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A seminar on Factor affecting IVIVC Guided by: Presented by: Dr.Manish.P.Patel Patel Jignesh.P Head of Department M.pharm-1sem Department of pharmaceutics M.pharm, Nootan Pharmacy college Visnagar. 1/37
The therapeutic efficacy of a pharmaceutical formulation is governed by factors related to:
in vitro dissolution characteristics of the drug &
its 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.”
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.
FDA had defined IVIVC as “A predictive mathematical model describing relationship between in-vitro property of a dosage form and in-vivo response.”
In-vitro properties are rate or extent of drug released under a given set of conditions. In-vivo properties are plasma drug conc. expressed in terms of Cmax, AUC.
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.
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7/37 To explore the relationship To assist quality control for certain SUPAC. Research tool for Formulation Screening To support biowaivers for bioequivalence testing Development of drug delivery systems. To set the dissolution specifications As a surrogate of in vivo bioavailability To reduce the number of human studies IMPORTANCE OF IVIVC
Pharmacological correlations based on clinical observations.
Semi quantitative correlations based on the drug blood levels or urinary excretion data.
Quantitative correlations arising from absorption kinetics and calculation of in vivo dissolution rate and absorption rate constants.
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Factors affecting development of a predictable IVIVC 9/37 DISSOLUTION METHOD PYSICOCHEMICAL METHOD COMPOSITION COMPLEXITY
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Mean Residence Time: MRT = AUMC / AUC where, AUMC = Area under first moment Curve (Concentration*time Vs time) AUC = Area under zero moment curve (Concentration Vs time) Mean Absorption Time: MAT = MRT oral – MRT i.v. Mean In-vivo Dissolution Time: MDT solid = MRT solid – MRT solution Percent Prediction Error: % PE = [(Observed value – Predicted value) / Observed value] x 100 FEW DEFINITIONS 10/37
Usually Correlations are linear, and no formal guidance on the non-linear IVIVC.
The data treatment involves a two stage Deconvolution Method.
Estimation of the in vivo absorption profile using Wagner-Nelson or Loo-Riegelman method
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.
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, T 1/2 or AUC).
Level C correlations can be useful in the early stages of formulation development when pilot formulations are being selected.
Lowest correlation level
Does not reflect a complete shape of plasma concentration time curve.
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.
15/37 C max , T max , K a , Time to have 10, 50, 90% absorbed, AUC Disintegration time, Time to have 10, 50, 90% Dissolved, Dissolution rate, Dissolution efficiency C Statistical Moment: MRT, MAT Statistical Moment: MDT B Input (absorption) curves Dissolution curve A In vivo In vitro Level
Pearson product moment correlation coefficient , quantify strength of relationship between x & y. r (-1 to +1)
Rank order correlation : (Spearman rank correlation, r s ) 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.
16/37 No Linear Relationship 0 Perfect Negative -1 Perfect Positive +1 Linear relationship Correlation (r) between variables
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17/37 Correlation Methods SIMPLE POINT TYPE COMPARISON OF PROFILES DIRECT DIFFERENTIAL EQUATION- BASED IVIVC
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.
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21/37 Limited or no IVIVC expected. Low Low IV Absorption/Permeability is rate determining and limited or no correlation with dissolution rate. Low High III IVIVC is expected if in-vitro dissolution rate is similar to in-vivo dissolution rate, unless dose is very high. High Low II IVIVC: if dissolution rate is slower than gastric emptying rate. Otherwise limited or no correlation required High High I IVIVC EXPECTATION PERMEABILITY SOLUBILITY CLASS
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.
[1] 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
= ( 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%.
[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.
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28/37 IVIVC – PARENTERAL DRUG DELIVERY DISSOLUTION SPECIFICATIONS FORMULATION ASSESSMENT EARLY STAGES OF DRUG DELIVERY TECHNOLOGY DEVELOPMENT FUTURE BIOWAIVERS APPLICATIONS OF IVIVC IN DRUG DELIVERY Potent Drugs & Chronic Therapy Limited volume Burst Release
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.
IVIVC: An Important Tool in the Development of Drug Delivery Systems; Gangadhar Sunkara, 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
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