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ivivc ivivc - A Tool for - A Tool for in vitroin vitro--in vivo in vivo Correlation Correlation Exploration with Exploration with RR

Speaker: Hsin-ya LeeSpeaker: Hsin-ya LeeAdvisors: Pao-chu Wu,Advisors: Pao-chu Wu, Yung-jin Lee

College of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan (R.O.C)

2008/08/14

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BackgroundBackground In vitro-in vivo correlation (IVIVC)

the correlation between in vitro drug dissolution and in vivo drug absorption

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Purpose of IVIVC 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).

The main purpose of an IVIVC model to utilize in vitro dissolution profiles as a surrogate for

in vivo bioequivalence and to support biowaivers Data analysis of IVIVC attracts attention from the

pharmaceutical industry.

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Purpose of our study

The purpose of this study is to develop an IVIVC tool (ivivc) in R.

ivivc in R is menu-driven package. The development of level A IVIVC model

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Frameworks of IVIVC in RFrameworks of IVIVC in R

Input/Edit In Vivo Absorption Data: IV, Oral solution or IR drug

Input/Edit In Vitro Dissolution Data and In Vivo absorption Data: ER drug with Different Release Rates

Develop an IVIVC Model: Fitting IV, Oral solution or IR drug

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Fitting IV, Oral solution or IR drug

PK parameters (kel and Vd) using PKfit Started with genetic algorithm (genoud is from

“rgenoud” package) fitting Nelder-Mead Simplex algorithm (optim) end with nls

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Frameworks of IVIVC in RFrameworks of IVIVC in R

Input/Edit In Vivo Absorption Data: IV, Oral solution or IR drug

Develop an IVIVC Model: Fitting IV, Oral solution or IR drug

Input/Edit In Vitro Dissolution Data and In Vivo absorption Data: ER drug with Different Release Rates

Input/Edit In Vivo Absorption Data: IV, Oral solution or IR drug

Input/Edit In Vitro Dissolution Data and In Vivo absorption Data: ER drug with Different Release Rates

Develop an IVIVC Model: Model Dependent Method

ER drug with Different Release Rates

Model Dependent Method: deconvolution The observed fraction of the drug absorbed is based

on the Wagner-Nelson method

observed drug

plasma concentration

(conc.obs)

estimated fraction of the drug absorbed

(Fab)

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Wagner-Nelson method

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IVIVC model IVIVC model

fraction of the drug absorbed vs. the drug dissolved the predicted fraction of the drug absorbed is

calculated from the observed fraction of the drug dissolved.

α and β are the intercept and slope of the regression line, α and β are the intercept and slope of the regression line, respectively.respectively.

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IVIVC modelIVIVC model

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the predicted fraction of the drug absorbed is then convolved to the predicted drug plasma concentrations

Convolution

Gohel M. and et al. http://www.pharmainfo.net/reviews/simplified-mathematical-approach-back-calculation-wagner-nelson-method

predicted fraction of the drug absorbed

(PredFab)

predicted drug plasma concentration

(conc.pred)

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Predicted drug plasma conc.Predicted drug plasma conc.

sciplot package

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Frameworks of IVIVC in RFrameworks of IVIVC in R

Input/Edit In Vivo Absorption Data: IV, Oral solution or IR drug

Develop an IVIVC Model: Fitting IV, Oral solution or IR drug

Input/Edit In Vitro Dissolution Data and In Vivo absorption Data: ER drug with Different Release Rates

Develop an IVIVC Model: Model Dependent Method

Input/Edit In Vivo Absorption Data: IV, Oral solution or IR drug

Input/Edit In Vitro Dissolution Data and In Vivo absorption Data: ER drug with Different Release Rates

Develop an IVIVC Model: Model Dependent Method

Evaluate an IVIVC model: Prediction Error

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Internal Validation of level A correlation

Predictability of a level A correlation estimating the percent prediction error (%PE)

between the observed and predicted drug plasma concentration profiles

pharmacokinetic parameters (Cmax, and the area under the curve from time zero to infinity, AUC∞).

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Limitation and Future worksLimitation and Future works

LimitationLimitation Model dependent method

One-compartment model: One-compartment model: Wagner-Nelson method

Future worksFuture works Model dependent method

Two-compartment model: Loo-Riegelman method Model independent method

Numerical deconvolution Differential-equation based IVIVC model

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AcknowledgmentAcknowledgment

Stephen D. Weigand (Departments of Biostatistics , Mayo Clinic Rochester, MN, USA): coding (by e-mail)

Henrique Dallazuanna (Curitiba-Paraná-Brasil): coding (by e-mail)

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More informationMore information Reference

1997. Guidance for industry, extended release oral dosage forms: Development, evaluation, and application of in vitro/ in vivo correlations.

Dutta S, Qiu Y, Samara E, Cao G, Granneman GR. 2005. J Pharm Sci 94(9):1949-1956.

Gohel M. , Delvadia RR, Parikh DC, Zinzuwadia MM, Soni CD, Sarvaiya KG, Joshi R and Dabhi AS. Simplified Mathematical Approach for Back Calculation in Wagner-Nelson Method. http://www.pharmainfo.net/reviews/simplified-mathematical-approach-back-calculation-wagner-nelson-method

Email Yung-Jin Lee : : pkpd.taiwan@gmail.compkpd.taiwan@gmail.com Hsin-Ya Lee: hsinyalee@gmail.com

Web http://pkpd.kmu.edu.tw/ivivc/

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Thanks for your attention!Thanks for your attention!