464286 Gender-Dependent PBPK Modeling

Monday, November 14, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Ioannis P. Androulakis1, Megerle Scherholz2, Patrick J. Sinko3, Marianthi Ierapetritou4 and Clara Hartmanshenn4, (1)Biomedical and Chemical & Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ, (2)Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Pisctaway, NJ, (3)Department of Pharmaceutics, Rutgers University, Piscataway, NJ, (4)Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ

Personalized medicine has the potential to improve disease prevention and treatment by tailoring therapies to the unique physiological and environmental factors that describe a subpopulation or even an individual patient. Personalized medicine aims at providing patients with “the right drug at the right dose at the right time” (1) to maximize therapeutic efficiency and minimize adverse events. Anatomical differences (height, body weight, body composition), ethnicity, genotype, disease state, age, and gender, amongst other factors can lead to significant variations in the bioavailability of a drug due to differences in the rates and/or extent of absorption, distribution, metabolism and elimination (ADME) following administration. The success of personized medicine hinges on the industry’s capacity to understand the role of these physiological and genetic factors that drive differences in ADME and ultimately the action of a drug. Identifying factors with the potential to impart the greatest effect on bioavailability is a critical step to explaining clinical observations and understanding the usefulness of a particular treatment. One such tool to enable this mechanistic understanding in silico is physiologically-based pharmacokinetic (PBPK) modeling.

Unlike traditional pharmacokinetics which calculates key parameters from existing experimental data, PBPK models have the ability to extrapolate bioavailability predictions to new populations or disease states, and for new administration routes or formulation, in addition to explaining physiological differences such as age or gender. PBPK models consist of a system of mathematical equations to describe the ADME processes across the various organs and tissues of the human body (2). These mechanistic models, in comparison to traditional compartmental modeling, expand the usefulness of pharmacokinetics to drug discovery, development and regulation for knowledge-based decision making. These models leverage drug physical chemical properties and body-specific physiological parameters to predict the amount of drug that is absorbed and reaches systemic circulation (3).

Physiological differences between genders are of particular interest given that women respond differently to therapies than males, both in regards to the effectiveness of a particular treatment as well as in the extent of observed adverse effects. These observations are well cited in the literature, indicating that physiological differences between genders can lead to vast differences in pharmacokinetic parameters (AUC, Cmax, clearance, volume of distribution) and potentially variations in pharmacodynamic responses (4-6). Differences in pharmacokinetics and pharmacodynamics has been observed clinically across many systems of the body including the central nervous system, cardiovascular system, energy metabolism, and the immune system (4). The clinical relevance of the differences in pharmacokinetic responses varies with the physicochemical properties of the drug, female physiology, and mechanism of action of the drug. The vast differences in drug behavior across a multitude of bodily systems suggests that sex-dependent pharmacokinetics are highly complex as the potential for differences span across all ADME processes.

Gender dependent responses are not always consistently reported in clinical studies given the strong influence of sex hormones during development, the menstrual cycle and with the use of oral contraceptives to drive higher variability in the pharmacokinetics for women as compared to men. Thus, incorporating gender differences is an important consideration and the next logical step in the expansion of PKPD modeling for more accurate predictions of clinical performance to tease out differences between males and females in well-defined and controlled virtual clinical studies. This expansion begins with an understanding of how the ADME processes vary in males and females in order to accurately predict bioavailability in both genders. In general, males and females are believed to have similar metabolic and signaling pathways with sex-dependent regulation of transcription, translation, and receptor signaling by sex hormones (7). Therefore, the focus of this work is to establish gender-specific PBPK model parameters for male and females that can be used for prediction of absorption and ultimately bioavailability of an oral solid dosage form. The opportunity for gender-dependent pharmacokinetics of an orally administered drug begins with absorption from the gastrointestinal tract. Sex hormones influence absorption from the gastrointestinal tract on several levels including gender-dependent physiology (passive diffusion), expression and activity of intestinal transporters (active transport), and expression and activity of gastric enzymes and cytochrome P450 isozymes (gut metabolism) in addition to gastrointestinal pH and transit time (8).

The properties of the drug (or formulation) for a solid oral dosage form dictate the extent of the observed differences in pharmacokinetics between genders. In a preliminary case study, we chose to study the effect of formulation properties, mainly pH-dependent solubility or in vivo dissolution, on the rate and extent of absorption in males and females. The purpose of this study was to establish an understanding of the gender-dependent sensitivity of absorption to changes in in vivo release. Using GastroPlus™ software, the Advanced Compartmental Absorption and Transit model parameters were adjusted to reflect male and female physiology. Gender-dependent absorption was predicted given dissolution profiles as input to the software with varying rates and extent of release.

1. Hamburg MA, Collins FS. The path to personalized medicine. The New England Journal of Medicine. 2010:301-4.

2. Yang RS, Mayeno AN, Liao KH, Reardon KF, Reisfeild B. Integration of PBPK and reaction network modelling: Predictive xenobiotic metabolomics. ALTEX 22. 2005(2).

3. Rowland M, Peck C, Tucker G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu Rev Pharmacol Toxicol. 2011;51:45-73.

4. Soldin OP, Chung SH, Mattison DR. Sex differences in drug disposition. J Biomed Biotechnol. 2011;2011:187103.

5. Ibarra M, Vazquez M, Fagiolino P, Derendorf H. Sex related differences on valproic acid pharmacokinetics after oral single dose. J Pharmacokinet Pharmacodyn. 2013;40(4):479-86.

6. Chen ML, Lee SC, Ng MJ, Schuirmann DJ, Lesko LJ, Williams RL. Pharmacokinetic analysis of bioequivalence trials: implications for sex-related issues in clinical pharmacology and biopharmaceutics. Clin Pharmacol Ther. 2000;68(5):510-21.

7. Regitz-Zagrosek V. Sex and Gender Differences in Pharmacology. Heidelberg: Springer; 2012. 599 p.

8. Freire AC, Basit AW, Choudhary R, Piong CW, Merchant HA. Does sex matter? The influence of gender on gastrointestinal physiology and drug delivery. Int J Pharm. 2011;415(1-2):15-28.

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