in vivo in vitro

Overview On In
Vitro/ In Vivo
Correlations-IVIVCs
Submissiondate:8/24/2014

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Submitted By
Registration No Name Email adress
14107030 (GPL) Sal SabilSohani salsabilsohani@gmail.com
14107021 RubelRanaBabu rubelranababu007@gmail.com
14107022 Imran Al Mamun Imran- Al –Mamun@yahoo.com
14107023 Muhammad NazmulHasan nazmuluap@yahoo.com
14107024 MdMamunSuzon Suzon2mamun@gmail.com
14107025 AnannajitDebnath ananna_ph@yahoo.com
14107026 Asif Iqbal asif2863@gmail.com
14107027 ZianurKadriShayer Shayer103504@gmail.com
14107028 Syed Tanvir Siddiqee syedtanvirsiddiqee@yahoo.com
14107029 AfrojaAkther afroja_akth@yahoo.com
Submitted To
Dr. Md. Selim Reza
Professor & Chairman
Department Of Pharmaceutical Technology
Faculty Of Pharmacy
University Of Dhaka

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Overview On In Vitro/In Vivo Correlations (IVIVCs)
Index
SL
No
Topics Pages
1 Introduction 4
2 What Is IVIVC 4 - 5
3 Why To Go For IVIVCs 5
4 Importance Of IVIVCs 5
5 Establishing In vitro/In Vivo correlations 6
6 Criteria For IVIVCs 6
7 Objective Of IVIVCs 6 - 7
8 Purposes Of IVIVCs 7
9 Need For IVIVC 7
10 Factors Affecting Development Of A Predictable
IVIVC
8
11 Types of correlation 8 - 9
12 Systematic Development Of A Correlation 9 - 12
13 Important Considerations In Developing A
Correlation
13
14 Levels Of Correlations 14 - 18
15 Correlation Methods 18 - 20
16 Stages Of IVIVC Model 20 - 23
17 A case study 24-26
18 What’s In Store For The Future 26
19 Applications Of IVIVC 27 - 29
20 Conclusion 29
21 References 30 - 31

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INTRODUCTION
The therapeutic efficacy of a pharmaceutical formulation is governed by factors
related to:
 in vitro dissolution characteristics of the drug &
 It’s in vivo bioavailability.
This inherent interdependency within the drug-patient biosystem is the major
concern that underlines the importance of in vitro/in vivo correlation studies.
 Bioavailability implications of dissolution should never be accepted on faith,
rather it has to be proved through carefully designed in vitro-in vivo
correlation studies.
 The need for such comparisons has been recognized since early 1960’s & the
regulations on bioavailability and bioequivalence were issued by the FDA in
1977.
 Long back, Wagner had stated that,
“Future research in dissolution rate should be directed mainly towards
establishing correlation of in-vitro data with in-vivo data.”
WHAT IS IVIVCs
In IVIVC, "C" denotes "Correlation", which means "the degree of relationship
between two variables". This term does not limit a relationship to only the
linear type, but allows for non-linear relationships as well.
Conceptually, IVIVC describes a relationship between the in vitro dissolution
/ release versus the in vivo absorption.
USP definition
• “The establishment of rational relationship b/w a biological property or a
parameter derived from a biological property produced by a dosage form
and physicochemical property of same dosage form”

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• Conceptually, IVIVC describes a relationship between the in vitro
dissolution / release versus the in vivo absorption.
FDA definition
• “A predictive mathematical model describing relationship between in-vitro
property of a dosage form and in-vivo response.”
WHY TO GO FOR IVIVCs
 Theoretically worthwhile, but Clinical approach is a poor tool for
accurate measurement of bioavailability.
 Determination of drug level at the site of administration.
 Urinary excretion analysis of drug is meaningful for establishing IVIVC
but complicated pharmacokinetic considerations.
 Thus it is generally assumed that blood (serum/plasma) level
measurements give a better assessment of bioavailability and
bioequivalence.
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 scaleup 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.

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IMPORTANCE OF IVIVCs
Establishing in vitro-in vivo correlations
• Simply a mathematical model describing the relationship b/w in vitro and in
vivo properties of drug.
• In vitro –in vivo correlation can be achieved using
 Pharmacological correlation
“Based on clinical observations”
 Semi quantitative correlation
“Based on the drug blood levels or urinary excretion data”
 Quantitative correlation
IMPORTANCE
OF
IVIVC
To reduce
the number of
human studies
As a surrogate
of in vivo
bioavailability
To set the
dissolution
specifications
Development of
drug delivery
systems.
To support
biow aivers
for
bioequivalence
testing
Research tool
for
Formulation
Screening
To assist
quality
control
for certain
SUPAC.
To explore the
relationship

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“Arising from absorption kinetics and calculation of in vivo dissolution rate and
absorption rate constants”
CRITERIA FOR IVIVCs
• Successful IVIVC can be developed when in-vitro dissolution is rate limiting
step in absorption and appearance of drug in in- vivo circulation
following oral or other routes of administration.
• These studies are to be conducted during the early stages of drug
product development in order to select the most effective
formulation and to establish appropriate dosage regimen.
• The release- controlling excipients in the formulations should either be
identical or very similar.
OBJECTIVE OF IVIVCs
• To reduce the number of human studies during the formulation development
• To serve as a surrogate for in vivo bioavailability
• To support biowaivers.
• To validates the use of dissolution methods and specification settings(This is
because the IVIVC includes in vivo relevance to in vitro dissolution
specifications).
• To assist quality control for certain scale-up and post-approval changes
(SUPAC).
• Due to all above objective, such IVIVC leads to
1. Shortens the drug development period,
2. Economizesthe resources and
3. Leads to improved product quality.
Purposes of IVIVCs
The optimization of formulations may require changes in the composition,
manufacturingprocess, equipment, and batch sizes and in order to prove the
validity of a new formulation,which is bioequivalent with a target
formulation, a considerable amount of efforts is required tostudy

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bioequivalence (BE)/bioavailability (BA). The main purpose of an IVIVC
model is toutilizein vitro dissolution profiles as a surrogate for in vivo
bioequivalence and to supportbio-waivers and data analysis of IVIVC attracts
attention from the pharmaceutical industry andalso to predict the entire in
vivo time course from the in vitro
data.
NEED FOR IVIVC
• Theoretically, correlation of in-vivo absorption rate with clinical response will
be the most worthwhile approach. But, clinical approach is a poor tool for
accurate measurement of bioavailability.
• Determination of drug level at the site of administration would be next logical
approach. But again, with some exceptions, it‘s impossible.
• Urinary excretion analysis of drug is meaningful for establishing IVIVC but
due to complicated pharmacokinetic considerations, such as drug metabolism
and urine collection problems.thus it is generally assumed that
blood(serum/plasma) level measurements give a better assessment of
bioavailability and bioequivalence.
• This relationship is an important item of research in the development of drug
delivery systems.
• A good IVIVC model can explore the relationship between in vitro dissolution
or release and in vivo absorption profiles.
• The IVIVC model relationship facilities the rational development and
evaluation of immediate or extended release dosage form as a tool for
formulation screening ,in setting dissolution specifications and as a surrogate
for bioequivalence testing.
FACTORS AFFECTING DEVELOPMENT OF A PREDICTABLE
IVIVC
1. Complexity of the delivery system.
2. Composition of formulation.
3. Method of manufacture.
4. Physicochemical properties.

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5. Dissolution method.
Types of correlation
• Quantitative correlation:
In vivo parameter-y, in vitro-x. y= mx +c
Pearson product moment correlation coefficient, quantify strength of
relationship between x & y. r (-1 to +1)
Correlation (r) between
variables
Linear relationship
+1 Perfect Positive
-1 Perfect Negative
0 No Linear
Relationship
• Rank order correlation: (Spearman rank correlation, rs) Values of
the two variables are ranked in ascending or descending order. Rank
order correlations are qualitative and are not considered useful for
regulatory purposes.
SYSTEMATIC DEVELOPMENT OF A CORRELATION
Any well designed and scientifically sound approach would be acceptable for
establishment of an IVIV correlation (2). As the development of an IVIVC is
COMPLEXITY
COMPOSITION
METHOD
PYSICOCHEMICAL
DISSOLUTION
METHOD

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a dynamic process starting from the very early stages of development
program through the final step, the following practical and detailed approach
with industrial application is summarized from reference number 5 without
modifications.
"To understand how an IVIVR is used 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
(Fig. 1). An assumed IVIVR is essentially one that provides the initial
guidance and direction for the early formulation development activity. Thus,
during stage 1 and with a particular product concept in mind, 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 cycle and in vivo characterization and, of course, extensive in vitro
testing is often developed what can be referred to asretrospective IVIVR.
With a defined formulation that meets the in vivo specification, Stage 2
commences. At this stage based on a greater understanding and
appreciation of defined formulation and its characteristics, a prospective
IVIVR is established through a well defined prospective IVIVR study. Once
the IVIVR is established and defined it can be then used to guide the final
cycle of formulation and process optimization leading into Stage 3 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 IVIVR 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
IVIVR".
"Stage 1: To undertake the development of an oral extended-release
product, stage 1 targets first must be defined. The target in vivo profile
needs to be first established, based on, if possible,
pharmacokinetic/pharmacodynamic models. Clearly, as described in the
pioneering work of Amidon in relation to the original biopharmaceutic drug
classification and the work of Corrigan relating to extended release product,
characterizing the permeability properties of a drug substance is a key
element both in establishing the initial feasibility of any formulation program
and in the subsequent interpretation of the observed in vivo absorption
characteristics of a given dosage form. The physicochemical characteristics
of the drug substance itself, in the context of how these affect the
formulation approach and in the context of relevance to dissolution at distal

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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. 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. The prototype formulation program itself is normally
initiated with some knowledge or expectation of what technologies and/or
mechanism of release are particularly suited to meet the desired targets.
This work is usually done at a laboratory level of manufacture with the
simplest dissolution methodology that seems appropriate. Prototypes that
meet the target in vitro profile are then selected involving one or, very
often, more than one technology or formulation approach. At least one, but
usually more than one prototype within each technology or formulation
approach is tested. More extended in vitro characterization, which looks at
the robustness of these prototypes across dissolution conditions such as pH,
medium, agitation speed and apparatus type, is routine at this point.
Certainly, stage 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. The results of this pilot
PK study provide the basis for establishing what has been referred to as a
retrospective IVIVR. In other words, a number of different prototypes with
some level of variation in release rate have now been characterized both in
vitro and in vivo. This information first allows a reality check on both the in
vivo and assumed IVIVR, either matching expectation or often causing a
fundamental shift in the assumed IVIVR. After the results of the in vivo
study are known, there is often a phase of significant revision of the in vitro
methods, sometimes driven by the need to detect an in vitro difference that
was observed in vivo but that had not been detected using the original in
vitro methods. This work sometimes results in revised in vitro targets and
reformulation strategy and the same cycle of activity again".
"Stage 2: By this stage of the development process, a defined formulation
that meets the in vivo targets has been achieved. The aim is to progress
through the normal formulation process optimization steps ultimately into
scale-up, registration, and approval. In stage 2, a defined formulation and
ideally a good understanding of the mechanism of release of this formulation
has been established. Based on this a priori understanding, and from a sort
of retrospective data generated from stage 1, an empirical basis exist for
determining the primary formulation related rate controlling variables. For
extended-release products, this a priori understanding is usually more
obvious than might be the case for immediate-release products. Based on
this information, a number of products with different release rates are

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usually manufactured by varying the primary rate controlling variable but
within the same qualitative formulation. Extensive in vitro characterization is
again performed across pH, media and apparatus, but the stage 1 work is
also taken into account. This leads to execution of a prospective IVIVR
study. The IVIVR 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 IVIVR. This ideally is a level A IVIVC
but, in particular, multiple-level C IVIVC continues to be both an acceptable
and useful IVIVR. 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.
Fig. 1: The product development process for extended-release products
(from reference 5 with permission).

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Once the IVIVR is established, it is routinely used in the completion of the
formulation/process optimization program using statistically based
experimental design studies looking at critical formulation and process
variables and their interactions. By now with a correlated in vitro method,
the robustness of the formulation and process can be established. This
information can also be used to establish appropriate in-process and
finished-product specification, of course, the appropriate targets for scale-
up". Development of in vitro in vivo correlation and validation using in vitro
dissolution and in vivo time course is also illustrated in Figure 2.

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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
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 nonnarrow
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% for absolute prediction error (%P.E.) of each formulation. 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 ( )%Prediction error (P.E.)= 100

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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 toolfor 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.
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.

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IMPORTANT CONSIDERATIONS IN DEVELOPING A
CORRELATION
When the dissolution is not influenced by factors such as pH, surfactants,
osmotic pressure, mixing intensity, enzyme, ionic strength, a set of
dissolution data obtained from one formulation is correlated with a
deconvoluted plasma concentration-time data set . To demonstrate a
correlation, fraction absorbed in vivo should be plotted against the fraction
released in vitro. If this relationship becomes linear with a slope of 1, then
curves are superimposable, and there is a 1:1 relationship which is defined
as point-to-point or level A correlation. Under these circumstances, the
correlation is considered general and could be extrapolated within a
reasonable range for that formulation of the active drug entity.
In a linear correlation, the in vitro dissolution and in vivo input curves may
be directly superimposable or may be made to be superimposable by the use
of appropriate scaling factor (time corrections) (2, 3). Time scaling factor
should be the same for all formulations and different time scales for each
formulation indicate absence of an IVIVC (3). Non-linear correlation may
also be appropriate.
In cases where, the dissolution rate depends on the experimental factors
mentioned above, the deconvoluted plasma concentration-time curves
constructed following administration of batches of product with different
dissolution rates (at least two formulations having significantly different
behavior) are correlated with dissolution data obtained under the same
dissolution condition. If there is no one-to-one correlation other levels of
correlation could be evaluated.
If one or more of the formulations (highest or lowest release rate
formulations) may not illustrate the same relationship between in vitro
performance and in vivo profiles compared with the other formulations, the
correlation is still valid within the range of release rates covered by the
remaining formulations .
The in vitro dissolution methodology should be able to adequately
discriminate between the study formulations. Once a system with most

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suitable discrimination is developed, dissolution conditions should be the
same for all formulations tested in the biostudy for development of the
correlation .
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 .
An established correlation is valid only for a specific type of pharmaceutical
dosage form (tablets, gelatin capsules, etc.) with a particular release
mechanism (matrix, osmotic system, etc.) and particular main excipients
and additives. The correlation is true and predictive only if modifications of
this dosage form remain within certain limits, consistent with the release
mechanism and excipients involved in it .
Extrapolation of IVIVC established in healthy subjects to patients has to be
taken into account. Drugs are often taken just before, with or after meal. All
these factors may increase variability. A posterior correlation might be
established using the patients' data only to increase the knowledge of the
drug.
The release rates, as measured by percent dissolved, for each formulation
studied, should differ adequately (e.g., by 10%). This should result in vivo
profiles that show a comparable difference, for example, a 10% difference in
the pharmacokinetic parameters of interest (Cmax or AUC) between each
formulation .
LEVELS OF CORRELATION
There are five levels of IVIVC that have been described in the FDA guidance,
which include
1. LEVEL A CORRELATION
2. LEVEL B CORRELATION

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3. LEVEL C CORRELATION
4. MULTIPLE LEVEL C CORRELATIONS
5. LEVEL D CORRELATION
1. LEVEL A CORRELATION
• Point-to-Point relationship
• Usually Correlations are linear, and no formal guidance on the non-
linear IVIVC.
• The data treatment involves a two stage Deconvolution Method.
1. Estimation of the in vivo absorption profile using Wagner-Nelson or
Loo-Riegelman method
2. Comparison of fraction of drug absorbed (Fa) and fraction of drug
dissolved (Fd) in-vitro to obtain a linear correlation.
• Formulations showing Level A correlation require no additional
human studies to justify change in manufacturing site, raw
material supplier or minor formulation changes.
• Most informative and very useful from a regulatory perspective.
• PURPOSE – DEFINE DIRECT RELATIONSHIP
Importants of level A correlation
• Providing process control and quality assurance
• Determining stable release characteristics of the product over time.
• facilitating certain regulatory determinations (e.g.,absence of effect of
minor formulation changes or of change in manufacturing site on
performance).
2. LEVEL B CORRELATION
• A predictive model for relationship between summary
parameters that characterize the in-vitro and in-vivo time course.

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• No point to point correlation
• It compares
1. MDT vitro to MDT vivo,
2. MDT vitro to MRT,
3. In-vitro Dissolution Rate Constant (kd) to Absorption Rate Constant
(ka).
• Comparison using Statistical moment analytical method.
• This type of correlation uses all of the in vitro and in vivo data.
• This is of limited interest and least useful for regulatory purposes
because more than one kind of plasma curve produces similar MRT.
3. LEVEL C CORRELATION
• Mathematical model of relationship between the amount of drug
dissolved in-vitro at a particular time and a summary pharmacokinetic
parameter that characterizes in-vivo time course. (e.g., Cmax, Tmax,
T1/2 or AUC).
• Single point correlation
• Level C correlations can be useful in the early stages of
formulation development when pilot formulations are being
selected.

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• Lowest correlation level
• Does not reflect a complete shape of plasma concentration time curve.
4. MULTIPLE LEVEL C CORRELATIONS
• It relates one or more pharmacokinetic parameters to the percent drug
dissolved at several time points of dissolution profile and thus may be
more useful.
• If a multiple Level C correlation is possible, then a Level A correlation
is also likely and is preferred
Level In vitro In vivo
A Dissolution curve Input (absorption) curves
B Statistical Moment: MDT Statistical Moment: MRT, MAT
C Disintegration time, Time to
have 10, 50, 90%
Dissolved, Dissolution rate,
Dissolution efficiency
C
max
, T
max
, K
a
, Time to have
10, 50, 90% absorbed, AUC
5. LEVEL D CORRELATION
• Level D correlation is a rank order and qualitative analysis and is not
considered useful for regulatory purposes. It is not a formal correlation
but serves as an aid in the development of a formulation or processing
procedure.

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NOTE:-
• Level B and C correlations can be useful in early formulation
development, including selecting the appropriate excipients, to
optimize manufacturing processes, for quality control
purposes, and to characterize the release patterns of newly
formulated immediate-release and modified-release products
relative to the reference.
Overall Approach
CORRELATION METHODS
There are three methods of IVIVC that have been described in the FDA
guidance, which include
1.SIMPLE POINT TYPE
2.COMPARISON OF PROFILES
3.DIRECT, DIFFERENTIAL EQUATION BASED

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1. SIMPLE POINT TYPE
• The percentage of drug dissolved in a given time or the
time taken for a certain percentage of drug to be
dissolved, is correlated with certain parameter of the
bioavailability.
2. COMPARISON OF PROFILES
• The entire in vivo response time profile can be correlated
to the entire dissolution rate time curve.
Some of the in vivo and in vitro parameters employed for correlation
are as follows
In vitro data In vivo data
1. Percent drug dissolution
profile
o Percent drug dissolved at time
t,
o Time taken for maximum
amount of drug to dissolve.
o Total amt. of drug dissolved.
o Time for a certain percentage
of drug to dissolve such as
t30% t50% t90%
1. Plasma conc. time profile
o Plasma concentration at time
t,
o Cmax,
o tmax,
o AUC
o
t
AUC
o
∞
o t30%, t50%, t90%
2. Kinetic parameters
o Dissolution rate constant
o Dissolution half life
2. Pharmacokinetic parameters
o Absorption & elimination rate
constant & half life
3. Percent drug dissolved time
profile
o Percent drug dissolved at
time t
3. Percent drug absorbed time
profile
4. Statistical moment analysis
o MDT
4. Statistical moment analysis
o MRT, MAT

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3.DIRECT, DIFFERENTIAL- EQUATION- BASED
in-vitro-in-vivo correlation (IVIVC) method = a novel method
▫ A new, differential equation-based in-vitro-in-vivo correlation
(IVIVC) method is proposed that directly relates the time-
profiles of in-vitro dissolution rates and in -vivo plasma
concentrations by using one- or multi- compartment
pharmacokinetic models and a corresponding system of
differential equations.
▫ The rate of in-vivo input is connected to the rate of in-vitro
dissolution through a general functional dependency that
allows for time scaling and time shifting. A multiplying factor
that accounts for the variability of absorption conditions as the
drug moves along is also incorporated.
▫ Two data sets incorporating slow-, medium-, and fast-release
formulations were used to test the applicability of the
method, and predictive powers were assessed with a leave-
oneformulation- out approach. All fitted parameters had
realistic values, and good or acceptable fits and predictions
were obtained as measured by plasma concentration mean
squared errors and percent AUC errors. Introduction of step-
down functions that account for the transit of the dosage
form past the intestinal sites of absorption proved useful.
▫ By avoiding the integral transforms used in the existing
deconvolution – or convolution based IVIVC models, the
present method can provide increased transparency, improved
performance, and greater modelling flexibility.
Convolution model
In the development of convolution model the drug concentrationtime 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

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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.
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

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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 deconvolutionbased approach, is not in widespread use.
Mathematically we can write the convolution as:
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.
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].

of 39
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,
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.
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 nonlinear 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:
For orally administered drugs, IVIVC is expected for highly permeable drugs,
or drugs under dissolution rate-limiting conditions, which is supported by the

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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.
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.

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STAGES OF IVIVC MODEL
1. Model Development
2. Model Validation
Model Development
• The principles of IVIVC model development have been successfully
applied to oral dosage forms.
• However, the rules for developing and validating IVIVC models for
novel and non-oral dosage forms/delivery systems (micro spheres,
implants, liposomes, etc) are still unclear today.
• For orally administered drugs, IVIVC is expected for highly permeable
drugs or drugs under dissolution rate-limiting conditions, which is
supported by BCS.
• For extended-release formulations following oral administration,
modified BCS containing the three classes (high aqueous solubility, low
aqueous solubility, and variable solubility) is proposed.
CLASS SOLUBILITY PERMEABILITY IVIVC EXPECTATION
I High High IVIVC: if dissolution rate is
slower than gastric emptying
rate.
Otherwise limited or no
correlation required
II Low High IVIVC is expected if 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

of 39
correlation with dissolution
rate.
IV Low Low Limited or no IVIVC expected.
• The most basic IVIVC models are expressed as a simple linear
equation (Equation 1) between the in vivo drug absorbed and in vitro
drug dissolved (released).
• In this equation, m is the slope of the relationship, and C is the
intercept.
• Ideally, m=1 and C=0, indicating a linear relationship.
However, depending on the nature of the modified-release system, some
data are better fitted using nonlinear models, such as Sigmoid, Higuchi, or
Hixson-Crowell.
• However, for dosage forms with complicated mechanisms of release
(longer duration), in vitro release may not be in the same time scale
as the in vivo release.
• Thus, in order to model such data, it is necessary to incorporate time-
shifting and time-scaling parameters within the model.
• This kind of data is routinely encountered in the development of
sustained-release dosage forms.
• In vivo release rate (X’vivo) can also be expressed as a function of in
vitro release rate (X’rel,vitro) with empirically selected parameters (a,
b), as shown in Eqn 2.

of 39
Determining the fraction of dose absorbed
o Model Dependent methods
• - Wagner Nelson Equation
• - Loo-Riegelman Method
o Model Independent methods
• - Deconvolution
Model Validation
[1] Internal Validation
(using data from the formulations used to build the model)
Internal validation serves the purpose of providing basis for the acceptability
of the model.
[2] External Validation
(using data obtained from a different (new) formulation)
External validation is superior and affords greater “confidence” in the model.
Internal Validation
] Using the IVIVC model, for each formulation, the relevant exposure
parameters (Cmax and AUC) are predicted and compared to the observed
values.
Prediction Error (%PE)
= ( Cmax observed – Cmax predicted) * 100
Cmax observed

of 39
= ( AUC observed – AUC predicted ) * 100
AUC observed
[2] The criteria set in the FDA guidance on IVIVC are: For Cmax and AUC,
the mean absolute % PE should not exceed 10%, and the prediction error
for individual formulations should not exceed 15%.
External Validation
[1] For a new formulation the relevant exposure parameters are predicted
using its in vitro dissolution profile and the IVIVC model and are compared
to the observed parameters.
[2] For Cmax and AUC, the % PE for the external validation formulation
should not exceed 10%. A prediction error of 10% to 20% indicates
inconclusive predictability and illustrates the need for further study using
additional data sets.
[3] For drugs with narrow therapeutic index, external validation is required
despite acceptable internal validation, whereas internal validation is usually
sufficient with non-narrow therapeutic index drugs.
A case study:an in vitro–in vivo correlation forextended
buspironeHCl release tablets
SevgiTakka, AdelSakr and Arthur Goldberg
Journal of Controlled Release
Volume 88, Issue 1 ,14 February 2003, Pages 147-157
In-vitro–in-vivo correlation
• The data generated in the bioavailability study were used to develop
the IVIVC.

of 39
• The percent of drug dissolved was determined using the
aforementioned dissolution testing method and the fraction of drug
absorbed was determined using the method of Wagner–Nelson.
• The dissolution rate constants were determined from % released vs.
the square root of time.
• Linear regression analysis was applied to the in-vitro–in-vivo
correlation plots and coefficient of determination (r2), slope and
intercept values were calculated.
• Level A in-vitro–in-vivo correlation was investigated using the percent
dissolved vs. the percent absorbed data for both the slow and fast
formulations, using both 0.1 M HCl and pH 6.8 phosphate buffer
dissolution media at both 50 and 100 rpm.
• A good linear regression relationship was observed between the
dissolution testing using pH 6.8 phosphate buffer at 50 rpm and the
percents absorbed for the combined data of the two dosage forms
• Another good linear regression relationship was observed between the
dissolution testing using 0.1 M HCl as the dissolution media at 50 rpm,
and the percents absorbed for the combined data of the two dosage
forms

of 39
• It is also observed that the in-vivo absorption rate constant (ka)
correlates well with the pH 6.8 phosphate buffer in-vitro dissolution
rate constant (kdiss), exhibiting a correlation coefficient of 0.9353.
• This was a better correlation than was obtained using the dissolution
rates in 0.1 M HCl, and therefore, pH 6.8 phosphate buffer was
selected as the dissolution media of choice.

of 39
Plot of in vitro dissolution rate (kdiss) versus in vivo absorption rate (ka)
constants (The zero–zero point is theoretical).
WHATS IN STORE FOR THE FUTURE
IVIVR (In vitro-in vivo relationship)
• One possible substitution for IVIVC is IVIVR, with "R" denoting
"relationship."
• Hence, IVIVR need not be limited to straight-line relationships, which
generally fails for IR products.
• This IVIVR analysis has been applied to several formulations of
metoprolol, piroxicam, and ranitidine.
• This indicated that one intent of IVIVR should be to learn about the
relative contribution of dissolution to a product's overall absorption
kinetics.

of 39
APPLICATIONS OF IVIVC
A. IVIVC IN DRUG DELIVERY
a. EARLY STAGES OF DRUG DELIVERY TECHNOLOGY
DEVELOPMENT
b. FORMULATION ASSESSMENT
c. DISSOLUTION SPECIFICATIONS
d. FUTURE BIOWAIVERS : For minor formulation and process
changes
e. IVIVC PARENTERAL DRUG DELIVERY :
CAUSES OF FAILURE OF PARENTERAL IVIVC…
I. Burst Release
II. Potent Drugs & Chronic Therapy
III. Limited volume of tissue fluids and Area of
absorption at the site of administration,
unlike following the oral route of
administration.
Therefore,it is very difficult to specify the in vitro dissolution
conditions that reflect the observed differences in the in vivo plasma
profiles corresponding to the in vitro release profiles.
B. NEW IVIVC APPLICATIONS
a. IVIVC FOR TRANSDERMAL ESTRADIOL SYSTEMS (Novel
pharmaceuticals)
b. WHY IVIVC FAIL FOR IMMEDIATE RELEASE DOSAGE FORM
c. DISSOLUTION SIMULATORS

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I. Gronings model
II. Sartorius dissolution simulator
III. Sartorius membrane filter solubility simulator
IV. Sartorius membrane filter absorption simulator
C. DISSOLUTION SIMULATORS
In order to enhance the capability of in vitro dissolution as a
predictor of the in vivo
behavior of dosage forms. But many of these attempts required highly
complex and
expensive apparatus with questionable advantage over traditional
systems.
1. Gronings model:-
• It consists of two interconnecting flow through cells and a reservoir
for the dissolution
medium, all contained in a constant temperature water bath.
• The dosage form disintegrates in the gastric part of the model and
some of the drug
particles are continuously pumped into the intestinal part.
• During an experiment the cells are rotated by a slow speed
electric motor. Unlike
conventional dissolution apparatus it gave good IVIVC.

of 39
Fig:GRONINGS MODEL
CONCLUSION
• Dissolution promotes good bioavailability but does not assure it.
• Meaningful IVIVC is possible only when dissolution rate dominates
membrane transport and transit rate, thus limiting the rate and/or
extent of absorption.
• In the era of tight budgets and increasing costs of drug development,
the most critical application of IVIVC with respect to cost savings is the
biowaiver, the avoidance of expensive clinical trials.
While the principles of IVIVC have been mostly applied to oral products,
there exists a need to develop methodologies and standards for non-oral
delivery systems

of 39
REFERENCES
• Guidance for Industry; Extended Release Oral Dosage
Forms: Development, Evaluation, and Application of In
Vitro/In Vivo Correlations.
www.fda.gov/cder/guidance/index.htm
• IVIVC: An Important Tool in the Development of Drug
Delivery Systems; GangadharSunkara, PhD, and Dakshina
M. Chilukuri, PhD.
http://www.drugdeliverytech.com/cgi-
bin/articles.cgi?idArticle=144
• Dissolution, Bioavailability and Bioequivalence by Hamed M.
Abdou, Mack Publishing House.
• IVIVC: An Important Tool in the Development of Drug
Delivery Systems; GangadharSunkara, PhD, and Dakshina
M. Chilukuri, PhD. http://www.drugdeliverytech.com/cgi-
bin/articles.cgi?idArticle=144
• Dissolution, Bioavailability and Bioequivalence by Hamed M.
Abdou, Mack Publishing House.
• Guidance for Industry; Extended Release Oral Dosage
Forms: Development, Evaluation, and Application of In
Vitro/In Vivo Correlations.
www.fda.gov/cder/guidance/index.htm
• IVIVC Vs IVIVR; James E. Polli, Ph.D.
http://www.dissolutiontech.com/DTresour/800Articles/800_
art1.html
• In Vitro–In Vivo Correlation: Importance of Dissolution in
IVIVC; J-M. Cardot, E. Beyssac, and M.Alric. Dissolution
Technologies | FEBRUARY 2007

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• IVIVC: Methods and Applications in Modified-Release Product
Development; HaraldRettig and Jana Mysicka. Dissolution
Technologies | FEBRUARY 2008.
• Journal Metadata Search: Pharmaceutical Press - Journal of
Pharmacy and Pharmacology55(4); 495 (2003)
• Pharmaceutical dissolution testing, Umesh V. Banakar
• Dissolution, bioavailability & bioequivalence, Hamed M.
Abdou.
• IVIVC Vs IVIVR; James E. Polli, Ph.D.
http://www.dissolutiontech.com/DTresour/800Articles/800_
art1.html
• IVIVC: Methods and Applications in Modified-Release Product
Development; HaraldRettig and Jana Mysicka. Dissolution
Technologies | FEBRUARY 2008.
• Journal Metadata Search: Pharmaceutical Press - Journal of
Pharmacy and Pharmacology55(4); 495 (2003)
• In Vitro–In Vivo Correlation: Importance of Dissolution in
IVIVC; J-M. Cardot, E. Beyssac, and M.Alric. Dissolution
Technologies | FEBRUARY 2007
• FDA guidance, CDER, US Department of Health and Human
Services, Food and Drug, Administration, Center for Drug
Evaluation and Research and Center for Veterinary Medicine
(CVM), Guidance for the Industry. Bioanalytical Method
Validation. May 2001. www.fda.gov/cder/guidance

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