Advances in Prediction of Food Effects

Transcription

1 Advances in Prediction of Food Effects John Crison APS Biopharmaceutics Focus Group MSD Innovation Centre, Hoddesdon, UK June 9, 2011

2 Outline Introduction/Theory Physiological and Physical Chemical Parameters Enhanced Dissolution Enhanced Solubilization Methods For Predicting Food Effects In Vitro/Cell Cultures In Vivo In Silico Statistical models PBPK models 1

3 Physiological and Physical Chemical Effects of Food Drug in Stomach with Food (dietary lipid) Delay in gastric emptying Drug in intestine w/ bile, enzymes, proteins, change in ph, changes in splanchnic blood flow, lymphatic transport. Change in absorption (over fasted conditions) The amount of lipophilic compound absorbed under fed conditions can increased through increased residence, solubility enhancement, lymphatic transport, etc. In order to predict a food effect, must understand which parameter is rate limiting. 2

4 Extension of the Macroscopic Mass Balance Approach Solid and Solution Phases Solid phase Soln. Phase rate of mass in rate of mass out rate of mass dissolved = 0 rate of mass in rate of mass out + rate of mass dissolved rate of mass absorbed = 0 Rate of mass in Rate of mass dissolved Rate of mass out Rate of mass absorbed Oh, et al, Pharmaceutical Research, Vol. 10, No. 2,

5 Solid and Solution Phases dr p dz dc dz L D R 2 Q N D o C s C r p V 4 o Q 2 L R 2 r p P 2R eff C s CL CL Q r p = particle radius D = diffusion coefficient R = intestinal radius Q = flow rate ρ = solid density C s = solubility C L = concentration in lumen P eff = intestinal permeability N 0 = number of particles V 0 = volume of water taken with dose z = axial length of tube 4

6 Dimensionless Transport Parameters dr dz dc dz Dn 3r 1 C Do Dn r 1 C 2An C Mo Vo Do CS Dn DC 4ro r 4 o 3 r An P eff R t res 2 t 3 res o 5

7 Fraction Dose Absorbed Amidon, G.L., et al, Pharm Res, 12(3), 1995

8 Outline Introduction/Theory Physiological and Physical Chemical Parameters Enhanced Dissolution Enhanced Solubilization Methods For Predicting Food Effects In Vitro/Cell Cultures In Vivo In Silico Statistical models PBPK models 7

9 Enhanced Solubility and Dissolution Micelle-Facilitated Dissolution Lipophilic drug are solubilized by mixed micelles. Increased drug concentration drives absorption. Research Models In Vitro In Silico 8

10 Micelle-Facilitated Dissolution Solid Diffusional Boundary Layer solute + micelle C= C s solute Crison, J.R., et al, J Pharm Sci, 85(9): , 1996

11 Micelle Facilitated Solubility & Dissolution S S water SAA 1 k C micelle D s = diffusivity of solute D eff = effective diffusivity of micelle C micelle = concentration of micelle S water = concentration of solute in water S SAA = concentration of solute in surfactant J water = Dissolution rate of solute in water J SAA = Dissolution rate of solute in surfactant k = equilibrium coefficient J J water SAA D D eff S 1 k C micelle

12 Predicting Food Effects Based on In Vitro Solubilization olubilization Lipids Micelle-facilitated n Vitro Methods for Measuring Solubility Enhancement Synthetic surfactants Bile salts, bile salts/lecithin, bile salts/lecithin/lipids mixed micelles Microemulsions (parenteral emulsions, milk) Lipid/enzyme systems 11

13 Physiologically Similar Dissolution Media Component Concentration Sod. Taurocholate, mm 10 Lecithin, mm 2 Glycerol Monooleate 5 Sodium Oleate 0.8 Maleic Acid Sodium Hydroxide Sodium Chloride ph 5.8 Osmolarity 390 ± 10 Buffer Capacity 25 Use of physiologically similar dissolution media gave an advantage over compendial media. Shono,Y., et al, Eur J Pharm and Biopharm, 76:95-104, Jantratid, E., et al, Pharm Res., 25(7): ,

14 Use of In Silico Models everal commercial products now include: Physiologically based PK absorption models Default values for bile salt concentrations under fed and fasted conditions. User input of experimental solubilization values Diffusion coefficients of mixed micelles tatistical Models (literature) Predict food effect on extent of absorption Solubility, permeability, dose, logd Predict lymphatic uptake based on SAR Molecular descriptors include fraction of hydrophilic surface area, hydrophilic-lipophilic ratio, sphericity, center of mass to hydrophilic regions, center of mass to lipophilic regions. Gu, C.H., Pharm Res, 24(6): , 2007 Holm, R., et al, Int J Pharm, 272: ,

15 Intestinal Lymphatic Drug Transport Lymphatic Transport Physical chemical properties associated with lymphatic transport: Typically logp > 5 Solubility in long chain triglycerides > 50mg/gm Association with colloidal lipoproteins Mono- and poly-unsaturated lipids Research Models Animal In Vitro/Cell Culture In Silico Trevakis, N.L., et al, Adv Drug Del Rev, 60: ,

16 Intestinal Lymphatic Drug Transport Research Models In vivo Surgical access to the lymphatic duct: Collect entire volume of lymph Sample lymph over time via shunt Rats, dogs Larger animals can be dosed human dosage forms In Vitro/Cell Cultures In Silico Statistical SAR model Molecular descriptors include fraction of hydrophilic surface area, hydrophilic-lipophilic ratio, sphericity, center of mass to hydrophilic regions, center of mass to lipophilic regions. Karpf, D.M., et al, J Pharm Sci, 95(1):45-55, 2006 Holm, R., et al, Int J Pharm, 272: ,

17 Animal Models for Predicting Food Effects Test Animal - Beagle Dogs Model Attributes Qualitatively correlated to the magnitude of food effect in humans Preclinical dosage forms tested Range of doses and formulation types to validate robustness Rapid throughput Not over-predicting Test Conditions FDA high fat meal, 50 gm Pentagastrin treated In Vitro/Cell Cultures Lentz, K., J Pharm Sci, 96: ,

18 Conclusions Advances Advances have been made in the use of dog models for in vivo preclinical predictions. Several new in vitro methods have been or are under development. In many cases, results from in vitro and preclinical in vivo models are incorporated into in silico PBPK absorption models to refine predictions in humans. 17