In vitro in vivo correlation by Dr. Neeraj Mishra, ISFCP, Moga, Punjab

In vitro in vivo correlation by Dr. Neeraj Mishra, ISFCP, Moga, Punjab

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  IN VITRO INVIVO CORRELATION Presented by Dr. Neeraj Mishra Department of Pharmaceutics, PROFESSOR ISF College of Pharmacy, Moga, Punjab, 142001 Email:neerajdops@rediffmail.com
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  IN VITRO INVIVO CORRELATION 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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  In Vitro Studies 1.Quality control procedures 2. Tablet or Capsule disintegration 3. Instrumental methods of analysis 4. Dissolution Rate Test The rate of drug absorption Dissolution Profile Parameters In Vivo Performance Proper In-Vitro Dissolution Rate – Correlate the data with the bioavailability
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  In-Vivo Studies • Definition:In-vivo studies deals with the evolution of bioavailability and bio equivalence of pharmaceutical dosage forms using parameters like AUC,Cmax etc.. • PARAMETERS: 1.Drug concentration in plasma at each sampling time 2.Apparent rate constant for elimination 3.Biological half life 4. Urinary excretion rate and amount excreted in urine at infinity
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  Comparison methods The invitro dissolution is compared by three way 1. Simply positioning one curve (in-vitro dissolution curve) over the other (In-vivo input rate curve) 2. by determining intensity factor (I) (I) = (time for 50%absorption) / (time for 50%dissolution) This may also be quantified by defining the equation for each curve & comparing the Corresponding constant such as m & c Y (In-vivo absorbed) = m X(In vitro dissolved)+ c (‘m’ is the slope of the relationship, and ‘c’ is the intercept) 3. Plot the graph between fraction absorbed in vivo verses the fraction released in vitro. Simply positioning one curve over another:
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  LEVELS(METHODS)OF IN VITRO-IN VIVOCORRELATION 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.
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  Level In-Vitro In-Vivo ADissolution curve In put (Absorption) curve B Statistical Moment: MDT Statistical Moment: MRT, MAT Etc. C Disintegration time T10%, T50%, T90% Dissolved Dissolution rate Dissolution efficiency Cmax, Tmax, Ka, T10%, T50%, T90% Absorption AUC (Total or Cumulative)
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  Level A CORRELATION Itis 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. 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). 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
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  A successful IVIVCmodel can be developed if in vitro dissolution is the rate-limiting step in the sequence of events leading to appearance of the drug in the systemic circulation following oral or other routes of administration. Thus, the dissolution test can be utilized as a surrogate for bioequivalence studies (involving human subjects) if the developed IVIVC is predictive of in vivo performance of the product.
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  The main purposeto conduct a dissolution test is to establish a dissolution profile and then predict/determine a C-t profile from it to assess potential in vivo characteristics of the test product. Therefore, it can be said that in reality the purpose of commonly referred practices of IVIVC is to transfer a dissolution (in vitro) to a C-t (in vivo) profile, or simply in vitro-to-in vivo profiling. The mathematical technique to transfer in vitro profile to in vivo profile is known as convolution. Convolution is relatively simpler than de-convolution as the former can be applied using simple spreadsheet software, e.g., MS Excel.
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  Determining plasma bloodconcentrations (output function), if input function (dissolution results) is available, the procedure will be called convolution technique and inverse of it, that is obtaining input function (absorption/dissolution results) if output function (Plasma drug concentration) is provided, the procedure will be called deconvolution. There are computer software available which provide the capability of solving for a function when the others are available. However, the convolution approach could be simpler where use of commonly available spreadsheet software may also be used.
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  Deconvolution Prediction of plasmadrug concentrations Prediction using convolution integral: 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. C(t) = ᶘ0t C (t-u)X’vitro (u)du The function C 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.
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  Evaluating the Predictabilityof 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 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
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  INTERNAL PRADICTIBILITY :  Itis 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.
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  EXTERNAL PREDICTABILITY It isbased on how well the IVIVC predicts additional test data .it provides more comprehensive analysis of the predictability than internal one. This approach 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) 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
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  ADVANTAGE It reflects completeplasma 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
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  Formulation Filler Polymer(%) Mag. Strearate (%) Lubricant Blending time (min) Compression Force (Kg) Fast Lactose 15 1.0 2 400 Medium Lactose+ DCP 50:50 32.5 1.5 6 600 Slow DCP 50 2.0 2 800 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 CASE STUDY
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  Case Study contd… Step3:Determinethe f2 metric similarity for dissolution data. by this equation. F2 = 50 log{[1 + 1/n t=1 (Rt – Tt)2]-0.5 x 100} 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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  Case Study contd… 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. 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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  Time(h) Fast (F) Medium(M) Slow (S) FRD FRA FRD FRA FRD FRA 0.5 0.289 0.043 0.186 0.032 0.150 0.051 1.0 0.438 0.243 0.299 0.163 0.238 0.132 1.5 0.557 0.445 0.384 0.293 0.309 0.224 2.0 0.672 0.328 0.464 0.424 0.373 0.302 4.0 0.899 0.900 0.596 0.660 0.478 0.478 6.0 0.950 0.972 0.709 0.777 0.568 0.593 8.0 0.962 0.964 0.859 0.904 0.708 0.778 10.0 0.964 0.971 0.939 0.954 0.805 0.874 12.0 0.975 0.958 0.978 0.965 0.877 0.893 IVIVC Models (FRD & FRA) for F, M and S Metoprolol formulations FRD: Fraction Drug Dissolved; FRA: Fraction Drug Absorbed
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  IVIVC model predictability IVIVCmodel predictability was assessed by percent Cmax & AUC prediction errors. 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.
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  LEVEL B CORRELATION Itutilizes 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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  Mean Residence Time(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. Mean Dissolution Time (MDT) It represents the mean time for drug molecules to completely dissolve.
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  Limitation level B usesall 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.
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  LEVEL C CORRELATION Itis 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.
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  MULTIPLE LEVEL CCORRELATION 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.
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  LEVEL D CORRELATION LevelD 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.
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  Class Solubility PermeabilityIVIVC I High High Correlation (If dissolution is rate limited step) II Low High IVIVC Expected III High Low Little or no IVIVC IV Low Low Little or no IVIVC Bio-pharmaceutical drug classification and expected IVIVC for immediate release drug products
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  Class Solubility PermeabilityIVIVC Ia High & Site independent High & Site independent IVIVC Level ‘A’ Expected 1b High & Site independent Site dependent with narrow Abs window IVIVC Level ‘C’ Expected IIa Low & Site independent High & Site independent IVIVC Level ‘A’ Expected IIb Low & Site independent Site dependent with narrow Abs window Little or no IVIVC III High Low Little or no IVIVC IV Low Low Little or no IVIVC Va (Acidic) Variable Variable Little or no IVIVC Vb (Basic) Variable Variable IVIVC Level ‘A’ Expected Bio-pharmaceutical drug classification and expected IVIVC for Extended release drug products