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correlation could be referred to as the relationship between appropriate in vitro release characteristics and in vivo bioavailability parameters DEVLOPING THE CORRELATION 1)Develop formulation with different release rate such as slow ,medium, fast or a single release rate if dissolution is condition independent. 2)Obtain in vitro dissolution profiles &derive in vitro dissolution parameters to be correlated. 3)obtain in vivo plasma conc. profiles by definitive BA studies of these formulation & estimate the in vivo absorption or dissolution time course by proper data treatment i.e. Wagner-nelson method.

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4) The in vitro dissolution is compared by three way time for 50%absorption I = ---------------------------- time for 50%dissolution This may also be quantified by defining the equation for each curve & comparing the Corresponding constant such as m & c Plot the graph between fraction absorbed in vivo verses the fraction released in vitro. Simply positioning one curve over another: The in vitro dissolution curve &the in vivo input rate curve are either directly super impossible or may be made by intensity factor (I)


LEVELS(METHODS)OF IN VITRO-IN VIVO CORRELATION The concept of correlation is based on its ability to reflect the entire plasmatic concentration time curve, obtained after the administration of the dosage form. It is the relationship between the entire in vitro dissolution curve to the entire curve of plasmatic levels of drug which defines the correlation. Five levels of correlation may be defined and classified in a descending order of usefulness.


Level A CORRELATION It is highest level of correlation It represents a relation point to point between the in vitro dissolution, and in vivo input rate (sometimes referred to as in vivo dissolution) of the drug from the dosage form. a this level of correlation, the in vitro and in vivo dissolution curves are directly super imposable, or may be superimposed using a constant (scale factor). A Level A correlation is usually estimated by a two-stage procedure: 1) deconvolution 2) followed by comparison of the fraction of drug absorbed to the fraction of drug dissolved


Prediction of plasma drug concentrations using mathematical model based on the convolution integral. For example, the following convolution integral equation may be used to predict the plasma concentration (c(t)) resulting from the absorption rate time course. The function represents the concentration time course that would result from the instantaneous absorption of a unit amount of drug and can be estimated from either i.v. bolus data, oral solution, suspension or rapidly releasing (in vivo) immediate release dosage forms. DECONVOLUTION

B. Evaluating the Predictability of a Level A Correlation : 

B. Evaluating the Predictability of a Level A Correlation the objective of developing an IVIVC is to establish a predictive mathematical model describing the relationship between an in vitro property and a relevant in vivo response, the proposed evaluation approaches focus on the estimation of predictive performance or, conversely, prediction error. IT is done by two methods 1)INTERNAL PREDICTIBILITY 2)EXTERNAL PREDICTIBILITY


INTERNAL PRADICTIBILITY IT is defined as predictability of data used for model development &is recommended for all IVIVC model To predict each formulation’s plasma concentration profile from each respective formulation’s dissolution data. This is performed for each formulation used to develop the IVIVC model. The predicted bioavailability is then compared to the observed bioavailability for each formulation and a determination of prediction error is made. %PE= <(observed value-predicted value) observed value>*100 Criteria: 1) Average absolute percent prediction error (% PE) of 10% or less for C max and AUC establishes the predictability of the IVIVC. In addition, the %PE for each formulation should not exceed 15%. 2) If these criteria are not met, that is, if the internal predictability of the IVIVC is inconclusive, evaluation of external predictability of the IVIVC should be performed as a final determination of the ability of the IVIVC to be used as a surrogate for bioequivalence.


EXTERNAL PREDICTABILITY: It is based on how well the IVIVC predicts additional test data .it prove ides more comprehensive analysis of the predictability than internal one. THIS approached is used when 1) Internal PE is not conclusive. 2) Only two formulation of diff. release rate are available. 3) Correction is developed for narrow therapeutic index drug. This involves using the IVIVC to predict the in vivo performance for a formulation with known bioavailability that was not used in developing the IVIVC model. Criteria: 1) % PE of 10% or less for C and AUC establishes the external max predictability of an IVIVC. 2) % PE between 10 - 20% indicates inconclusive predictability and the need for further study using additional data sets. Results of estimation of PE from all such data sets should be evaluated for consistency of predictability. 3)% PE greater than 20% generally indicates inadequate predictability, unless otherwise justified.


ADVANTAGE: It reflects complete plasma level curve. since a point to point correlation is developed using every plasma level & dissolution point. A change in manufacture site, method of manufacturing raw material supplies, minor formulation modification & even product strength using the same formulation can be justified without need of additional human study. the extremes of Q.C. standards can be justified by convolution or deconvolution procedure.


CASE STUDY: Develop level a IVIVC model & evaluate internal predictability for three different release rate (fast, medium, slow) metoprolol tablet. Step 1:Select at least two formulation with diff. release rate such as fast, medium & slow by this formulation. Step 2:determine the dissolution vs. time profile for each formulation. The USP apparatus 1, pH 6.8 at the speed of 150 rpm used as dissolution testing. fraction of metoprolol absorbed was determined for each time point & assume that 100mg dissolved represent complete drug release

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Step3:Determine the f2 metric similarity for dissolution data. by this equation. the observed f2 for each pair of dissolution was less than 50 f2:FS=30.9,MS=39.3 ,FM=46.0 Step4: Conduct a bioavailability and determine plasma drug conc. vs. time profile for the ER tablets as well as reference solution. STEP5:Determine fraction of drug absorbed (FRA) -as the pharmacokinetic of metoprolol followed a one compartment model, wagner - nelson method used for determine FRA.

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Step6:Plot the fraction absorbed (FRA) vs. fraction dissolved (FRD) for each formulation separately. -the plot provides basic information of the relationship (i.e. linear, non linear) between two variables. -The regression line should be significant (i.e. p<0.05) &the slope should not be significant different from 1.

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Step7:Determine how well the correlation predicts the plasma conc. vs. time profile. The estimated plasma profile was estimated using Deconvolution technique.

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IVIVC model predictability was assessed by percent C max & AUC prediction errors.

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Based on FDA guidance, the correlation is valid if the average PE absolute across formulation is <10%for C max & AUC &the prediction error for any formulation is <15% for C max & AUC. So IVIVC was valid & can be used to predict the in vivo behavior of metoprolol ER formulation.


LEVEL B CORRELATION: It utilizes the principle of STATISTICAL MOMENT ANALYSIS in which the mean residence time (MRT) of the drug in the body is related to the mean dissolution time (MDT) in vitro. IT is based on the preliminary assumption that movement of the individual drug molecules through the body compartment is governed by probability. statistical moments are parameters that describes the characteristic of the time course of plasma conc. & urinary excretion rate that follow administration of a single dose of a drug.

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MRT: It is the first moment of the distribution. It is defined as the mean time for drug molecules to transit through the body.& involve any kinetic process. MDT: It represents the mean time for drug molecules to completely dissolve.

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Limitation: level B uses all the in vitro and in vivo data, but it is not considered a point to point correlation, because it does not reflect the actual plasma level curve, since a series of different in vivo curves may produce similar values of the mean residence time (MRT). It is not possible to consider only level B correlation to assess formulation changes, manufacturing site changes, excipients supplier changes, among others. The in vitro data of such correlation can not be used to obtain the extreme limits of the quality control standard.


CASE STUDY: Step1: Select at least two formulation with different release rates. Three different release rates of metoprolol IR formulation were developed. Step2:Determine the dissolution vs. time profile for each formulation. Dissolution time profile of metoprolol IR fast, moderate & slow releasing formulation are below.

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Step3: Conduct a bioavailability study & determine plasma drug conc. vs. time profile.

Step4: Determine the mean residence time for the dissoluti data (MDT) & the plasma drug conc. vs. time data (MRT) . The level B correlation (MDT&. MRT) data in table 5 : 

Step4: Determine the mean residence time for the dissoluti data (MDT) & the plasma drug conc. vs. time data (MRT) . The level B correlation (MDT&. MRT) data in table 5 plot of MDT &MRT are in plot 5 IN this plot linear regression line was observed. So the good correlation was obtain.


LEVEL C CORRELATION: IT is a single point correlation. This category relates a dissolution time point (t50%, t90%, etc) to a pharmacokinetic parameter such as AUC, C max or T max LIMITATION: it is a weakest level of correlation as partial relationship between absorption & dissolution established. since level C correlation does not utilize all the data, it can not reflect the complete plasma conc. time curve. APPLICABILITY: Since this type of correlation does not allow prediction of the actual performance of the in vivo product, it is useful only as a guide to the development of formulations or as a production quality control routine It can useful in the early stages of formulation development when pilot formulations are being selected. PREDICTIBILITY: the methods & criteria for assessing the predictability of level C correlation are same as those of level A correlation.


MULTIPLE LEVEL C CORRELATION: Multiple level C correlation relates one or several pharmacokinetic parameters of interest to the amount of drug dissolved at several time point of the dissolution profile. A relationship should be demonstrated 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. It should be based on at least three dissolution time point covering the early, middle & later stages of the dissolution profiles.


LEVEL D CORRELATION: Level D correlation is a rank order & qualitative analysis & is not consider useful for regulatory purpose. It is used in the development of a formulation or processing procedure.


GENERAL CONSIDERATION IN DEVLOPMENT OF IVIVC: Human data should be supplied for regulatory consideration of an IVIVC. Bioavailability studies for IVIVC development should be performed with enough subjects to characterize adequately the performance of the drug product under study. parallel studies or cross-study analyses is preferred. IVIVC are usually developed in the fasted state. When a drug is not tolerated in the fasted state, studies may be conducted in the fed state. Any in vitro dissolution method may be used to obtain the dissolution characteristics of the ER dosage form. The same system should be used for all formulations tested. The preferred dissolution apparatus is USP apparatus I (basket) or II (paddle), used at recognized rotation speeds (e.g., 100 rpm for the basket and 50-75 rpm for the paddle). An aqueous medium, either water or a buffered solution preferably not exceeding pH 6.8, is recommended as the initial medium for development of an IVIVC The dissolution profiles of at least 12 individual dosage units from each lot should be determined.


REFERENCES: The united states pharmacopoeia XXIII, NF XVIII, united states pharmacopoeial,Rockville,MD,1995 pg no,1924 M.Gibaldi & h. weintraub, J pharmaceutical science. Banakar u.v., pharmaceutical dissolution testing drugs the pharmaceutical Sci, vol. 49, marcel dekker, New york 1992,212-222,8(B)396

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