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On Modeling Methods and Predictability of In-Vitro-In-Vivo Correlation (IVIVC) of Oral Controlled Release Products Dr. Bhaswat S. Chakraborty Sr. Vice President, R&D, Cadila Pharmaceuticals Presented at BIOBIO 2010, Hyderabad, India, March 1-3, 2010

In vitro-in-vivo correlation

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Page 1: In vitro-in-vivo correlation

On Modeling Methods and Predictability of In-Vitro-In-Vivo Correlation (IVIVC)of Oral Controlled Release Products

Dr. Bhaswat S. ChakrabortySr. Vice President, R&D, Cadila Pharmaceuticals

Presented at BIOBIO 2010, Hyderabad, India, March 1-3, 2010

Page 2: In vitro-in-vivo correlation

Outline

• Relevance and definition of IVIVC

• Biopharmaceutics classification system (BCS)

• Levels of IVIVC

• Generation of in-vitro release profile

• In-vivo PK profile

• Generation of in-vivo release profile– Compartmental

– Linear Systems

– Other Methods

• Predictability Error

• Issues

• Conclusion

Page 3: In vitro-in-vivo correlation

Dissolution in CR Formulation Development

For Market

Retig et al. Diss Tech, Feb. 2008, 6-8

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Definition of IVIVC

• In-vitro-in-vivo correlations (IVIVC) are the predictive, mathematical models relating an in vitro property such as dissolution and an in vivo response, e.g., amount of drug absorbed, thus allowing an evaluation of the QC specifications, change in process, site, formulation and application for a biowaiver etc.

• Valid in vitro and in vivo methods valid IVIVC

Page 5: In vitro-in-vivo correlation

Biopharmaceutics Classification System (BCS)

Amidon et al. (1995), Pharm Res, 12, 413-420

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Levels of IVIVC• Level A – point-point; first

deconvolution to get in vivo %drug absorbed, then compare with %dissolved

• Level B – Statistical moments; MRT or MDT in vivo vs. MDT in vitro

• Level C – single point; PK parameter vs. %dissolved

Level A

Level B

Level ALevel C

Malinowski and Marroum, Encyclopedia of Contr. Drug Deliv.

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BCS Class PK Data IVIVR

API –Physicochemi-cal Properties

Scale factor

Dosage Form Properties

BioreleventDissolution

Computer Modeling Using Convolution including Transporters, PK Models, and PK Parameters, API properties or Drug Release Data

IVIVC

1

2

3

Overall Approach

Wang et al (2009) Diss Tech, 8, 6-12

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Generation of In-Vitro Release Profile

• USP apparatus 1 (basket, 100 rpm) or 2 (paddle, 50&75 rpm)

• Aqueous dissolution medium, 900 ml– pH 1-1.5, 4-4.5, 6-6.5 & 7-7.5 at 370C

– A surfactant may be required

• In-vitro food effect– Rotating dialysis cell method

– Effects of oils, enzymes and pH

Page 9: In vitro-in-vivo correlation

Dissolution Specifications

• Without IVIVC– ± 10% of the label claim from mean dissolution profile of the bio or

clinical batch

– Can be >10% but range not >25% in certain cases

• With IVIVC– All batches should have dissolution profiles with upper and lower

predicted bioequivalence

• Proper or Biorelevant Dissolution conditions– Consider medium, volume, duration, apparatus (hydrodynamics)

– pH 1 – 7.4

– Predictive of bioavailability• Similar conditions, similar dissolution and similar bioavailability

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Mean Doxazocin Concentrations from CR Formulations; n = 24

2mg fasted SD

8mg fasted SD

8mg fed SD

Chung et al. Br J Clin Pharmacol. (1999) 48, 678–687.

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Oral CR of Diltiazem with a Clinically Proven IR (first market entry)

Single Dose Fasting

Steady State

Malinowski and Marroum, Encyclopedia of Contr. Drug Deliv.

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Limits to Oral Drug AbsorptionRate-limiting

Steps

Conditions Comments

Dissolution limiting Tdiss > 199 min

Peff > 2 10-4 cm/sec

Dabs >> Dose

The absolute amount of absorbed drug increases with the increased dose.

Permeability limiting

Tdiss < 50 min

Peff < 2 10-4 cm/sec

Dabs >> Dose

The absolute amount of absorbed drug increases with the increased dose.

Solubility

limiting

Tdiss < 50 min

Peff > 2 10-4 cm/sec

Dabs < Dose

The absolute amount of absorbed drug does not increase with the increased dose.

(Yu, Pharm. Res. 16:1884-1888 (1999))

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Generation of In-Vivo Release Profile

• Compartmental Models–Wagner-Nelson

– Loo-Riegelman

• Linear Systems Models– Deconvolution

– Convolution

• Mathematically they all yield the same result

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Wagner Nelson (1 compartment)

Page 15: In vitro-in-vivo correlation

Loo-Riegelman (2 Compartments)

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Convolution

Where, C(t) = Plasma drug concentrations after oral doseCδ(t) = Plasma concentrations after an IV dose or a dose of oral solution

Upon taking the derivative of C(t) wrt time:

When Cδ(0) = 0

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Deconvolution

Page 18: In vitro-in-vivo correlation

Other Methods of Generating In-Vivo Release Profiles

• Macroscopic Mass Balance

• Where An is absorption number and Cb* is the lumen drug concentration

• Inverse Gaussian

Where MIT is mean input time and CV2I is a normalized variance

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Systemic Drug Absorption: Carbamazepine CR 15N Stable Isotope Study

Wilding et al. Br J Clin Pharmac (1991), 32, 573-579

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Systemic Drug Absorption:

Carbamazepine CR 15N Stable Isotope Study

Wilding et al. Br J Clin Pharmac (1991), 32, 573-579

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IVIVC Model Predictability

• PE% Cmax

Cmax (pred) – Cmax (obs)

Cmax (obs)

• PE% AUC

AUCmax (pred) – AUCmax (obs)

AUCmax (obs)

Page 22: In vitro-in-vivo correlation

IVIVC Model Predictability(Weak acid; highly lipophilic; bioavailability 60-70%)

Lobenberg R. www.aapspharmaceutica.com/meetings/files/126/lobenberg.pdf

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IVIVC Bench Issues

• Reliable and biorelevant dissolution method and apparatus suitability– Qualification and calibration of equipment, sink conditions

– Ability to discriminate non-BE lots

– Apparatus and media for continuous IVIVC (minimum 3 lots) and tuning with gi conditions

• Accurate deconvolution of the plasma concentration-time profile– e.g., %absorbed in-vivo may be reflective of processes other than

release; absorption rate limitation is common for CR products

• Dissolution Specifications – Based on biological findings rather than pharmacopeial or mechanistic

Page 24: In vitro-in-vivo correlation

IVIVC Modeling Issues

• Intra- and Inter-subject variation– High variations can distort the mean data and in turn the

deconvolution– Enterohepatic recycling or second peak– Reproducibility of reference profiles

• Modeling– Smoothness of input and response functions– Stability of numerical methods– Jumps in input rate functions, e.g., delayed release or

gastric emptying– Statistical properties of the models

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Conclusions

• Biorelevant and reliable dissolution profiles can predict the in-vivo absorption of drugs from CR formulations

• Batches with similar dissolution will be BE and dissimilar dissolution will be non-BE

• Several methods exist for estimating in-vivo absorption– Mainly mass balance (compartmental) and superposition (convolution)

• Level A (point-to-point) or B (mean dissolution times) correlation can be obtained for BCS class 1 or 2 drugs

• At least 3 lots (desirable, fast and slow) must be established with IVIVC and proper reference

• IVIVC is useful in– QBD, SUPAC and biowaivers…

• Both practical and modeling issues must be addressed

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Thank you very much