In vitro-in-vivo-correlation-ivivc-a-strategic-tool-in-drug-development-jbb.s3-001

Open Access
Sakore and Chakraborty, J Bioequiv Availab 2011, S3
DOI: 10.4172/jbb.S3-001
Open Access
J Bioequiv Availab ISSN:0975-0851 JBB, an open access journalBA/BE: LC-MS
Keywords: IVIVC definitions; Predictions; BCS classification;
IVIVC Levels; Applications, Guidance
Abbreviations: IVIVC: In Vitro In Vivo correlation; FDA: Food
and Drug Administration; AUC: Area Under Curve; MDT vitro:
Mean in vitro Dissolution Time; MRT: Mean Residence Time; BCS:
Biopharmaceutical Classification System
Introduction
In vitro in vivo correlations (IVIVC) play a key role in the drug
development and optimization of formulation which is certainly a
time consuming and expensive process. Formulation optimization
requires alteration in formulation, composition, equipments, batch
sizes and manufacturing process. If such types of one or more changes
are applied to the formulation, the in vivo bioequivalence studies in
human may required to be done to prove the similarity of the new
formulation which will not only increase the burden of carrying out
a number of bioequivalence studies but eventually increase the cost
of the optimization process and ultimately marketing of the new
formulation. To overcome these problems it is desirable to develop in
vitro tests that reflect can bioavailability data. IVIVC can be used in the
development of new pharmaceuticals to reduce the number of human
studies during the formulation development. Thus, the main objective
of an IVIVC is to serve as a surrogate for in vivo bioavailability and to
support biowaivers.
IVIVC is a mathematical relationship between in vitro properties
of a dosage form with its in vivo performance. The In vitro release
data of a dosage form containing the active substance serve as
characteristic in vitro property, while the In vivo performance is
generally represented by the time course of the plasma concentration
of the active substance. These In vitro & In vivo data are then treated
scientifically to determine correlations. For oral dosage forms, the in
vitro release is usually measured and considered as dissolution rate.
The relationship between the in vitro and in vivo characteristics can
be expressed mathematically by a linear or nonlinear correlation.
However, the plasma concentration cannot be directly correlated to
the in vitro release rate; it has to be converted to the in vivo release
or absorption data, either by pharmacokinetic compartment model
analysis or by linear system analysis [1].
IVIVC definitions
United state pharmacopoeia (USP) definition of IVIVC
The establishment of a rational relationship between a biological
property, or a parameter derived from a biological property produced
by a dosage form, and a physicochemical property or characteristic of
the same dosage form [2].
Food and drug administration (FDA) definition of IVIVC
An In-vitro in-vivo correlation (IVIVC) has been defined by the
Food and Drug Administration (FDA) as “a predictive mathematical
model describing the relationship between an in-vitro property of a
dosage form and an in-vivo response”.
Generally, the In vitro property is the rate or extent of drug
dissolution or release while the In vivo response is the plasma drug
concentration or amount of drug absorbed. Practically, the purpose of
IVIVC is to use drug dissolution results from two or more products to
predictsimilarityordissimilarityofexpectedplasmadrugconcentration
(profiles). Before one considers relating in vitro results to in vivo, one
has to establish as to how one will establish similarity or dissimilarity
of in vivo response i.e. plasma drug concentration profiles. The
methodology of establishing similarity or dissimilarity of plasma drug
concentrations profile is commonly known as bioequivalence testing.
There are very well established guidances and standards available for
establishing bioequivalence between drug profiles and products [3].
*Corresponding author: Somnath Sakore, Cadila Pharmaceuticals Ltd, Research
& Development, 1389, Trasad Road, Dholka, Ahmedabad 387810, Gujarat, India,
Tel: +91 9879112032; E-mail: drb.chakraborty@cadilapharma.co.in
Received October 06, 2011; Accepted December 31, 2011; Published January
02, 2012
Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC):
A Strategic Tool in Drug Development. J Bioequiv Availab S3. doi:10.4172/jbb.
S3-001
Copyright: © 2011 Sakore S, et al. This is an open-access article distributed under
the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and
source are credited.
Abstract
In Vitro–In Vivo Correlation (IVIVC) plays a key role in pharmaceutical development of dosage forms. This
tool hastens the drug development process and leads to improve the product quality. It is an integral part of the
immediate release as well as modified release dosage forms development process. IVIVC is a tool used in quality
control for scale up and post-approval changes e.g. to improve formulations or to change production processes &
ultimately to reduce the number of human studies during development of new pharmaceuticals and also to support
the biowaivers. This article provides the information on the various guidances, evaluation, validation, BCS application
in IVIVC, levels of IVIVC, applications of IVIVC in mapping, novel drug delivery systems and prediction of IVIVC from
the dissolution profile characteristics of product.
In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug
Development
Somnath Sakore* and Bhaswat Chakraborty
Cadila Pharmaceuticals Ltd, Research & Development, 1389, Trasad Road, Dholka, Ahmedabad 387810, Gujarat, India
Review Article
Journal of Bioequivalence & Bioavailability
JournalofBioequivalence &
BioavailabilityISSN: 0975-0851

Citation: Sakore S, Chakraborty B (2011) In Vitro–In Vivo Correlation (IVIVC): A Strategic Tool in Drug Development. J Bioequiv Availab S3.
doi:10.4172/jbb.S3-001
Page 2 of 12
Purpose of IVIVC
Reduction of regulatory burden
IVIVC can be used as substitute for additional in vivo experiments,
under certain conditions.
Optimization of formulation
The optimization of formulations may require changes in the
composition, manufacturing process, equipment, and batch sizes. In
order to prove the validity of a new formulation, which is bioequivalent
with a target formulation, a considerable amount of efforts is required
to study bioequivalence (BE) /bioavailability (BA).
Justification for “therapeutic’ product quality
IVIVC is often adequate for justification of therapeutically
meaningful release specifications of the formulation.
Scale up post approval changes (Time and cost saving during
the product development)
Validated IVIVC is also serves as justification for a biowaivers in
filings of a Level 3 (or Type II in Europe) variation, either during scale-
up or post approval, as well as for line extensions (e.g., different dosage
strengths).
IVIVC as surrogate for in vivo bioequivalence and to support
biowaivers (Time and cost saving)
The main purpose of an IVIVC model to utilize in vitro dissolution
profiles as a surrogate for in vivo bioequivalence and to support
biowaivers.
Levels of Ivivc
There are four levels of IVIVC that have been described in the FDA
guidance, which include levels A, B, C, and multiple C [4]. The concept
of correlation level is based upon the ability of the correlation to reflect
the complete plasma drug level-time profile which will result from
administration of the given dosage form.
Level A correlation
An IVIVC that correlates the entire in vitro and in vivo profiles
has regulatory relevance and is called a Level A Correlation .This level
of correlation is the highest category of correlation and represents a
point-to-point relationship between in vitro dissolution rate and in
vivo input rate of the drug from the dosage form [3,5].
Level A correlation is the most preferred to achieve; since it allows
bio waiver for changes in manufacturing site, raw material suppliers,
and minor changes in formulation. The purpose of Level A correlation
is to define a direct relationship between in vivo data such that
measurement of in vitro dissolution rate alone is sufficient to determine
the biopharmaceutical rate of the dosage form.
Level B correlation
A level B IVIVC is based on the principles of statistical moment
analysis. In this level of correlation, the mean in vitro dissolution time
(MDTvitro)oftheproductiscomparedtoeithermeaninvivoresidence
time (MRT) or the mean in vivo dissolution time (MDTvivo). MRT,
MDTvitro and MDTvivo will be defined throughout the manuscript
where appropriate [6]. A level B correlation does not uniquely reflect
the actual in vivo plasma level curves, also in vitro data from such a
correlation could not be used to justify the extremes of quality control
standards hence it is least useful for regulatory purposes [5].
Level C correlation
Level C correlation relates one dissolution time point (t50%, t90%,
etc.) to one mean pharmacokinetic parameter such as AUC, tmax
or Cmax
.
This is the weakest level of correlation as partial relationship between
absorption and dissolution is established since it does not reflect the
complete shape of plasma drug concentration time curve, which is the
critical factor that defines the performance of a drug product.
Due to its obvious limitations, the usefulness of a Level C
correlation is limited in predicting in vivo drug performance. In the
early stages of formulation development Level C correlations can be
useful when pilot formulations are being selected while waiver of an in
vivo bioequivalance study (biowaiver) is generally not possible [5,6].
Multiple level C correlations
This level refers to the relationship between one or more
pharmacokinetic parameters of interest (Cmax
, AUC, or any other
suitable parameters) and amount of drug dissolved at several time point
of dissolution profile. Multiple point level C correlation may be used to
justify a biowaivers provided that the correlation has been established
over the entire dissolution profile with one or more pharmacokinetic
parameters of interest. A multiple Level C correlation should be based
on at least three dissolution time points covering the early, middle,
and late stages of the dissolution profile. The development of a level A
correlation is also likely, when multiple level C correlation is achieved
at each time point at the same parameter such that the effect on the in
vivo performance of any change in dissolution can be assessed [5,6].
Level D correlation
It is not a formal correlation but it is a semi quantitative (qualitative
analysis) and rank order correlation and is not considered useful for
regulatory purpose but can be serves as an aid in the development of a
formulation or processing procedure [5,7] (Table 1).
IVIVC Models
The relationship of observed drug concentration-time profiles
following administration of a tablet/capsule with drug dissolution and
pharmacokinetics may be described graphically as shown in Figure 1.
It is generally assumed that absorption and dissolution have a
Level In vitro In vivo
A Dissolution curve Input (absorption) curves
B
Statistical moments: mean
dissolution time (MDT)
Statistical moments: mean
residence time (MRT), mean
absorption time (MAT), etc
C
Disintegration time, time
to have 10%, 50%, 90%
dissolved, dissolution rate,
dissolution efficiency (DE)
Maximum observed concentration
(Cmax
), observed at time (Tmax
),
absorption constant (Ka), Time to have
10, 50, 90% absorbed, AUC
(total or cumulative)
A: one-to-one relationship between in vitro and in vivo data, e.g., in vitro
dissolution vs. in vivo absorption
B: correlation based on statistical moments, e.g., in vitro MDT vs. in vivo MRT
or MAT
C: point-to-point relationship between a dissolution and a pharmacokinetic
parameter, e.g., in vitro T50% vs. in vivo T max, Multiple C: relationship between
one or several PK parameters and amount dissolved at several time points.
Table 1: Various parameters used in IVIVC depending on the level.

doi:10.4172/jbb.S3-001
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linear relationship hence dissolution and absorption characteristics of
a drug are commonly shown interchangeably. Thus from Figure 2, it
is to be noted that one should be able to establish drug profiles with
dissolution profiles combined with the pharmacokinetic characteristics
of the drug as describe in the example above. This process of obtaining
a drug profile from dissolution results is known as convolution. The
opposite of this, i.e., obtaining or extracting a dissolution profile from
a blood profile, is known as deconvolution Figure 2.
Convolution model
In the development of convolution model the drug concentration-
time profiles obtained from dissolution results may be evaluated using
criteria for in vivo bioavailability/ bioequivalence assessment, based on
Cmax
and AUC parameters.
In mathematical terminology, dissolution results become an input
function and plasma concentrations (e.g. from IV) become a weighting
factor or function resulting in an output function representing plasma
concentrations for the solid oral product.
Implementation of convolution-based method involves the
production of a user-written subroutine for the NONMEM software
package, has shown that a convolution-based method based on that
of O’Hara et al. [9] produces superior results. Using the NONMEM
package, a nonlinear mixed effects model can be fitted to the data with
a time-scale model linking the in vitro and in vivo components [10].
It has been demonstrates that the convolution based and differential
equation based models can be mathematically equivalent [11]. Software
has been developed which implements a differential equation based
approach. This method utilises existing NONMEM libraries and is an
accurate method of modeling which is far more straightforward for
users to implement. This research shows that, when the system being
modeled is linear, the use of differential equations will produce results
that are practically identical to those obtained from the convolution
method.
But is a task that can be time consuming and complex [12]. As a
result, this methodology, despite its advantages over the deconvolution-
based approach, is not in widespread use.
Mathematically we can write the convolution as:
0
( ) ( ) ( ) ( ) ( )
t
C t C t F t C F t dδ δ τ τ τ= = −∫ (1)
Where, C(t) = Plasma drug concentrations after oral dose
Cδ(t) = Plasma concentrations after an IV dose or a dose of oral
solution
Upon taking the derivative of C(t) with respect to time:
0
( ) ( ) ( ) (0) ( )
t
C t C t F t C F dδ δ τ τ= + ∫ (2)
When Cδ(0) = 0
( )* ( )C t F tδ (3)
Advantages of this approach relative to deconvolution-based
IVIVC approaches include the following: The relationship between
measured quantities (in vitro release and plasma drug concentrations)
is modeled directly in a single stage rather than via an indirect two
stage approach. The model directly predicts the plasma concentration
time course. As a result the modeling focuses on the ability to predict
measured quantities (not indirectly calculated quantities such as the
cumulative amount absorbed). The results are more readily interpreted
in terms of the effect of in vitro release on conventional bioequivalence
metrics [5].
Deconvolution model
Deconvolution is a numerical method used to estimate the time
course of drug input using a mathematical model based on the
convolution integral.
The deconvolution technique requires the comparison of in vivo
dissolution profile which can be obtained from the blood profiles
with in vitro dissolution profiles. The observed fraction of the drug
absorbed is estimated based on the Wagner-Nelson method. IV, IR or
oral solution are attempted as the reference. Then, the pharmacokinetic
parameters are estimated using a nonlinear regression tool or obtained
from literatures reported previously. Based on the IVIVC model,
the predicted fraction of the drug absorbed is calculated from the
observed fraction of the drug dissolved. It is the most commonly
cited and used method in the literature [10]. However this approach
is conceptually difficult to use. For example: (1) Extracting in
vivo dissolution data from a blood profile often requires elaborate
mathematical and computing expertise. Fitting mathematical models
are usually subjective in nature, and thus do not provide an unbiased
approach in evaluating in vivo dissolution results/profiles. Even when
in vivo dissolution curves are obtained there is no parameter available
with associated statistical confidence and physiological relevance,
Figure 1: A typical drug concentration (in blood) – time profile reflecting the fate
of a drug in the human body following an oral dose (tablet/capsule).
Cmax
Concentration
Tmax Time
Figure 2: Schematic representation of deconvolution and convolution processes.
Convolution is the process of combined effect of dissolution and elimination of
drug in the body to reflect blood drug concentration-time profile (right to left). On
the other hand, extracting dissolution profiles from blood drug concentration-time
profile is known as the deconvolution process (left to right) [8].
Cmax
Conc.
Tmax Time
Blood drug concentration
Deconvolution
Convolution
CONC.%DISSOLVED
Time
Elimination of drug
Time
Dissoution profile

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which would be used to establish the similarity or dissimilarity of
the curves [13]. A more serious limitation of this approach is that it
often requires multiple products having potentially different in vivo
release characteristics (slow, medium, fast). These products are then
used to define experimental conditions (medium, apparatus etc.) for
an appropriate dissolution test to reflect their in vivo behavior. This
approach is more suited for method/apparatus development as release
characteristics of test products are to be known (slow, medium, fast)
rather product evaluation [14].
Differential equation based approach
Another approach, has been proposed is based on systems of
differential equations [15]. The use of a differential equation based
model could also allow for the possibility of accurately modelling non-
linear systems and further investigation is being carried out into the
case where the drug is eliminated by a nonlinear, saturable process. The
convolution and deconvolution methods assume that the system being
modelled is linear but, in practice, this is not always the case. Work
to date has shown that the convolution-based method is superior, but
when presented with nonlinear data even this approach will fail. It is
expected that, in the nonlinear case, the use of a differential equation
based method would lead to more accurate predictions of plasma
concentration.
The incorporation of time-scaling in the PDx-IVIVC equation
allows this parameter to be estimated directly from the in vivoand vitro
release data. As a result, the predictability of an IVIVC model can be
evaluated over the entire in vivo time course.Internal predictability of
the IVIVC model was assessed using convolution.PDx-IVIVC Model
Equation:
1 2 1 2
0, t 0.
( )
( ), t 0.vivo
vitro
x t
a a x b b t
≥
= 
+ − + ≥
(4)
For orally administered drugs, IVIVC is expected for highly
permeable drugs, or drugs under dissolution rate-limiting conditions,
which is supported by the Biopharmaceutical Classification System
(BCS) [6,16]. For extended-release formulations following oral
administration, modified BCS containing the three classes (high
aqueous solubility, low aqueous solubility, and variable solubility) is
proposed [17].
IVIVC Development
Any well designed and scientifically sound approach would be
acceptable for establishment of an IVIVC. For the development and
validation of a IVIVC model, two or three different formulations with
different release rates, such as slow, medium, fast should be studied In
vitro and In vivo [6].
A number of products with different release rates are usually
manufactured by varying the primary rate controlling variable (e.g.,
the amount of excipient, or a property of the drug substance such as
particle size) but within the same qualitative formulation. To develop
a discriminative in vitro dissolution method, several method variables
together with formulation variables are studied, e.g., different pH
values, dissolution apparatuses and agitation speeds. Essentially at this
stage a level A correlation is assumed and the formulation strategy
is initiated with the objective of achieving the target in vitro profile.
Development of a level A IVIVC model includes several steps.
In context of understanding the applications of IVIVR throughout
the product development cycle, it is useful to become familiar with the
following terms as they relate to a typical product development cycle
for oral extended-release product [5].
An assumed IVIVC is the one that provides the initial guidance
and direction for the early formulation development activity. Thus,
during step 1 and with a particular desired product, appropriate
in vitro targets are established to meet the desired in vivo profile
specification. This assumed model can be the subject of revision as
prototype formulations are developed and characterized in vivo, with
the results often leading to a further cycle of prototype formulation and
In vivo characterization.
Out of this product development cycle and In vivo characterization
and, of course, extensive in vitro testing is often developed what can be
referred to as retrospective IVIVC.
The defined formulation that meets the in vivo specification is
employed for Stage 2. At this stage based on a greater understanding
and appreciation of defined formulation and its characteristics, a
prospective IVIVC is established through a well defined prospective
IVIVC study [18,5].
Step 1
In the first step, the In vivo input profile of the drug from different
formulations is calculated from drug concentrations in plasma (Figure
3). The target In vivo profile needs to be first established, based on, if
possible, pharmacokinetic/pharmacodynamic models. Certainly, step
1 activity should culminate in a pilot PK study. This is typically a four
or five-arm cross-over study. The size of this pilot pharmacokinetic
study will vary depending on the inherent variability of the drug itself
but typically range from 6 to 10 subjects [5]. The results of this pilot PK
study provide the basis for establishing what has been referred to as a
retrospective IVIVC .To separate drug input from drug distribution
and elimination, model-dependent approaches, such as Wagner-
Nelson and Loo-Riegelman, or model independent procedures, based
on numerical deconvolution, may be utilised [19,20,21]. In step 1, the
parameters that describe drug input rate, drug distribution and/or
elimination are determined. In the model dependent approaches, the
distribution and elimination rate constants describe pharmacokinetics
after absorption. In the numerical deconvolution approach, the drug
unit impulse response function describes distribution and elimination
phases, respectively. The physicochemical characteristics of the drug
substance itself, in relevance to formulation approach and dissolution
at distal sites in the gastro-intestinal tract, need to be taken into account.
Based on this information a priori in vitro methods are usually then
developed and a theoretical in vitro target is established, which should
achieve the desired absorption profile [5,18].
Step 2
By this phase of the development process, a defined formulation
that meets the In vivo targets has been achieved. Extensive In vitro
characterization is again performed across pH, media and apparatus,
along with the consideration of results of stage 1. This leads to
execution of a prospective IVIVC study. The IVIVC is developed
and defined after an analysis of the result of that prospective in vivo
study. It can often involved further in vitro method development in
the context of the observed results, but clearly with the objective of
establishing a definitive IVIVC. In this step, the relationship between

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Step1;
Step3;
Step 2: IVIVC
% absorbed
%Dissolved
Prospective
Time (hr)
Time (hr)
% Released
In vitro Dissolution
Release rate:
Release rate:
Release rate:
Release rate:
Fast
Fast
Fast
Fast
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Assumed IVIVC
Retrospectiv IVIVC
Defined formulation
DECONVOLUTION
IVIVC
IVIVC
In vivo absorption
Absorbed
Time
Comcentration
(mg/ml)
VALIDATION
Predicted Plasma Levels
Concentration
(ng/ml)
Time
observed plasma LeveiS
CONVOLUTION
Figure 3: Development of IVIVC with validation.
in vitro dissolution and the in vivo drug input profile is determined
(Figure 3). Either a linear or nonlinear relationship may be found.
In some cases, time-scaling of in vitro data must be used, because In
vitro dissolution and In vivo input may follow the same kinetics but
still have different time-scales [6,22]. The time-scaling factor should be
the same for all formulations if an IVIVC at level A is sought. During
the early stages of correlation development, dissolution conditions may
be altered to attempt to develop a 1-to-1 correlation between the in
vitro dissolution profile and the In vivo dissolution profile. This work
should also result in the definitive in vitro method that has been shown
to be correlated with in vivo performance and sensitive to the specific
formulation variables.
Step 3
In this phase plasma drug concentration profiles are predicted
and compared to the observed time courses for different formulations
(Figure 3). To generate predicted time courses, the drug input profile
is predicted based on In vitro dissolution data and the In vitro-In
vivo relationship generated in step 2. In the convolution process, the
predicted drug input and parameters describing drug distribution and/
or elimination phases are combined in order to get predicted time
courses. This procedure, which includes steps 1-3, is called two-stage
deconvolution. Alternatively, a drug input profile based on in vitro
dissolution data can be solved together with parameters describing
systemic pharmacokinetics, i.e. distribution and elimination. This
approach is called direct convolution.
Different IVIVC model are used as a tool for formulation
development and evaluation of immediate and extended release dosage
forms for setting a dissolution specification and as a surrogate for
bioequivalence testing.
As a result, considerable effort goes into their development and
the main outcome is “the ability to predict, accurately and precisely,
expected bioavailability characteristics for an extended release (ER)
drug product from dissolution profile characteristics [10].

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Once the IVIVC is established and defined it can be then used to
guide the final cycle of formulation and process optimization program
statistically based experimental design studies looking at critical
formulation and process variables. This information can also be used
into the activities of scale-up, pivotal batch manufacture, and process
validation culminating in registration, approval and subsequent post-
approval scale-up and other changes. Thus rather than viewing the
IVIVC as a single exercise at a given point in a development program,
one should view it as a parallel development in itself starting at the initial
assumed level and being built on and modified through experience and
leading ultimately to a prospective IVIVC”.
Validation of IVIVC Model
Evaluation of predictability of IVIVC
Prediction errors are estimated for Cmax
and AUC to determine the
validity of the correlation.
Various approaches of are used to estimate the magnitude of the
error in predicting the in vivo bioavailability results from in vitro
dissolution data.
Predictability of correlation
The objective of IVIVC evaluation is to estimate the magnitude
of the error in predicting the in vivo bioavailability results from in
vitro dissolution data. This objective should guide the choice and
interpretation of evaluation methods. Any appropriate approach
related to this objective may be used for evaluation of predictability
[5,23]. It can be calculated by Prediction error that is the error in
prediction of in vivo property from in vitro property of drug product
(Figure 3).
Depending on the intended application of an IVIVC and the
therapeutic index of the drug, evaluation of prediction error internally
and/or externally may be appropriate [24].
Internal predictability
Evaluation of internal predictability is based on the initial data used
to define the IVIVC model. Internal predictability is applied to IVIVC
established using formulations with three or more release rates for non-
narrow therapeutic index drugs exhibiting conclusive prediction error.
If two formulations with different release rates are used to develop
IVIVC, then the application of IVIVC would be limited to specified
categories. The bioavailability (Cmax
, tmax
/AUC) of formulation that is
used in development of IVIVC is predicted from its in vitro property
using IVIVC. Comparison between predicted bioavailability and
observed bioavailability is done and % P.E is calculated. According to
FDA guidelines, the average absolute %P.E should be below 10% and
%P.E for individual formulation should be below 15% for establishment
of IVIVC.
Under these circumstances, for complete evaluation and
subsequent full application of the IVIVC, prediction of error externally
is recommended [23].
Acceptance criteria
According to FDA guidance
1) ≤15%forabsolutepredictionerror(%P.E.)ofeachformulation.
2) ≤ 10% for mean absolute prediction error (%P.E.).
External predictability
Most important when using an IVIVC as a surrogate for
bioequivalence is confidence that the IVIVC can predict in vivo
performance of subsequent lots of the drug product. Therefore, it may
be important to establish the external predictability of the IVIVC.
Evaluation of external predictability is based on additional test data
sets [5]. External predictability evaluation is not necessary unless the
drug is a narrow therapeutic index, or only two release rates were used
to develop the IVIVC, or, if the internal predictability criteria are not
met i.e. prediction error internally is inconclusive [4,23]. The predicted
bioavailability is compared with known bioavailability and % P.E is
calculated. The prediction error for external validation should be below
10% whereas prediction error between 10-20% indicates inconclusive
predictability and need of further study using additional data set [24].
The % prediction error can be calculated by the following equation:
Prediction error
For Cmax
max max
max
( )
%Prediction error (P.E.)= 100
C observed C predicted
C observed
−
× (5)
For AUC:
(AUC AUC )
%Prediction error (P.E.)= 100
AUC
observed predicted
observed
−
× (6)
Limitation of predictability metrics
Metrics used to evaluate the predictability is described simply
the prediction error (%P.E.) for only two PK parameters i.e. Cmax
and
AUC. Emax
predicted with IVIVC model represents the maximum of
the mean plasma profiles but is compared with the mean Cmax
observed
calculated as the average of individual profile at different Tmax
. But Tmax
is not included in predictability metrics.
Factors to be Consider in Developing a Correlation
Biopharmaceutics classification system (BCS)
Biopharmaceutics Classification System (BCS) is a fundamental
guideline for determining the conditions under which in-vitro, in-vivo
correlations are expected [25]. It is also used as a tool for developing the
in-vitro dissolution specification.
The classification is based on the drug dissolution and absorption
model, which identifies the key parameters controlling drug absorption
as a set of dimensionless numbers: the Absorption number, the
Dissolution number and the Dose number [25-27].
The Absorption number is the ratio of the mean residence time to
the absorption time.
2
/ ( / ) / ( / )n res abs effA T T R L Q R Pπ= + (7)
The Dissolution number is a ratio of mean residence time to mean
dissolution time given as equation 2
2 2 min
0/ ( / ) / ( / 3 )n res diss sD T T R L Q pr DCπ= + (8)
The Dose number is the mass divided by an uptake volume of 250
ml and the drug’s solubility as Equation 3
min
/ ( / )o o sD Dose V C= (9)
The mean residence time here is the average of the residence time

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in the stomach, small intestine and the colon. The fraction of dose
absorbed then can be predicted based on these three parameters. For
example, Absorption number 10 means that the permeation across
the intestinal membrane is 10 times faster than the transit through the
small intestine indicating 100% drug absorbed.
In the BCS, a drug is classified in one of four classes based solely on
its solubility and intestinal permeability [27].
A biopharmaceutic drug classification scheme for correlating in
vitro drug product dissolution and in vivo bioavailability is proposed
based on recognizing that drug dissolution and gastrointestinal
permeability are the fundamental parameters controlling rate and
extent of drug absorption. This classification system was devised by
Amidon et al. [27].
The drugs are divided into high/low-solubility and permeability
classes. Currently, BCS guidelines are provided by USFDA, WHO, and
EMEA (European Medicines Academy)
Class I: HIGH solubility / High permeability,
Class II: LOW solubility / High permeability,
Class III: HIGH solubility / LOW permeability,
Class IV: LOW solubility / LOW permeability.
Class I: High solubility- high permeability drugs
In case of class I , drugs (such as metoprolol) is well absorbed
(though its systemic availability may be low due to first pass
extraction/ metabolism) and the rate limiting step to drug absorption
is drug dissolution or gastric emptying if dissolution is very rapid.
The dissolution specification immediate release (IR) dosage forms of
perhaps 85% dissolved in less than 15 min. May insure bioequivalence.
To insure bioavailability for this case, the dissolution profile must be
well defined and reproducible. [5,27].
Class II: Low solubility- high permeability drugs
This is the class of drugs (such as phenytoin) for which the
dissolution profile must be most clearly defined and reproducible.
More precisely this is the case where absorption number, (An) is high
and Dissolution number (Dn) is low. Drug dissolution in vivo is then
the rate controlling step in drug absorption and absorption is usually
slower than for class I [28-31].
Class III: High solubility-low permeability drugs
For this class of drugs (such as cimetidine) Permeability is the rate
controlling step in drug absorption. While the dissolution profile must
be well defined, the simplification in dissolution specification as in Class
I is applicable for immediate release dosage forms where drug input to
the intestine is gastric emptying rate controlled.. Both rate and extent
of drug absorption may be highly variable for this class of drugs, but id
dissolution is fast i.e. 85% dissolved in less than 15 min, this variation
will be due to the variable gastrointestinal transit, luminal contents ,
and membrane permeability rather than dosage form factors [5].
Class IV: Low solubility-low permeability drugs
This class of drugs present significant problems for effective oral
delivery. The number of drugs that fall in this class will depend on the
precise limits used from the permeability and solubility classification.
Applications
ThisconceptunderlyingtheBCSpublishedfinallyledtointroducing
the possibility of waiving in vivo bioequivalence (BE) studies in favor of
specific comparative in vitro testing to conclude BE of oral immediate
release (IR) products with systemic actions [32].
In terms of BE, it is assumed that highly permeable, highly soluble
drugs housed in rapidly dissolving drug products will be bioequivalent
and that, unless major changes are made to the formulation, dissolution
data can be used as a surrogate for pharmacokinetic data to demonstrate
BE of two drug products. The BCS thus enables manufacturers to reduce
the cost of approving scale-up and post approval changes to certain
oral drug products without compromising public safety interests [33].
It is a drug-development tool that allows estimation of the
contributions of three major factors, dissolution, solubility and
intestinal permeability that affect oral drug absorption from IR solid
oral dosage forms. It was first introduced into regulatory decision-
making process in the guidance document on immediate release solid
oral dosage forms: Scale-up and post approval changes [2]. BCS system
is an indicator of developing a predictive IVIVC and also examined
the importance of drug dissolution and permeability on IVIVC validity
(Table 2).
The establishment of correlation needs, as described in
the FDA or USP definitions, to use various parameters
summarized in following table: Waiver of in vivo BE studies
Class Solubility Permeability IVIVC correlation for IR Products
I High High
IVIVC correlation if dissolution rate is slower
than gastric emptying rate, otherwise limited
or no correlation
II Low High
IVIVC correlation expected if in in vitro
dissolution rate is similar to in vivo dissolution
rate , unless dose is very high
III High Low
Absorption [permeability] is rate determining
and limited or no IVIV correlation with
dissolution rate.
IV Low Low Limited or no IVIV correlation expected.
Table 2: IVIV correlation expectation for immediate release product based on
biopharmaceutic class.
Biopharmaceutics Drug Classification
for Extended Release Drug Products **
Class Solubility Permeability
IVIVC
IA
High & Site
Independent
High & Site Independent
IVIVC Level A
expected
IB
High & Site
Independent
Dependent on site & Narrow
Absorption Window
IVIVC Level
C expected
IIa
Low & Site
Independent High & Site Independent
IVIVC Level A
expected
IIb
Low & Site
Independent
Dependent on site & Narrow
Absorption Window
Little or no
IVIVC
Va:
Acidic Variable Variable
Little or no
IVIVC
Vb:
basic
Variable Variable
IVIVC Level A
expected.
Table 3: Biopharmaceutics Drug Classification for Extended Release Drug
Products.

doi:10.4172/jbb.S3-001
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based on BCS Recommended for a solid oral Test product that exhibit
rapid (85% in 30 min) and similar in vitro dissolution under specified
conditions to an approved Reference product when the following
conditions are satisfied (Table 3,4):
• Products are pharmaceutical equivalent
• Drug substance is highly soluble and highly permeable and is
not considered have a narrow therapeutic range
• Excipients used are not likely to effect drug absorption
In vitro dissolution
Dissolution plays the important role in the formulation
development as an obvious stage in IVIVC development when the
dissolution is not influenced by factors such as pH, surfactants, osmotic
pressure, mixing intensity, enzyme, ionic strength. Drug absorption
from a solid dosage form following oral administration depends on the
release of the drug substance from the drug product, the dissolution
or solubilization of the drug under physiological conditions, and the
permeability across the gastrointestinal tract. The purpose of the in-
vitro dissolution studies in the early stage of drug development is to
select the optimum formulation, evaluate the active ingredient and
excipients, and assess any minor changes for drug products. During
the early stages of correlation development, dissolution conditions
may be altered to attempt to develop a one-to-one correlation between
the in vitro dissolution profile and the in vivo dissolution profile [5].
For the IVIVC perspective, dissolution is proposed to be a surrogate
of drug bioavailability. Thus, dissolution standard may be necessary
for the in-vivo waiver [26]. The dissolution methodology, which is
able to discriminate between the study formulations and which best,
reflects the in vivo behavior would be selected. Once a discriminating
system is developed, dissolution conditions should be the same for all
formulations tested in the biostudy for development of the correlation
and should be fixed before further steps towards correlation evaluation
are undertaken [34]. The types of dissolution apparatus used as per
USP recommended in the FDA guidance especially, for modified
release dosage form are specified by the USP and are:
[1] Rotating basket,
[2] Paddle method,
[3] Reciprocating cylinder,
[4] Flow through cell,
Other dissolution methodologies may be used, however, the first
four are preferred, especially the basket and paddle. But primarily it is
recommended to start with the basket or paddle method prior to using
the others [26].
The in vitro dissolution release of a formulation can be modified
to facilitate the correlation development. Changing dissolution testing
conditions such as stirring speed, choice of apparatus, pH of the
medium, and temperature may alter the dissolution profile.
As previously described, appropriate dissolution testing conditions
should be selected so that the formulation behaves in the same manner
as the in vivo dissolution.
For an appropriate dissolution test, in general and in particular
for developing IVIVC, one requires to conduct the test selecting
experimental conditions to simulate an in vivo environment as closely
as possible. Commonly the following experimental conditions should
be considered in this regard.
A common dissolution medium is dearated water, simulated gastric
fluid (pH 1.2), or intestinal fluid (pH 6.8 or 7.4) without enzyme, and
buffers with a pH range of 4.5 to 7.5 and be maintained at 37°C. For
sparingly water-soluble drugs, use of surfactants in the dissolution
medium is recommended [34,35]. A simple aqueous dissolution media
is also recommended for BCS Class I drug as this type of drug exhibits
lack of influence of dissolution medium properties [5,36]. Water and
simulated gastric fluid then are the default mediums for most of the
Class I drugs. A typical medium volume is 500 to 1000 ml.
1. Frequent samples (8-10) should be withdrawn to obtain a
smooth dissolution profile leading to complete dissolution
within the dosing interval of the test product in humans.
2. The normal test duration for immediate release is 15 to 60
minutes with a single time point. For example, BCS class I
recommend 15 minutes. Additionally, two time points may be
required for the BCS class II at 15 minutes and the other time
at which 85% of the drug is dissolved [36].
3. In contrast, in vitro dissolution tests for a modified release
dosage form require at least three time points to characterize
the drug release. The first sampling time (1-2 hours or 20- 30%
drug release) is chosen to check dose-dumping potential. The
intermediate time point has to be around 50% drug release in
order to define the in vitro release profile.
4. The dissolution medium should not be de-aerated. Preference
should be given that the medium be equilibrated at 37°C with
dissolved air/gasses, particularly for IVIVC studies.
5. An apparatus should be selected to have an appropriate
BCS Class Examples Drug delivery technology
Class I
Metoprolol, Diltizem, Verapamil, Propranolol,
Acyclovir, Atropine, verapamil.
Macrocap, Micropump, MODAS (Multiporous oral drug absorption system), SCOT (Single
composition osmotic tablet system), and SPDS (Stabilized pellet delivery system) [28,30,31].
Class II
Phenytoin, Danazole, Ketokonazole, Mefenamic
acid, Tacrolimus, Piroxicam, griseofulvine,
Warfarin,
Micronization, stabilization of high-energy states (including lyophilized fast-melt systems), use of
surfactants, emulsion or microemulsion systems, solid dispersion and use of complexing agent such
as cyclodextrins.e.g nanosuspension and nanocrystals are treated as hopeful means of increasing
solubility and BA of poorly water-soluble active ingredients [28,30,31].
Class III Cimetidine, Neomycin, ranitidine, Amoxycillin,
Oral vaccine system, Gastric retention system, High-Frequency Capsule and Telemetric Capsule
[28,30,31].
Class IV
Cyclosporin A, Furosemide, Ritonavir,
Saquinavir andTaxol.
The class IV drugs present a major challange for the development of drug delivery systems due to
their poor solubility and permeability characteristics. These are administered by parenteral route
with the formulation containing solubility enhancers [ 28,30,31].
Table 4: BCS class and drug delivery technology.

doi:10.4172/jbb.S3-001
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mechanism to provide thorough but gentle mixing and stirring
for an efficient product/medium interaction. Use of sinkers may
be avoided as these often alter the dissolution characteristics of
the test products. Paddle and basket apparatuses are known for
their inefficient stirring and mixing, thus their use should be
critically evaluated before use for IVIVC studies.
6. The last time point is to define essentially complete drug
release. The dissolution limit should be at least 80% drug
release. Further justification as well as 24 hours test duration
are required if the percent drug release is less than 80 [34,37].
7. If the dissolution results are not as expected, then the product/
formulation should be modified to obtain the desired/expected
release characteristics of the product. However, altering
experimental conditions such as medium, apparatus, rpm etc.
should be avoided as these are generally linked to GI physiology
which remains the same for test to test or product to product.
Obtaining dissolution results by altering testing (experimental)
conditions may void the test for IVIVC purposes.
Once the discriminatory system is established, dissolution testing
conditions should be fixed for all formulations tested for development
of the correlation [6]. A dissolution profile of percentage or fraction of
drug dissolved versus time then can be determined.
Comparison between dissolution profiles could be achieved using
a difference factor (f1
) and a similarity factor (f2
) which originates from
simple model independent approach. The difference factor calculates
the percent difference between the two curves at each time point and is
a measurement of the relative error between the two curves:
1
1 1
/ *100
n n
t t t
t r
f R T R
= =
    
=  −      
    
∑ ∑ (10)
Where, n is the number of time points, Rt is the dissolution value of
the reference batch at time t, and Tt is the dissolution value of the test
batch at time t. The similarity factor is a logarithmic reciprocal square
root transformation of the sum squared error and is a measurement of
the similarity in the percent dissolution between the two curves
0.5
2
1
50*log 1 (1/ ) *100
n
t t
t
f n R T
−
2
=
   
= + ( − )  
   
∑ (11)
Generally, f1 values up to 15 (0-15) and f2 values greater than 50
(50-100) ensure sameness or equivalence of the two curves. The mean
in vitro dissolution time (MDTvitro) is the mean time for the drug to
dissolve under in vitro dissolution conditions. This is calculated using
the equation 6:
0
( ( )) /vitroMDT M M t dt M
∞
∞ ∞= −∫ (12)
For the IVIVC development, the dissolution profiles of at least
12 individual dosage units from each lot should be determined. The
coefficient of variation (CV) for mean dissolution profiles of a single
batch should be less than 10%. Since dissolution apparatuses tend
to become less discriminative when operated at faster speeds, lower
stirring speeds should be evaluated and an appropriate speed chosen
in accordance with the test data. Using the basket method the common
agitation is 50-100 rpm; with the paddle method, it is 50-75 rpm and 25
rpm for suspension [5].
In vivo absorption (Bioavailability studies)
The FDA requires in vivo bioavailability studies to be conducted
for a New Drug Application (NDA). A bioavailability study should
be performed to characterize the plasma concentration versus time
profile for each of the formulation. These studies for the development
of IVIVC should be performed in young healthy male adult volunteers
under some restrictive conditions such as fasting, non-smoking,
and no intake of other medications. In prior acceptable data sets,
the number of subjects has ranged from 6 to 36. Although crossover
studies are preferred, parallel studies or cross-study analyses may
be acceptable. The latter may involve normalization with a common
reference treatment. The drug is usually given in a crossover fashion
with a washout period of at least five half-lives.
The bioavailability study can be assessed via plasma or urine data
using the following parameters: (I) area under the plasma time curve
(AUC), or the cumulative amount of drug excreted in urine (Du), (II)
maximum concentration (Cmax
), or rate of drug excretion in urine
(dDu/dt), and (III) a time of maximum concentration (Tmax
).
Several approaches can be used for determining the In vivo
absorption. Wagner-Nelson, Loo-Riegelman, and numerical
deconvolution are such methods [2,37]. Wagner Nelson and Loo-
Riegelman are both model dependent methods in which the former
is used for a one-compartment model and the latter is for multi-
compartment system.
The Wagner Nelson method is less complicated than the Loo-
Riegelman as there is no requirement for intravenous data. However,
misinterpretation on the terminal phase of the plasma profile may be
possible in the occurrence of a flip flop phenomenon in which the rate
of absorption is slower than the rate of elimination.
Application of An IVIVC
Application in drug delivery system
Various rate controlling technologies are used as the basis for
Modified release dosage forms e.g. Diffusion-dissolution, matrix
retardation, osmosis, etc. to control, and prolong the release of drugs,
for the administration by oral or parenteral route [24,38].
The novel drug delivery systems have been developed such
as OROS, liposomes, niosomes, pharmacosomes, microspheres,
nanoparticles, implants, in situ gelling system, organogels, transdermal
drug delivery systems, parenteral depots, etc. as a substitute for
conventional dosage forms. The obvious objective of these dosage
forms is to achieve zero-order, long term, pulsatile, or “on demand”
delivery. Major applications of IVIVC related to oral drug delivery and
a few issues related to the development of IVIVC models for parenteral
drug delivery are addressed herewith [39].
In early stages of drug delivery technology development
The most crucial stage in the drug development is drug candidate
selection. Such selection is primarily based on the drug “developability”
criteria, which include physicochemical properties of the drug and the
results obtained from preformulation, preliminary studies involving
several in vitro systems and in vivo animal models, which address
efficacy and toxicity issues [24,40]. During this stage, IVIVC (exploring
the relationship between in vitro and in vivo properties) of the drug in
animal models provide an idea about the feasibility of the drug delivery
system for a given drug candidates. In such correlations, study designs
including study of more than one formulation of the modified-release

doi:10.4172/jbb.S3-001
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dosage forms and a rank order of release (fast/slow) of the formulations
should be incorporated. Even though the formulations and methods
used at this stage are not optimal, they promise better design and
development efforts in the future.
Formulation assessment: In vitro dissolution
A suitable dissolution method that is capable of distinguishing the
performance of formulations with different release rates in vitro and in
vivo is an important tool in product development. Depending on the
nature of the correlation, further changes to the dissolution method can
be made. When the discriminatory in vitro method is validated, further
formulation development can be relied on the in vitro dissolution only.
Dissolution specifications
Modified-release dosage forms typically require dissolution testing
over multiple time points, and IVIVC plays an important role in setting
these specifications [24,39]. Specification time points are usually chosen
in the early, middle, and late stages of the dissolution profiles. In the
absence of an IVIVC, the range of the dissolution specification rarely
exceeds 10% of the dissolution of the pivotal clinical batch. However,
in the presence of IVIVC, wider specifications may be applicable based
on the predicted concentration-time profiles of test batches being
bioequivalent to the reference batch.
The process of setting dissolution specifications in the presence
of an IVIVC starts by obtaining the reference (pivotal clinical batch)
dissolution profile. The dissolution of batches with different dissolution
properties (slowest and fastest batches included) should be used along
with the IVIVC model, and prediction of the concentration time
profiles should be made using an appropriate convolution method.
Specifications should optimally be established such that all batches
with dissolution profiles between the fastest and slowest batches
are bioequivalent and less optimally bioequivalent to the reference
batch. The above exercise in achieving the widest possible dissolution
specification allows majority of batches to pass and is possible only if a
valid Level A model is available [24].
Future biowaivers
Frequently, drug development requires changes in formulations
due to a variety of reasons, such as unexpected problems in stability,
development, availability of better materials, better processing results,
etc. Having an established IVIVC can help avoid bioequivalence studies
by using the dissolution profile from the changed formulation, and
subsequently predicting the in vivo concentration-time profile [24,41].
This predicted profile could act as a surrogate of the in vivo
bioequivalencestudy.Thishasenormouscost-savingbenefitintheform
of reduced drug development spending and speedy implementation
of post-approval changes. The nature of post-approval changes
could range from minor (such as a change in non release-controlling
excipient) to major (such as site change, equipment change, or change
in method of manufacture, etc) [24,42].
IVIVC - Parenteral drug delivery
IVIVC can be developed and applied to parenteral dosage forms,
such as controlled-release particulate systems, depot system, implants,
etc, that are either injected or implanted. However, there are relatively
fewer successes in the development of IVIVC for such dosage forms,
which could be due to several reasons, a few of which are discussed
further. Sophisticated modeling techniques are needed to correlate the
in vitro and in vivo data, in case of burst release which is unpredictable
and unavoidable [24,43].
Potent Drugs & Chronic Therapy - In general, several parenteral
drug delivery systems are developed for potent drugs (eg, hormones,
growth factors, antibiotics, etc) and for long-term delivery (anywhere
from a day to a few weeks to months). In such instances, to establish
a good IVIVC model, the drug concentrations should be monitored
in the tissue fluids at the site of administration by techniques such as
microdialysis, and then the correlation should be established to the in
vitro release.
Biowaivers
Validated IVIVC is applicable to serve as justification for a
biowaiver in filings of a Level 3 (or Type II in Europe) variation, either
during scale-up or post approval, as well as for line extensions (e.g.,
different dosage strengths). A biowaiver will only be granted if the
prediction of the in vivo performance of the product with the modified
in vitro release rate remains bioequivalent with the originally tested
product (i.e., the new dissolution rate remains within the IVIVC based
biorelevant corridor).
The FDA guidance outlines five categories of biowaivers: 1)
biowaivers without an IVIVC, 2) biowaivers using an IVIVC: non-
narrow therapeutic index drugs, 3) biowaivers using an
IVIVC: narrow therapeutic index drugs, 4) biowaivers when in
vitro dissolution is independent of dissolution test conditions and 5)
situations for which an IVIVC is not recommended for biowaivers
Biowaivers may be granted for manufacturing site changes, equipment
changes, manufacturing process changes, and formulation composition
changes according to a predictive and reliable IVIVC. The changes
may range from minor changes that are not significant to alter product
performance to major ones where an IVIVC is not sufficient to justify
the change for regulatory decision [4,24].
Establishment of dissolution specifications
It is relatively easy to establish a multipoint dissolution specification
for modified-release dosage forms .The dissolution behavior of the
biobatch maybe used to define the amount to be released at each time
point.However,thedifficultyarisesinthevariationtobeallowedaround
each time point [37]. The FDA guidance describes the procedures of
setting dissolution specifications in cases of level A, multiple levels C,
and level C correlation and where there is no IVIV correlation. Once an
IVIVC developed, IVIVC should be used to set specifications in such
a way that the fastest and lowest release rates allowed by the upper and
lower dissolution specifications result in a maximum difference of 20%
in the predicted Cmax
and AUC. Predicted plasma concentration and
consequent AUC and Cmax
could be calculated using convolution or
any other appropriate modeling techniques [24]. In the case of multiple
level C correlation, the last time point should be the time point where
at least 80% of drug has dissolved. For level C correlation, reasonable
deviations from ±10 % may be acceptable if the range at any time
point does not exceed 25%. When there is no IVIVC, the tolerance
limits may be derived from the spread of in vitro dissolution data of
batches with demonstrated acceptable in vivo performance (biobatch)
or by demonstrating bioequivalence between batches at the proposed
upper and lower limit of the dissolution range (the so called side batch

doi:10.4172/jbb.S3-001
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concept). Variability in release at each time point is recommended not
to exceed a total numerical difference of ±10% (a total of 20%) or less
of the labeled claim. In certain cases, deviations from this criterion can
be acceptable up to a maximum range of 25%. Beyond this range, the
specification should be supported by bioequivalence studies [43].
Mapping
Mapping is a process which relates Critical Manufacturing
Variables (CMV), including formulation, processes, and equipment
variables that can significantly affect drug release from the product.
The mapping process defines boundaries of in vitro dissolution profiles
on the basis of acceptable bioequivalency criteria. The optimum goal
is to develop product specifications that will ensure bioequivalence
of future batches prepared within the limits of acceptable dissolution
specifications. Dissolution specifications based on mapping would
increase the credibility of dissolution as a bioequivalency surrogate
marker and will provide continuous assurance and predictability of the
product performance [5].
Some Limitations in the IVIVC Arising from the In
Vivo Data
Could easily be understood:
1. More than one dosage form is needed and if possible intravenous
or solution is essential to calculate deconvolution.
2. Pharmacokinetics and absorption of the drug should be ‘‘linear.’’
If the pharmacokinetic processes are dependent on the
fraction of dose reaching the systemic blood flow (or of the
dose administered) or on the rate of absorption, comparison
between formulation and simulation cannot be made. This
non-linearity may be owing to saturable absorption processes
(active absorption), induction or inhibition of the metabolism,
the first past effect, which is rate/absorption dependent, etc.
Those points must be studied before any attempt to establish
an IVIVC.
3. Absorption should not be the limiting factor, if the solubility
is not the limiting factor in comparison to the drug release,
an IVIVC may be attempted. The release must depend on
the formulation, and must be the slowest phenomenon vs.
dissolution and absorption.
Conclusions
The pharmaceutical industry has been striving to find a ways to
savingpreciousresourcesinrelevancetothebudgetsandincreasingcost
of drug development. IVIVC is a tool applied in various areas and stages
of drug development to find a place in the regulatory bodies around
the world. IVIVC can serve as surrogate for in vivo bioavailability and
to support biowaivers also allows setting the dissolution specification
and methods. The substitute of expensive clinical trials with the use
of IVIVC is perhaps the most important feature of IVIVC. From the
regulatory point of view IVIVC can assist certain scale-up and post-
approval changes. IVIVC principles have been mostly applied to oral
products, there exists a need to develop methodologies and standards
for non-oral delivery systems, to develope more meaningful dissolution
and permeation methods.
Acknowledgement
The authors gratefully acknowledge Mrs. Sangita Sakore (Regulatory affairs,
Formulation & Development, MKPPL, Pune, India) for her contribution.
References
1. Leeson LJ (1995) In vitro/ In vivo correlations. Drug Info J 29: 903-915.
2. US Department of Health and Human Services (1995) Guidance for industry:
Immediate release solid oral dosage forms scale-up and postapproval changes:
chemistry, manufacturing, and controls, in vitro dissolution testing, and in vivo
bioequivalence documentation. Center for drug Evaluation and Research.
3. Center for Drug Evaluation, USFDA (1995) Guidance for Industry: Immediate
Release Solid Oral Dosage Forms: Scale Up and Post Approval Changes.
4. Uppoor VRS (2001) Regulatory perspectives on in vitro (dissolution)/in vivo
(bioavailability) correlations. J Control Rel 72: 127-132.
5. Jaber E (2006) In vitro - In vivo Correlation: From Theory to Applications. J
Pharm Pharmaceut Sci 9: 169-189.
6. Food and Drug Administration (1997) Guidance for industry: extended release
oral dosage forms: Development, evaluation, and application of in vitro/in vivo
correlations.
7. Sirisuth N, Eddington ND (2002) In vitro in vivo correlations, systemic methods
for the development and validation of an IVIVC metoprolol and naproxen drug
examples. Int J Generic Drugs 3: 250-258.
8. Qureshi SA (2010) In Vitro-In Vivo Correlation (IVIVC) and Determining Drug
Concentrations in Blood from Dissolution Testing - A Simple and Practical
Approach. Open Drug Delivery J 4: 38-47.
9. O’Hara T, Hayes S, Davis J, Devane J, Smart T, et al. (2001) In vivo-In
Vitro Correlation (IVIVC) Modeling Incorporating a Convolution Step. J
Pharmacokinet Pharmacodyn 28: 277-298.
10. Gaynor C, Dunne A, Davis J (2008) A Differential Equations Approach to In
Vitro – In Vivo Correlation Modelling. International Biometric Conference,
Dublin.
11. Dunne A (2007) Approaches to developing IVIVC models, Ch 5. In Chilukuri,
Sunkara and Young (Eds), Pharmaceutical Product Development: In Vitro – In
vivo Correlation. Taylor and Francis, New York.
12. Beal SL, Sheiner LB (1992) NONMEM User’s Guides, NONMEM Project
Group, University of California, San Francisco.
13. Meyer MC, Straughn AB, Mhatre RM, Shah VP ,Williams RL (1998) Lack of in
vitro / in vivo correlations of 50 mg and 250 mg primidone tablets. Pharm Res
15: 1085-1089.
14. Food and Drug Administration. Rockville, MD Abdou, HM (1989) Dissolution
Bioavailability and Bioequivalence. Easton Pennsylvania: Mack Printing.
15. Buchwald P (2003) Direct, differential-equation-based in-vitro-in-vivo correlation
(IVIVC) method. J Pharm Pharmacol 55: 495-504.
16. Dressman JB, Amidon GL, Reppas C, Shah VP (1998) Dissolution testing as
a prognostic tool for oral drug absorption: immediate release dosage forms.
Pharm Res 15: 11-22.
17. Corrigan OI (1997) The biopharmaceutic drug classification and drugs
administered in extended release (ER) formulations. Adv Exp Med Biol 423:
111-128.
18. Yu H, Joves R (2004) The STATs of cancer--new molecular targets come of
age. Nat Rev Cancer 4: 97-105.
19. Wagner JG, Nelson E (1964) Kinetic analysis of blood levels and urinary
excretion in the absorptive phase after single doses of drug. J Pharm Sci 53:
1392-1403.
20. Loo JC, Riegelman S (1968) New method for calculating the intrinsic absorption
rate of drugs. J Pharm Sci 57: 918-928.
21. Cutler DJ (1978) Linear system analysis in pharmacokinetics. Pharmacokinet
Biopharm 6: 265-282.
22. Brockmeier D, Voegele D, von Hattingberg HM (1983) In vitro-in vivo
correlation, a time scaling problem? Basic techniques for testing equivalence.
Arzneimittelforschung 33: 598-601.
23. Jayaprakasam B, Seeram NP, Nairs MG (2003) Anticancer and antiinflammatory
activities of cucurbitacins from Cucurbita andreana. Cancer Lett 189: 11-16.

doi:10.4172/jbb.S3-001
Page 12 of 12
24. Chilukuri DM, Sunkara G (2003) IVIVC: An Important Tool in the Development
of Drug Delivery Systems. Drug Deliv Technol 3: 4.
25. Young D, Devane JG, Butler J (1997) In Vitro-In Vivo Correlations. New York:
Plenum press.
26. Amidon GL, Robinson JR, Williams RL (1997) Scientific Foundations for
Regulating Drug Product Quality. American Association of Pharmaceutical
Scientists. Alexandria, Virginia: AAPS Press.
27. Amidon GL, Lennernas H, Shah VP, Crison JR (1995) A theoretical basis for
a biopharmaceutic drug classification: The correlation of in vitro drug product
dissolution and in vivo bioavailabilty. Pharm Res 12: 413-419.
28. Gohel MC, Mehta NR (2005) An audit of recent inputs on biopharmaceutical
classification system. Pharmaceut Rev.
29. Yu LX, Amidon GL, Polli JE, Zhao H, Mehta MU, et al. (2002) Biopharmaceutics
classification system: The scientific basis for biowaiver extension. Pharm Res
19: 921-925.
30. Wilding I (1999) Evolution of the Biopharmaceutics Classification System
(BCS) to Modified Release (MR) formulations: What do we need to consider?
Eur J Pharm Sci 8: 157-159.
31. Devane J (1998) Oral drug delivery technology: Addressing the solubility/
permeability paradigm. Pharmaceut Technol 22: 68-80.
32. Helga M (2002) The Biopharmaceutical Classification System (BCS) and its
usage. Drugs Made in Germany 45: 63-65.
33. Dressman J, Butler J, Hempenstall J, Reppas C (2001) The BCS: Where do
we go from here? Pharmaceut Technol 25: 68-76.
34. Sievert B, Siewert M (1998) Dissolution tests for ER products. Dissolut Technol 5.
35. Shargel L, Yu ABC (1993) Applied Biopharmaceutics and Pharmacokinetics.
East Norwark, Connecticut: Appleton & Lange.
36. Galia E, Nicolaides E, Horter D, Lobenberg R, Reppas C, et al. (1998)
Evaluation of various dissolution media for predicting in vivo performance of
class I and class II drugs. Pharm Res 15: 698-705.
37. Abdou HM (1989) Dissolution, Bioavailability and Bioequivalence. Easton,
Pennsylvania: Mack Printing.
38. Strickley RG (1999) Parenteral formulations of small molecules therapeutics
marketed in the United States Part I, PDA. J Pharm Sci Tech 53: 324-349.
39. Modi NB, Lam A, Lindemulder E, Wang B, Gupta SK (2000) Application of
in vitro-in vivo correlation (IVIVC) in setting formulation release specifications.
Biopharm Drug Dispos 21: 321-326.
40. Venkatesh S, Lipper RA (2000) Role of the development scientist in compound
lead selection and optimisation. J Pharm Sci 89: 145-154.
41. Hwang SS, Gorsline JJ, Louie J, Dye D, Guinta D, et al. (1995) in vitro and in
vivo evaluation of a once-daily controlled release pseudoephedrine product. J
Clin Pharmacol 35: 259-267.
42. FDA (1997) Guidance for Industry: SUPAC-MR: Modified release solid oral
dosage forms: scale-up and post-approval changes: chemistry, manufacturing
and controls, in vitro dissolution testing, and in vivo bioequivalence
documentation.
43. Young D, Chilukuri D, Becker R, Bigora S, Farrell C, et al. (2002) Approaches
to developing a Level-A IVIVC for injectable dosage forms. AAPS Pharm Sci
4: M1357.
This article was originally published in a special issue, BA/BE: LC-MS
handled by Editor(s). Dr. Bhaswat Chakraborty, Cadila Pharmaceuticals Ltd,
India

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