-
rectly reject a false null hypothesis (H0: relative risk =
1; total sample size of 13,300 bioequivalence studies)
was much higher than the total content of the SINEB.
Thus, the sample size was calculated considering only
comparisons between classes 1, 3, and 4 versus class
2 of the BCS. This calculation indicated the need to
consider at least 96 bioequivalence studies for each
of the BCS classes. Taking into account the distribu-
tion of drugs belonging to each class of BCS in a set
of registered generic drug products,36 we randomly
sampled 500 bioequivalence studies from SINEB, en-
abling us to statistically evaluate how the charac-
teristics related to the drug (solubility, intestinal
DOI 10.1002/jps JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013
3138 CRISTOFOLETTI ET AL.
permeability, and extension of drug metabolism) and
dosage form (in vitro dissolution) can influence the
outcome of a bioequivalence study. All studies sam-
pled were approved by the ethics committees and
conducted by the contract research organizations cer-
tified for good laboratory practices, good clinical prac-
tices, and in accordance to the Helsinki declaration
and the Brazilian law. In vitro dissolution data, per-
formed under pharmacopeial or validated conditions,
were also collected, where available.
Drug Classification
Drugs were classified according to the BDDCS by re-
ferring to a previous list.37 This list also provided
the classification of drug solubility over pH range
of 1.0–7.5 and the calculated log P(clog P) value,
which was chosen as a parameter of lipophilicity to
provisionally classify the sampled drugs into BCS.
Metoprolol was chosen as the reference compound for
intestinal permeability because its absorbed fraction
was around 90%.38 On this basis, drugs showing clog
Pvalues higher than or equal to the corresponding
value for metoprolol were assumed to be highly per-
meable.
Statistical Analysis
The proportions of non-BE results were compared
among all BCS or BDDCS classes using a chi-square
test (or Fisher’s exact as appropriate). Multiple 2 ×
2 contingency tables were developed to compare all
combinations of the independent classes of BCS or
BDDCS. The relative risk of obtaining a non-BE or
a BIE result and its 95% confidence interval (95%
CI) were also calculated. Data were analyzed using
SPSS R
for Windows, version 17 (SPSS Inc., Chicago,
Illinois). A pvalue of less than 0.05 was considered
significant.
The predictability of the in vitro dissolution test
with respect to the bioequivalence outcome was
evaluated by the following diagnostic parameters:
sensitivity, specificity, likelihood ratio positive (LR+),
likelihood ratio negative (LR−), and posttest prob-
ability. Sensitivity is the conditional probability of
detecting a similar in vitro dissolution profile given
that a generic drug product is indeed BE. In turn,
specificity is the conditional probability of detecting
a nonsimilar in vitro dissolution profile given that
a generic drug product is non-BE. The complemen-
tary probabilities of sensitivity and specificity are the
false-negative and false-positive probabilities, respec-
tively. The LR+is the ratio between sensitivity and
the false-positive probability (1 −specificity). In other
words, LR+for dissolution tests is a statistic for sum-
marizing how many times more likely BE generic
drug products are to have similar in vitro dissolution
profiles than non-BE drug products. On the contrary,
LR−is the ratio between the false-negative proba-
bility (1 −sensitivity) and specificity, showing how
many times less likely BE generic drug products are
to have nonsimilar in vitro dissolution profiles than
non-BE drugs products. A LR+higher than 1 indi-
cates that similar in vitro dissolution profiles are as-
sociated with BE results, whereas a LR−lower than 1
indicates that nonsimilar in vitro dissolution profiles
are associated with non-BE results. Thus, a LR whose
95% CI contains 1 lacks diagnostic value. Although
these four indicators summarize diagnostic accuracy,
they can only address how well a BE (or a non-BE)
result “predicts” an in vitro dissolution result because
they represent conditional probabilities whose a pri-
ori condition is the result of the in vivo study (i.e.,
given a BE result what is the probability of finding a
similar in vitro dissolution?). However, in the regula-
tory field, it is of greater interest to know how well the
in vitro test can predict the bioequivalence outcome.
This was assessed by calculating the posttest prob-
ability, which combines the prevalence (also known
as the pre-test probability) of BE and non-BE re-
sults with LR+and LR−, respectively. According to
Bayes’ theorem, such a combination describes, for in-
stance, how a similar or a nonsimilar in vitro disso-
lution profile changes the prior knowledge about the
probability of obtaining a BE or a non-BE result. To
apply the posttest probability, some additional calcu-
lations (described in the following references) were
required to convert odds to probabilities.39–43 Alge-
braically, these diagnostic parameters can be defined
as follows (please see Table 1):
•Sensitivity =a/(a+c)
•Specificity =d/(b+d)
•LR+=sensitivity/(1 −specificity)
•LR−=(1 −sensitivity)/specificity
•Posttest probabilityBE =posttest oddsBE/(1 +
posttest oddsBE), where
•Posttest oddsBE =pretest oddsBE ×LR+
•Pretest oddsBE =prevalenceBE/(1 −
prevalenceBE)
Table 1. General 2 ×2 Contingency Table
In vivo Result
In vitro Result Bioequivalent (BE) Nonbioequivalent (non-BE)
Similar dissolution profile a (true positive) b (false positive)
Nonsimilar dissolution profile c (false negative) d (true negative)
JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013 DOI 10.1002/jps
A COMPARATIVE ANALYSIS OF BCS AND BDDCS 3139
•PrevalenceBE =pretest probabilityBE =(a+c)/(a
+b+c+d)
•Posttest probabilitynon-BE is defined analogously,
where posttest oddsnon-BE =pretest oddsnon-BE ×
(1/LR−).
The 95% CIs for sensitivity, specificity, LR+,and
LR−were calculated according to previously reported
methods.44,45
RESULTS
All sampled bioequivalence studies were conducted
with drug products formulated as IR dosage forms
that were not intended for absorption in the oral
cavity. Moreover, only non-BE studies whose statis-
tical power a posteriori was higher than 80% were in-
cluded in this survey. In this context, it was assumed
that a non-BE study with a point estimate outside the
bioequivalence boundaries was BIE; in other words,
the non-BE result was because of the differences be-
tween the test and the reference formulations.
A total of 107 out of 114 drugs were classified ac-
cording to BCS and BDDCS, representing 95% (475)
of the studies previously sampled. Figure 1 summa-
rizes the number of drug substances grouped at each
class of BCS and BDDCS.
Drugs with at least 70% metabolism were clas-
sified as being extensively metabolized; however, if
Figure 1. Distribution of drugs sampled between BCS
and BDDCS classes.
its fraction metabolized was lower than this cutoff
value, the drug was classified as poorly metabolized.37
The lipophilicity of 66 extensively metabolized drugs
and 23 poorly metabolized drugs were, respectively,
higher and lower than the metoprolol value. On the
contrary, nine drugs with fraction metabolized higher
than 70% of the administered dose had a clog Pvalue
lower than metoprolol, whereas nine drugs showing
high lipophilicity were classified as being poorly me-
tabolized. This lack of a one to one correspondence
has already been addressed by several authors and
has mainly been attributed to the differences in ac-
cess to the metabolizing enzymes within the hep-
atocytes or the predominance of a drug absorption
mechanism based on paracellular or carrier-mediated
transport.27,32, 46,47
In all classes of both classification systems, there
were non-BE results for Cmax (peak plasma con-
centration) and AUC0–t(area under the plasma
concentration-time curve). The general prevalence of
non-BE results ranged from 10% (class 3) to 40%
(class 2). Moreover, BIE results were also observed
in all BCS and BDDCS categories (see Table 2).
Table 3 shows a comparison between the relative
risks of obtaining a non-BE or a BIE result for each
class of BCS or BDDCS taken two at a time. Summa-
rizing, the risk of non-BE for drug products containing
class 2 drug substances according to either the BCS
or BDDCS was between 2.5-fold and fourfold higher
than those containing highly soluble drugs. In all of
these comparisons, the statistical power was higher
than 99% (calculated on OpenEpi R
version 2.3.1).33
On the contrary, we were not able to ensure an ad-
equate statistical power for comparing the classes 1
and 3, as expected, or for any comparison involving
class 4 drugs (mainly because of the very low preva-
lence of BCS class 4 drugs in our sample—only 2.8%).
As none of the comparisons involving BCS or BDDCS
class 4 drugs showed statistical validity, studies of
drug products containing these drugs were excluded
from subsequent analysis.
Table 2. Distribution of Non-BE Results Between the Four Classes of BCS and BDDCS
System Classes
Non-BE Results
Only for Cmax
Non-BE Results
Only for AUC0–t
Non-BE Results for
Cmax and AUC0–t Non-BE Results
Number of
Studies Sampled
BCS 1 18 (7) 0 4 (1) 22 (8) 140
2 52 (21) 5 (0) 26 (11) 83 (32) 206
3 7 (4) 1 (0) 4 (1) 12 (5) 115
4 1 (0) 1 (0) 1(1) 3 (1) 14
BDDCS 1 18 (8) 1 (0) 4 (2) 23 (10) 150
2 48 (19) 5 (0) 25 (10) 78 (29) 191
3 7 (4) 0 4 (1) 11 (5) 105
4 5 (2) 1 (0) 2 (1) 8 (3) 29
The numbers between parentheses represent the BIE results (point estimate outside 80–125 in a study with statistical power is greater than 80%) among
those already declared as non-BE.
DOI 10.1002/jps JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013
3140 CRISTOFOLETTI ET AL.
Table 3. Relative Risk of Obtaining a Non-BE or a BIE Result
95% Confidence Interval 95% Confidence Interval
System Classes Compared Risk of Non-BEaLower Upper Risk of BIEaLower Upper
BCS 1 ×20.390∗0.257 0.592 0.368∗0.175 0.774
1×31.506 0.779 2.910 1.314 0.442 3.908
2×33.861∗2.204 6.764 3.573∗1.432 8.916
BDDCS 1 ×20.375∗0.248 0.567 0.395∗0.193 0.809
1×31.464 0.746 2.871 1.575 0.498 4.980
2×33.898∗2.173 6.994 3.986∗1.440 11.030
aThese columns show the relative risks of the first class compared with the second class, in each comparison 2 ×2 (i.e., for the first line: BCS 1 compared
with BCS 2).
∗p<0.01 showing a significant difference in the proportion of non-BE or BIE results between the classes compared.
The predictability of in vitro dissolution profile per-
formed under a single experimental condition, phar-
macopeial or validated, over the bioequivalence out-
come was also evaluated for all classes of BCS and BD-
DCS. A total of 29 out of 475 drug products sampled
did not present a comparison of in vitro dissolution
profile; thus, the diagnostic parameters sensitivity,
specificity, LR+,LR−, and posttest probability were
calculated with data provided by 432 and 417 drug
products containing drug substances from classes 1–3
of BCS and BDDCS, respectively (Tables 4 and 5).
A similar in vitro dissolution profile was approx-
imately 1.7 times more likely for a BE than for
a non-BE generic drug product containing a BCS or
a BDDCS class 1 drug. The probability of detecting
a BE drug product was increased to 90% when the
in vitro dissolution profile of the test drug product had
been similar to the reference drug product (posttest
probability). Also, the predictability of a non-BE out-
come was significantly increased after performing an
in vitro dissolution test for drug products containing
highly soluble drugs. The posttest probability of de-
tecting a non-BE result for drug products containing
BCS classes 1 or 3 drugs was 4.5- or 2.5-fold higher
than the respective pretest probability, after obtain-
ing a nonsimilar in vitro dissolution profile.
Table 4. Similarities Between in vitro and in vivo Results Inside Each Class of BCS and BDDCS
System Classes BE and DS Non-BE and DS BE and DNS Non-BE and DNS Total
BCS 1 112 12 4 10 138
2 98 60 17 10 185
2a13 7 1 1 22
3 91 7 8 3 109
3b74 3 25 7 109
BDDCS 1 123 13 4 10 150
2 90 57 15 9 171
379 6 8 3 96
aResults for a set of five highly permeable acidic drugs.
bThe in vitro test was considered similar only when both test and reference drug products showed a very rapid dissolution (Q >85% in 15 min).
BE, bioequivalent result; non-BE, nonbioequivalent result; DS, similar in vitro dissolution profile; DNS, nonsimilar in vitro dissolution profile.
Table 5. Predictability of BCS and BDDCS over the Bioequivalence Outcome
Systems Classes Sensitivity Specificity LR+
Pretest
Probability
of BE
Posttest
Probability
of BE LR−
Pretest
Probability
of Non-BE
Posttest
Probability
of Non-BE
BCS 1 0.96 (0.91–0.99) 0.45 (0.27–0.65) 1.77 (1.21–2.60) 0.84 0.90 0.07 (0.03–0.22) 0.16 0.71
2 0.85 (0.78–0.90) 0.14 (0.08–0.24) 1.00 (0.88–1.12) 0.62 0.62 1.03 (0.50–2.13) 0.38 0.38
2a0.93 (0.70–0.99) 0.12 (0.02–0.47) 1.07 (0.79–1.43) 0.64 0.64 0.53 (0.04–7.44) 0.36 0.36
3 0.92 (0.84–0.96) 0.30 (0.11–0.60) 1.31 (0.87–1.97) 0.91 0.91 0.27 (0.09–0.87) 0.09 0.27
3b0.75 (0.65–0.82) 0.70 (0.40–0.89) 2.49 (0.96–6.12) 0.91 0.91 0.36 (0.21–0.61) 0.09 0.22
BDDCS 1 0.97 (0.92–0.99) 0.43 (0.26–0.63) 1.71 (1.20–2.46) 0.85 0.90 0.07 (0.02–0.21) 0.15 0.71
2 0.86 (0.78–0.91) 0.14 (0.07–0.24) 0.99 (0.88–1.12) 0.61 0.61 1.05 (0.49–2.26) 0.39 0.39
3 0.91 (0.83–0.95) 0.33 (0.12–0.64) 1.36 (0.85–2.17) 0.91 0.91 0.28 (0.09–0.86) 0.09 0.27
aResults for a set of five highly permeable acidic drugs.
bThe in vitro test was considered similar only when both test and reference drug products showed a very rapid dissolution (Q>85% in 15 min).
JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013 DOI 10.1002/jps
A COMPARATIVE ANALYSIS OF BCS AND BDDCS 3141
On the contrary, performing an in vitro dissolution
test for a drug product containing a class 2 drug did
not add any value to diagnosis of a BE or a non-BE
result because both LR+and LR−lack statistical sig-
nificance (both 95% CI contain 1).
DISCUSSION
Distribution of Non-BE Results Among BCS and BDDCS
Classes
The prevalence of non-BE results among the BCS
classes (Fig. 1 and Table 2) was similar to those previ-
ously reported.34,35 The highest prevalence of non-BE
results occurred for the poorly soluble, highly perme-
able drugs. This result was expected because accord-
ing to the BCS theory, the absorption of a class 2 drug
is controlled by in vivo drug dissolution or even by its
solubility (as in the case of drugs with very high dose
number like that of griseofulvin), which means that
pharmaceutics properties rather than emptying gas-
tric time or intestinal permeability control the drug
absorption.4,48
Also, the proportion of non-BE results were sim-
ilar in each BCS/BDDCS class, even though these
two systems employ different cutoff values to clas-
sify the extent of drug absorption: more than 90% for
BCS and more than 70% for BDDCS. Indeed, the frac-
tion absorbed of extensively metabolized drugs might
be even lower than 70% of the administered dose in
some cases because the metabolism criterion used for
BDDCS assignment did not limit the metabolic pro-
cesses to oxidative (phase 1) and conjugative (phase 2)
enzymes, which occur only after drug absorption,31,37
and many drugs can be metabolized presystemically
by bacterial enzymes.49,50
Relative Risk of Obtaining a Non-BE Result for Each
Class of BCS and BDDCS
The relative risk of obtaining a non-BE or a BIE result
was not different from unity when comparing drug
products containing drugs belonging to the classes 1
and 3 of BCS or BDDCS. However, it should be men-
tioned that the type 2 error was too high for these
analyses (around 70%, with H0:μclass 1 =μclass 3) be-
cause we were not able to collect an adequate sample
size, as already explained. On the contrary, the rel-
ative risk of getting a non-BE or a BIE result was
almost fourfold higher for poorly soluble and highly
absorbed drugs when compared with highly soluble
drugs (see Table 3). Because the estimated risks were
similar between both comparisons, class 1 or 3 ver-
sus class 2 of both systems, it seems that solubility
outweighs any effect of the extent of absorption with
regard to the bioequivalence outcome. These results
can aid in assessing the risk of extending biowaiver
beyond BCS class 1 drugs, as suggested by Polli et al.8
However, a potential weakness in the above anal-
ysis is that the BCS classification relied on clog P
as a measure of permeability. Clog Pdata are not
recognized in any regulatory guidance of biowaiver
as being sufficient for or even supportive of a per-
meability classification. So the provisional BCS clas-
sification based on solubility and clog Pcould lead
to false negative results (in the case of drugs that
are substrates for uptake with regard to permeability
assessment). On the contrary, there is a reasonably
good correlation between lipophilicity and intestinal
permeability, at least for drugs absorbed mainly by
passive mechanisms.46,47
Predictability of
In Vitro
Dissolution Test of
Bioequivalence Outcome—Diagnostic Parameters for
Highly Soluble Drugs
Considering that a comparative in vitro dissolution
profile and a bioequivalence study can have dichoto-
mous outcomes, it was possible to compare both in 2 ×
2 contingency tables. Indicators of test performance
derived from such tables were used to evaluate the
predictability of in vitro test over in vivo outcomes
(Tables 1 and 5).
The sensitivity of the single in vitro dissolution
test was significantly high for all BCS or BDDCS
classes, indicating that 75%–96% of the BE drug prod-
ucts showed similar in vitro dissolution profiles to
their respective reference drug products, whereas the
specificity was not statistically significant for drugs
belonging to classes 1 and 3 of BCS and BDDCS; in
other words, 50% of the non-BE drug products showed
nonsimilar in vitro dissolution profiles, whereas the
other half showed similar in vitro results. However,
the biowaiver based on the BCS requires not one but
a set of three in vitro dissolution profiles performed
under conditions relevant to pH in the upper gastroin-
testinal tract. This set can be interpreted as a serial
diagnostic test because the result of the first deter-
mines whether the second test is performed.51 For
example, if the in vitro dissolution profiles at pH 1.2
are similar, the second in vitro dissolution test at pH
4.5 is performed, and if it is also similar, the third test
at pH 6.8 is conducted. Only if all three in vitro dis-
solution profiles are similar, the drug product will be
approved according to the biowaiver procedure, oth-
erwise the diagnostic is negative. This combination
of multiple tests leads to a higher overall specificity
than is possible with a single in vitro test.52 Consider-
ing that the diagnostic indicators in this survey were
calculated using only a single in vitro result from a
dissolution test performed under pharmacopeial or
manufacturer-validated conditions to assess quality
control, it seems safe to expect a higher accuracy of
the diagnostic test when performing the complete set
of in vitro dissolution profiles required to support a
biowaiver request.
DOI 10.1002/jps JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013
3142 CRISTOFOLETTI ET AL.
The absorption of a class 3 drug is more complex
than that of a class 1 drug because its absorption is
segmentally dependent along the small intestine,53–57
and it is also mediated by uptake transporters.27,58
Therefore, the absorption of a class 3 drug could
be more affected by certain excipients, which inter-
act with gastrointestinal motility, reducing the in-
testinal transit time,59 and/or interact with uptake
transporters.58 As Brazilian law does not require a
quantitative or qualitative similarity between generic
and reference formulations,60 the composition of such
drug products generally differ. As the formulations of
the 500 drug products sampled were not compared
with the respective reference formulations, we can-
not exclude the possibility of different excipients pre-
sented in a generic formulation having affected a
membrane carrier or the gastrointestinal motility, re-
sulting in a non-BE that could not have been predicted
by in vitro dissolution testing. This might explain the
lower posttest probability presented by drug products
containing class 3 drug substances when compared
with class 1 drugs (27% vs. 71%). Further studies
would be necessary to confirm this point. Neverthe-
less, because of the generally low risk of obtaining
a non-BE result for class 3 drugs, it seems safe to
extend biowaiver decisions for generic drug products
containing highly soluble, poorly absorbed drugs as
long as they are formulated with the same excipients
present in the reference formulation, along the lines
of the EMA guideline.12
Rapid Dissolution Versus Very Rapid Dissolution for
Biowaiving BCS Class 3 Drugs
The diagnostic indicators for drug products contain-
ing BCS class 3 drugs were also calculated using two
dissolution criteria, rapid dissolution (Q>85% in
30 min, with similarity being demonstrated by f2)
versus very rapid dissolution (Q>85% in 15 min,
without f2 calculation). As the 95% CI for the di-
agnostic parameters calculated for both dissolution
criteria almost completely overlapped (see Table 5),
it seems that the predictability of the in vitro dis-
solution profile of the BE outcome is not improved
by employing a more restrictive dissolution criterion.
Further, this procedure increased the probability of
false negative results (1 −sensitivity, from 8% to
25%) and decreased the posttest probability of non-
BE results (from 27% to 22%). Previous reports have
already demonstrated that a very rapid dissolution
criterion is too conservative for biowaiving oral for-
mulations containing BCS class 3 drugs.16,17 ,21,61,62
Predictability of
In Vitro
Dissolution Test of BE
Outcome—Diagnostic Parameters for Class 2 Drugs
The probability of false positive results obtained in
in vitro test for class 2 drugs was almost 90%, show-
ing a statistically significant 95% CI for the speci-
ficity, suggesting that the pharmacopeial dissolution
methods are not biorelevant. Furthermore, LR+and
LR−lack diagnostic value because its 95% CI con-
tains unity. So, the posttest probability is equal to the
pretest probability; in other words, the predictabil-
ity of in vitro dissolution test, performed according to
the pharmacopeial methods, with respect to the bioe-
quivalence outcome was not different from the inher-
ent prevalence of BE or non-BE results (see Table 5).
However, as we did not have access to the set of in
vitro dissolution profiles, which would be required by
guidelines on the BCS-based biowaiver for these drug
products, no conclusion can be reached about their
predictability.
Diagnostic Parameters for Highly Permeable Weak
Acidic Drugs Showing High Solubility at pH 6.8
As the WHO recommends an extension of biowaiver
based on BCS for drug products containing class 2
drugs that show high solubility and rapid dissolution
at pH 6.8, we also calculated the diagnostic indica-
tors utilizing 22 results of in vitro dissolution profiles
performed at neutral conditions (phosphate buffer
under pH 6.8–7.5) for a set of eight non-BE (all of
them because of Cmax) and 14 BE drug products con-
taining five weak acidic drugs with pKaoflessthan
5.5 and which have dose numbers lower than one at
pH values ranging from 6.8 to 7.4.22 However, these
diagnostic parameters proved not to be different from
those calculated for all drugs belonging to BCS class
2, in accordance with the previous reports for drug
products containing ibuprofen that showed that dis-
solution tests under neutral conditions were unable
to detect differences in absorption rate on one hand25
or overdiscriminated in cases of in vivo equivalence
on the other hand.26 In fact, it seems that the disso-
lution of weak acidic drugs under gastric conditions
might be able to detect in vivo differences related to
Cmax,18,23 ,25 but the low amount of drug dissolved pre-
cludes a meaningful calculation of the f2 statistics.
Recently, some authors suggested scaling the data
to 100% release from the reference formulation be-
fore applying the f2 statistics (as the f2 represents an
absolute rather than a relative difference). However,
the discussion in this arena has just started, and the
best way to handle the dissolution data for products
containing highly permeable weak acidic drugs still
needs to be agreed upon.24
CONCLUSIONS
With this cross-sectional survey, we demonstrated
that solubility outweighs any effect of the extent of
drug absorption, measured either as intestinal per-
meability or extension of drug metabolism, with re-
gard to the bioequivalence outcome. Also, as the esti-
mated risks were similar between the comparisons of
JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 102, NO. 9, SEPTEMBER 2013 DOI 10.1002/jps
A COMPARATIVE ANALYSIS OF BCS AND BDDCS 3143
classes 1 and 3 versus class 2 of both systems, BDDCS
could be considered as adequate as BCS in the classifi-
cation of drugs with a view to applying the biowaiver.
As in some cases, drug metabolism data are more
readily available than permeability data; it seems
useful to accept both ways of classifying drugs for reg-
ulatory purposes. Moreover, because of the generally
low risk of obtaining non-BE or BIE results for class
3 drugs, it seems safe to extend biowaiver decisions
for generic drug products containing highly soluble,
poorly absorbed drugs as long as they are formulated
with the same excipients present in the reference for-
mulation and in similar amounts. On the contrary,
because of the high risk of obtaining non-BE or BIE
results and the lack of significance of LR+and LR−
seen with the quality control in vitro dissolution test,
extending biowaiver for class 2 drugs does not seem
to be as straightforward.
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