Views:

Category: Education

## Presentation Description

No description available.

## Presentation Transcript

### Under The Guidance: Dr.T.E.G.K .MURTHY :

Under The Guidance: Dr.T.E.G.K .MURTHY M.Pharm . PhD PRESENTED BY: G.RADHA IVIVC – Methods and applications in MR Product Development

### Slide 2:

In Vitro-In Vivo Correlation (IVIVC) Definition: A predictive mathematical model describing the relationship between an in vitro property of a dosage form (usually the rate or extent of drug release) and a relevant in vivo response (e.g. plasma drug concentrations or amount of drug absorbed).

### Slide 3:

Purpose of IVIVC and BCS : Reduction of regulatory burden:with IVIVC data we can exempt additional in vivo experiments, leading to • Time/Cost savings during product development • Scale-up and post approval changes[SUPAC] • In process optimization • Justification for “therapeutic” product quality • therapeutically meaningful release specifications • Less testing in humans.

### Slide 4:

Categories of In Vitro-In Vivo Correlations: Level A correlation : Functional relationship between In vitro dissolution and the In vivo input rate, correlation of both the p rofiles (linear or non-linear relationship). It is the highest level of correlation represents a point to point relation between invitro dissolution and invivo input rate(plasma conc. Vs time profile). At this level of correlation the invitro and invivo dissolution curves are directly superimposable . This correlation is usually estimated by a 2 methods : i ) Deconvolution [model independent]. ii) wagner -Nelson method[model dependent]

### Slide 5:

Deconvolution is a numerical method used to estimate the time course of drug input using a mathematical model based on the convolution integral. For example the absorption rate - time course ( rabs ) that results in plasma concentration (ct) may be estimated by solving the convolution integral equation for rabs . Where, cδ represents the concentration time profile resulting from an instantaneous absorption of a unit amount of drug which is typically from bolus intravenous injection or reference oral solution data. c(t)- Plasma concentration Vs time profile of the tested formulation. r abs - Input rate of the oral solid dosage form into the body. u – variable of integretion

### Slide 6:

Deconvolution methd requires no assumptions regarding the no. of compartments in the model or the kinetics of absorption, but requires data obtained after both oral and i.v administration in the same subject and assumes no differences in the P.K of drug distribution from one study to the other. Covolution and Deconvolution ; Convolution: Converting the fraction of drug absorbed (observed Fab ) into predicted plasma conc.( pred conc.) by using mathematical equation. Deconvolution : Converting the predicted plasma conc.( pred conc.) into predicted Fraction of drug absorbed( pred Fab ).

### Slide 7:

Evaluation of Predictability of IVIVC Estimation of the magnitude of the error in predicting the bioavailability from In vivo dissolution data Different approaches are acceptable: • Internal predictability (with the formulations used for the development of IVIVC) • External predictability (with the formulations not used for the development of IVIVC)

### Slide 8:

Acceptance Criteria: • ≤ 15% for absolute prediction error (%PE) of each formulation. • ≤ 10% for mean absolute prediction error (%PE ) across formulations Metrics to Evaluate Predictability of IVIVC Percent prediction error (%PE): For Cmax : {[ Cmax ( obs ) – Cmax ( pred )]/ Cmax ( obs )}*100 For AUC: {[AUC( obs ) – AUC( pred )]/AUC( obs ) }*100

### Slide 9:

Limitation of the Predictability Metrics • Metrics used to evaluate the predictability is described simply as the prediction error (%PE) for Cmax and AUC, i.e. predicted plasma profiles are reduced to only two PK Parameters • Cmax predicted with the IVIVC model represents the maximum of the mean plasma profile - but is compared with the mean Cmax observed calculated as the average of individual profiles (at different Tmax !) • Tmax is not included in predictability metrics

### Slide 10:

Weakness of the Predictability Metrics Cmax predicted ~ Cmax observed, but Tmax different

### Slide 11:

WAGNER - NELSON METHOD: According to Wagner-Nelson method, the cumulative fraction of drug absorbed at time t is calculated from the Equation as follows: F T = C T + K E ∫ ∞ T Cdt KE ∫ 0 T Cdt Where, C T is plasma concentration at time T and Ke is elimination rate constant. So a plot is obtained by taking % drug dissolved on X-axis and % unabsorbed on Y-axis the intercept obtained should be zero and slope 1 for linear relationship.

### Slide 12:

The apparent absorption rate constant (Ka) could be obtained from the least square fitted log-linear plot of the percent unabsorbed versus time. The absorption half-life (t1/2a) is calculated as 0.693 / Ka. The Loo- Riegelman method requires drug concentration time data after both oral and intravenous administration of the drug to the same subject and the fraction absorbed at any time t is given by: ( Xp ) T = amount of drug in peripheral compartment as a function of time after oral administration. Vc = apparent volume of central compartment.

### Slide 13:

Level B correlation : Based on principles of statistical moment analysis in which Mean Invitro d issolution time( MDT vitro ) correlated with Mean Invivo residence time( MRT vivo ) of the drug in the body. It is based on the assumption that movement of the individual drug molecules through the body compartment is governed by probability.

### Slide 14:

Mean residence time is the mean time that the drug resides in the body and is calculated by following equation: Mean in vivo dissolution time reflects the mean time for drug to dissolve in vivo from a solid dosage form and is estimated as:

### Slide 15:

Level C correlation : single point relationship between one dissolution parameter, (e.g. T50%, % dissolved in 4h) and one pharmacokinetic parameter ( e.g.AUC , Cmax ). Multiple-Level C correlation : Multiple level C corelation relates one or several pharmacokinetic (P.K) parameters of interest to the amount of drug dissolve at several time points of the dissolution profile. A relationship should be demonstrated at each time point at the same parameter such that the effect on the invivo performance of any change in dissolution can be assessed.

### Slide 16:

It should be based on atleast three dissolution time points covering the early, middle and later stages of the dissolution Level D correlation : Is a qualitative analysis and is not considered useful for regulatory purposes. It is not a formal correlation but serves as a aid in the development of a formulation of a processing procedure.

### Slide 17:

Systematic development of a correlation As development of an IVIVC is a dynamic process starting from the very early stages of development program through the final step, the following practical and detail approaches with industrial application is summarized as: Assumed IVIVR: Is essentially one that provides initial guidance and direction for the early formulation development activity. Retrospective IVIVR: Prototype formulation and pilot P.K are characterised . Prospective IVIVR: Formulation and process optimisation . This information can be used to establish appropriate in-process and finished product specification.

### Slide 19:

General considerations in development 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 the drug product under study. Mostly parallel studies or cross study analysis is performed. IVIVC usually developed in fasted state. When a drug is not tolerated in the fasted state, studies may be conducted in the fed state. The preferred dissolution apparatus is U.S.P I – IV. An aqueous medium either water or a buffered solution preferably not exceeding pH 6.8, is recommended as the initial medium for the development of IVIVC.

### Slide 20:

Main Applications of the IVIVC in Product Development • Evidence for biorelevant and/or discriminating dissolution method • Basis for biorelevant in vitro release specifications • Justification for a biowaiver - Wider than standard (±10%) in vitro release specifications - Line extensions (intermediate or lower strength)

### Slide 21:

Concept of mapping: Mapping is a process which relates Critical Manufacturing Variables (CMV), including formulation, processes, and equipment variables that can significantly affect drug release from the product, to a response surface derived from an in vitro dissolution curve and an in vivo bioavailability data.

### Slide 22:

Benefit from an IVIVC for the Registration of New Products • Modified release products: justification of release Specifications • Justification for discriminating in vitro test method • Modifications made during Scale-up • Line extensions (e.g. intermediate strength) • (Anticipation of later product changes )

### Slide 23:

Specification Setting for Modified Release Products (EMEA) • IVIVC established: Predicted profiles from upper and lower release limits are in 20% range of AUC • No IVIVC: Justify that side-batches are bioequivalent difference upper / lower limit: up to 20% • Specifications must be met during shelf-life of product

### Slide 24:

Phase New Active Compound Already Registered Compound Preclin . Classification according to BCS: • Solubility in the pH range 1.2 – 6.8 • Assessment of permeability If additional extended release form from registered normal product (or IVIVC exists already for normal formulation) • Dissolution profiles in pH range 1.2 – 6.8 I If dissolution rate determining for absorption: • Initial development of IVIVC from first in vivo data (Inclusion of rapid formulation in study for use as weighting function) • Development of IVIVC from in vivo data from at least two ER formulations (as well as IR formulation or solution) • If imitator product (generic): IVIVC study with 2 formulations as well as reference product and solution (weighting function ) Application/Request of a Biowaiver

### Slide 25:

II. • IVIVC study with „final“ formulation for discriminating dissolution method • Justification for discriminating dissolution method • Justification • IVIVC study with „final“ formulation for discriminating dissolution method III. IVIVC as base for biorelevant release specification setting • IVIVC as base for biorelevant release specification setting IV. (marketed) • IVIVC as justification for a biowaiver 1. of additional strengths or line extensions • IVIVC as justification for a biowaiver 1. of additional strengths or line extensions

### Slide 26:

Summary • IVIVCs cannot be generated for all drugs or formulations. But if the criteria are met, they are accepted by the authorities in USA and EU, Japan will probably also accept them as part of the ICH • IVIVC is a credible tool to select the discriminating in vitro test conditions and to set therapeutically meaningful in vitro release Specifications • Applied correctly, the IVIVC can save substantial costs and time when registering product changes ( biowaiver !)

### Slide 27:

Summary (cont’d) • Essential data (needed for a later IVIVC) ought to be generated in the regular development path of a compound. Following the BCS is helpful in this regard • Deconvolution /Convolution mathematics are more widely applicable for an IVIVC than methods based on PK models • It is advantageous to discuss the plan for filing an IVIVC - supported product change with the health authorities

### Slide 28:

REFERENCES : USP –NF 2004 ;USP XXVII, NF XXII , ASIAN EDITION In vitro-In vivo correlation : Theory to Applications J. Pharmacutical Science (www.cspscanada.org ) on 1-3-2011 Principles and Application of Biopharmacuetics and pharmacokinetics by Dr.H . P. TIPNIS, Dr . AMRITHA BAJAJ , First edition.