Use of Mechanistic Population Based PBPK Models in the Establishment and Application of IVIVCs. Nikunjkumar Patel, Simcyp Limited

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1 Use of Mechanistic Population Based PBPK Models in the Establishment and Application of IVIVCs Nikunjkumar Patel, Simcyp Limited

2 IVIVC and Its Components CONVOLUTION VALIDATION DECONVOLUTION MODELS IVIVC

3 IVIVC Components: Deconvolution Methods Deconvolution in simplified terms is the method to estimate the rate of input in the system that produces the observed response (PK profile) Deconvolution Methods Model Dependent Methods Model Independent Methods Algebraic Equation Based Differential Equation Based Direct Numerical Deconvolution Numerical Deconvolution Through Convolution Wagner Nelson DE Compartmental Model Loo Riegelman Physiological (ADAM) Model

4 Deconvolution: Limitations of Conventional Methods Wagner Nelson and Loo-Riegelman Methods Assumes human body as one or two compartments Can not be used for nonlinear elimination Deconvolutes systemic input rate which is a composite function of dissolution + GI Transit + Permeation + First Pass Numerical Methods No physiological assumptions but mathematical assumptions: input site is the same for all formulations and input rate is constant (infusion) between two time points Numerical stability of calculations Deconvolutes systemic input rate which is a composite function of dissolution + GI Transit + Permeation + First Pass

5 Deconvolution: Physiologically Based Oral Absorption Model (ADAM) Gastric Emptying Luminal Transit in vivo dissolution is deconvoluted separately from GIT transit, permeation, gut wall metabolism and first pass extraction Jamei et al., AAPSJ, 2009 GUT WALL DISSOLVED DRUG FINE PARTICLES SOLID DOSAGE Degradation Metabolism Portal Vein LIVER Dissolution Precipitation Supersaturation Release Absorption Efflux/Influx PBPK DISTRIBUTION MODEL

6 Physiologically-based vs. Conventional IVIVC In vivo CR BCS I OR BCS II Low Extraction In vitro Conventional Deconvolution In vivo CR BCS I OR BCS II High Extraction In vitro Conventional Deconvolution CR BCS III OR BCS IV Low Extraction In vivo In vitro Conventional Deconvolution CR BCS III OR BCS IV High Extraction In vivo In vitro Conventional Deconvolution Differing Permeation/Metabolism in GIT In vivo In vitro Drugs with Enterohepatic Recirculation Conventional Deconvolution In vivo In vitro Conventional Deconvolution Dissolution Permeation Systemic Input

7 Physiologically-based IVIVC Case Study Using the ADAM model Metoprolol is a BCS Class I (High Solubility High Permeability) High First Pass Extraction Drug Relatively short half life and sufficient absorption from colon makes it suitable candidate for extended release formulation ER formulations of BCS Class I drug are Dissolution/Release Controlled Absorption ER BCS I OR BCS II High Extraction In vivo In vitro Conventional Deconvolution Conventional methods may require IVIVC function with lag time, sigmoid or power function to accommodate delay and slowness of in vivo availability as compared to dissolution

8 Model 1: Numerical Deconvolution with Oral Solution as UIR In vitro in vivo relationship In vitro In vivo USP II, ph 6.8, 50 RPM USP II, ph 6.8, 150 RPM The IVIVC was sigmoid or with lag time. FRA -> FRD graphs shown here used all three formulation data to establish IVIVC. Eddington et al. (1998) Pharm Res 15(3), 466

9 Model 2: Semi Mechanistic Parent/Metabolite Model (Using Differential Equation) In vitro in vivo relationship USP II, ph 6.8, 150 RPM In vivo Parent and Metabolite Data In spite of using parent and metabolite data and lag time IVIVC, prediction errors were higher. Sirisuth and Eddington (2002) EJPS 53, 301

10 Deconvolution Using the Physiologically Based ADAM Model

11 Validation of Physiologically-based IVIVC C max (ng/ml) AUC (ng/ml*h) Obs Pred %PE Obs Pred %PE Fast Medium Slow Mean

12 Designing New Once-Daily Metoprolol Formulation Therapeutic Cp range (mean) of metoprolol is ng/ml All three formulations have Cp below 20 ng/ml after 12 h Thus they require administration every 12 h (twice daily) The Fast formulation leads to Cp beyond maximum tolerable Cp (100 ng/ml) How can you use physiologically based model to design new once-daily (24 h) formulation?

13 Generating Desired Cp Profile of a New Formulation Intuitively design a desired PK profile keeping in mind the disposition kinetics of the drug How to decide the required dose??? As metoprolol has linear elimination in studied dose range, required dose for new formulation was estimated assuming linear dose-exposure (AUC) proportionality Estimated Dose of New Formulation is 200 mg

14 Estimating Required Dissolution Profile to Achieve Desired Cp Profile Apply Validated IVIVC Model to Get in vitro %Diss Profile in your in vitro settings Design a Formulation That Matches Required in vitro Dissolution Profile

15 Assessing Population Variability of New Formulation Simulating Cp profiles for 100 (10X10) healthy volunteers aged Mean Cp was maintained within Mean Therapeutic Range ( ng/ml) up to ~21 hour after dose

16 Assessing the Steady State Performance of the Designed Formulation Simulating Cp profiles for 100 (10X10) healthy volunteers aged 20-50

17 Simulating Drug Exposure in Subjects with Different CYP2D6 Phenotypes CYP2D6 is the main metabolic route for metoprolol clearance CYP2D6 Phenotypes and Frequency of Occurrence in Caucasian Population Poor Metaboliser (PM) ~ 8.2% Extensive Metaboliser (EM) ~ 86.5% Ultra Rapid Metaboliser (UM) ~ 5.3% CYP2D6 PM Subjects C max,mean = 475 ng/ml C 22h, mean = 317 ng/ml CYP2D6 EM Subjects C max,mean = 108 ng/ml C 22h, mean = 18 ng/ml CYP2D6 UM Subjects C max,mean = 62 ng/ml C 22h, mean = 06 ng/ml Such PBPK simulations could help to optimise clinical trials and identify covariates It is also helpful in deciding the dosage strengths to be studied for new formulation

18 Further Virtual Clinical Studies Using Population Based PBPK Models Performance of this new formulation in elderly, paediatric and specific age groups can also be assessed using PBPK models Various disease groups, ethnicity, etc. can be studied Metabolic DDIs can be evaluated for the designed formulation The simulated PK profiles could be linked to pharmacodynamics models to estimate and understand the efficacy of the designed formulation

19 Acknowledgment Sebastian Polak David Turner Masoud Jamei Amin Rostami-Hodjegan THANK YOU OrBiTo IMI (Pending Signature) Oral Biopharmaceutics Tool Aim is to develop new models and methods that will significantly improve prediction accuracy of in vivo drug absorption

20 Assessing Pharmacokinetic Variability with CYP Enzyme Phenotypes CYP2D6 Phenotypes and Frequency Poor Metaboliser (PM) ~ 8.2% Extensive Metaboliser (EM) ~ 86.5% Ultra High Metaboliser (UM) ~ 5.3% If the enzymes responsible for clearance and f m are known, PBPK models could be used to predict the drug exposure in subjects with different phenotypes