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Abstracts / Drug Metabolism and Pharmacokinetics 32 (2017) S1eS21
SC4.2 MODELLING METHODS AND CASE STUDIES Karen Rowland-Yeo. Simcyp (A Certara Company), Sheffield, UK The development of in vitro e in vivo extrapolation (IVIVE), a “bottom-up” approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems which act as surrogates for delineating various elements of the interactions relevant to absorption, distribution metabolism and excretion (ADME) processes. One of the main objectives of the presentation is to discuss the application of IVIVE in conjunction with physiologically based pharmacokinetic (PBPK) modelling to characterize potential DDIs interactions in individual patients, including those whom cannot be investigated in formal clinical trials for ethical reasons. Although PBPK models are built using a mathematical framework, they are parameterized using known physiology and consist of a larger number of compartments which correspond to the different organs or tissues in the body. These compartments are connected by flow rates that parallel the circulating blood system. These models provide estimates of common PK parameters e.g. clearance, volume of distribution and effective half-life. However, these more physiologically relevant models, provide a quantitative mechanistic framework by which scaled drug specific parameters (using IVIVE) can be used to predict the plasma and importantly tissue concentration time profiles of new drugs, following intravenous or oral administration. By their very nature, they can be used to extrapolate a dose in healthy volunteers to one in a disease population if the relevant physiological properties of the target population are available. Specifically, methodologies relating to IVIVE and PBPK and the prediction of PK will be discussed. In addition, issues relating to the prediction of complex DDIs involving inhibition of CYP- and transporter-mediated activities via multiple drugs or moieties will be addressed. Case studies will be used to illustrate the application of PBPK modelling in an industry setting. SC4.3 PREDICTION OF DRUG INTERACTIONS AT TRANSPORTERS Kazuya Maeda. Laboratory of Molecular Pharmacokinetics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan The importance of transporter-mediated drug-drug interactions (TP-DDIs) have been well recognized by the various clinical evidences and thus regulatory agencies routinely ask the sponsors to evaluate the potential risk of TP-DDIs for new drug candidates as a victim or a perpetuator with in vitro inhibition assays and clinical TP-DDI studies if necessary. At the early stage of drug development, risk assessment of TP-DDIs is performed by static model with considering the maximum concentration of inhibitor drug to avoid the false-negative prediction. In a static model, accurate estimation of both inhibition constant (Ki) and theoretically-maximum unbound concentration of inhibitors (Iu) should be necessary since the extent of AUC increase is calculated by 1 + Iu/Ki (R value). We have previously investigated what kind of assumptions are effective for evaluating the risk of hepatic OATPs (organic anion transporting polypeptides)mediated DDIs with static model. As a result, to avoid the false-negative predictions, it is necessary to consider that (i) intestinal availability (FaFg) becomes assumed to be 1 when intestinal efflux transporters (P-glycoprotein, BCRP (breast cancer resistance protein)) can be inhibited, (ii) theoretically-maximum unbound concentration at the inlet to the liver (Iu,in,max) should be used, and (iii) product of R values for uptake transporters and efflux transporters should be considered when simultaneous inhibition of both hepatic uptake and efflux transporters possibly occurs. For more accurate prediction of TP-DDIs, dynamic physiologically-based pharmacokinetic (PBPK) modeling with considering the time-dependent change of concentrations of substrate and inhibitor drugs is often used. At the moment, researchers used their original model structures and parameters for the risk evaluation of different individual clinical DDI cases, but the universal methods have not been fully established to cover the multiple DDI cases. Collaborative efforts of RIKEN (PI: Dr. Yuichi Sugiyama) with us lead to a systematic method to construct PBPK model for describing OATP-mediated DDIs. In our model, liver is divided into five
compartments to mimic dispersion model, distribution of drugs to skin, adipose and muscle is considered, and empirical compartments for describing enterohepatic circulation are installed. Our analyses revealed that Ki values of cyclosporine A for OATPs with its preincubation prior to the in vitro inhibition assay must be used in several DDI cases. On the other hand, it was almost impossible to determine a unique set of model parameters only by top-down approach since different fitted parameters could be successfully found when different b values (¼[CLmet + CLseq]/ [CLmet + CLseq + CLeff]) were fixed in advance. This is further confirmed by the use of “Cluster Newton Method”, which enables to find multiple sets of model parameters which can well reproduce the clinically-observed data. From our experiences, to realize a full bottom-up approach, some critical parameters such as Rdif (¼CLpassive/CLactive) and b value must be fixed from the in vitro experiments. In my presentation, I want to touch on some issues to be solved for the better prediction of TP-DDIs. SC4.4 ABSTRACT UNAVAILABLE S1 DRUG TRANSPORTERS: STARRING ROLES IN NEW DRUG DISCOVERY AND DEVELOPMENT Yuichi Sugiyama. Sugiyama Laboratory, RIKEN Innovation Center, RIKEN, Yokohama, Japan I will summarize the significant role played by drug transporters in drug disposition, focusing particularly on their roles in the liver. The use of transporter function offers the possibility of delivering a drug to the target organ, avoiding distribution to other organs (thereby reducing the chance of toxic side-effects), controlling the elimination process, and/or improving oral bioavailability. Even when drugs ultimately undergo metabolism and/or biliary excretion in the liver, their elimination rate is sometimes determined by the hepatic uptake rate mediated by uptake transporters. Elucidation of the rate-determining process in the overall hepatic elimination of drugs is therefore critical for predicting their hepatic clearance, and their systemic and regional exposures. I will show you how to understand the so-called “Extended clearance concept” and to establish a physiologically based pharmacokinetic (PBPK) model that includes the transporter-mediated membrane transport and enzyme-mediated metabolism processes and to investigate the effect of changes in transporter (influx, efflux) function and metabolizing enzyme function on the pharmacokinetics of drugs in the blood and the liver and, ultimately, the pharmacological and/or toxicological effects. For drugs, the target molecule of which is inside the cells, the efflux transporter is the determinant for their pharmacological effect or adverse reactions even though it had negligible impact in the plasma concentrations. Because of difficulty in quantitative evaluation of the subsequent efflux process, the transporters playing key roles in the efflux process remains unclear in humans. Development of probe substrates applicable to the PET imaging will elucidate the quantitative relationship between the transport activities and drug response. Recently, many studies on genetic polymorphisms(PGx) in drug transporters and transporter-mediated drug-drug interactions(DDI) have been published, and these are part of mechanisms of interindividual difference in drug response. It is important to predict such interindividual difference at early stage of drug development. This presentation will provide a brief overview of extended “clearance concept” and a PBPK model that includes the transporter-mediated transport processes in the liver. With such concept and model, the effect of changes in transporter function on the pharmacokinetics and, ultimately, the pharmacological and/ or toxicological effects will be predicted. 1. Giacomini K.M. and Sugiyama Y. Membrane transporters and drug response, in “Goodman & Gilman's The Pharmacological Basis of Therapeutics 12th Edition”, (Brunton LL, Chabner BA, Knollman B, eds) Chapter 5, McGraw-Hill Companies, New York, NY, pp 89-122 (2011). 2. Kusuhara H., Maeda K. and Sugiyama Y.. “Impact of Drug Transporters in the Pharmacological and Adverse Reactions of Drugs” pp563-598 In New Horizons in Predictive Toxicology: Current Status and Application, Ed. by Wilson AGE (2011). 3. Yoshida K., Maeda K., Sugiyama Y. Hepatic and Intestinal Drug Transporters: Prediction of Pharmacokinetic Effects Caused by Drug-Drug
Abstracts / Drug Metabolism and Pharmacokinetics 32 (2017) S1eS21
SC4.2 MODELLING METHODS AND CASE STUDIES Karen Rowland-Yeo. Simcyp (A Certara Company), Sheffield, UK The development of in vitro e in vivo extrapolation (IVIVE), a “bottom-up” approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems which act as surrogates for delineating various elements of the interactions relevant to absorption, distribution metabolism and excretion (ADME) processes. One of the main objectives of the presentation is to discuss the application of IVIVE in conjunction with physiologically based pharmacokinetic (PBPK) modelling to characterize potential DDIs interactions in individual patients, including those whom cannot be investigated in formal clinical trials for ethical reasons. Although PBPK models are built using a mathematical framework, they are parameterized using known physiology and consist of a larger number of compartments which correspond to the different organs or tissues in the body. These compartments are connected by flow rates that parallel the circulating blood system. These models provide estimates of common PK parameters e.g. clearance, volume of distribution and effective half-life. However, these more physiologically relevant models, provide a quantitative mechanistic framework by which scaled drug specific parameters (using IVIVE) can be used to predict the plasma and importantly tissue concentration time profiles of new drugs, following intravenous or oral administration. By their very nature, they can be used to extrapolate a dose in healthy volunteers to one in a disease population if the relevant physiological properties of the target population are available. Specifically, methodologies relating to IVIVE and PBPK and the prediction of PK will be discussed. In addition, issues relating to the prediction of complex DDIs involving inhibition of CYP- and transporter-mediated activities via multiple drugs or moieties will be addressed. Case studies will be used to illustrate the application of PBPK modelling in an industry setting. SC4.3 PREDICTION OF DRUG INTERACTIONS AT TRANSPORTERS Kazuya Maeda. Laboratory of Molecular Pharmacokinetics, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan The importance of transporter-mediated drug-drug interactions (TP-DDIs) have been well recognized by the various clinical evidences and thus regulatory agencies routinely ask the sponsors to evaluate the potential risk of TP-DDIs for new drug candidates as a victim or a perpetuator with in vitro inhibition assays and clinical TP-DDI studies if necessary. At the early stage of drug development, risk assessment of TP-DDIs is performed by static model with considering the maximum concentration of inhibitor drug to avoid the false-negative prediction. In a static model, accurate estimation of both inhibition constant (Ki) and theoretically-maximum unbound concentration of inhibitors (Iu) should be necessary since the extent of AUC increase is calculated by 1 + Iu/Ki (R value). We have previously investigated what kind of assumptions are effective for evaluating the risk of hepatic OATPs (organic anion transporting polypeptides)mediated DDIs with static model. As a result, to avoid the false-negative predictions, it is necessary to consider that (i) intestinal availability (FaFg) becomes assumed to be 1 when intestinal efflux transporters (P-glycoprotein, BCRP (breast cancer resistance protein)) can be inhibited, (ii) theoretically-maximum unbound concentration at the inlet to the liver (Iu,in,max) should be used, and (iii) product of R values for uptake transporters and efflux transporters should be considered when simultaneous inhibition of both hepatic uptake and efflux transporters possibly occurs. For more accurate prediction of TP-DDIs, dynamic physiologically-based pharmacokinetic (PBPK) modeling with considering the time-dependent change of concentrations of substrate and inhibitor drugs is often used. At the moment, researchers used their original model structures and parameters for the risk evaluation of different individual clinical DDI cases, but the universal methods have not been fully established to cover the multiple DDI cases. Collaborative efforts of RIKEN (PI: Dr. Yuichi Sugiyama) with us lead to a systematic method to construct PBPK model for describing OATP-mediated DDIs. In our model, liver is divided into five
compartments to mimic dispersion model, distribution of drugs to skin, adipose and muscle is considered, and empirical compartments for describing enterohepatic circulation are installed. Our analyses revealed that Ki values of cyclosporine A for OATPs with its preincubation prior to the in vitro inhibition assay must be used in several DDI cases. On the other hand, it was almost impossible to determine a unique set of model parameters only by top-down approach since different fitted parameters could be successfully found when different b values (¼[CLmet + CLseq]/ [CLmet + CLseq + CLeff]) were fixed in advance. This is further confirmed by the use of “Cluster Newton Method”, which enables to find multiple sets of model parameters which can well reproduce the clinically-observed data. From our experiences, to realize a full bottom-up approach, some critical parameters such as Rdif (¼CLpassive/CLactive) and b value must be fixed from the in vitro experiments. In my presentation, I want to touch on some issues to be solved for the better prediction of TP-DDIs. SC4.4 ABSTRACT UNAVAILABLE S1 DRUG TRANSPORTERS: STARRING ROLES IN NEW DRUG DISCOVERY AND DEVELOPMENT Yuichi Sugiyama. Sugiyama Laboratory, RIKEN Innovation Center, RIKEN, Yokohama, Japan I will summarize the significant role played by drug transporters in drug disposition, focusing particularly on their roles in the liver. The use of transporter function offers the possibility of delivering a drug to the target organ, avoiding distribution to other organs (thereby reducing the chance of toxic side-effects), controlling the elimination process, and/or improving oral bioavailability. Even when drugs ultimately undergo metabolism and/or biliary excretion in the liver, their elimination rate is sometimes determined by the hepatic uptake rate mediated by uptake transporters. Elucidation of the rate-determining process in the overall hepatic elimination of drugs is therefore critical for predicting their hepatic clearance, and their systemic and regional exposures. I will show you how to understand the so-called “Extended clearance concept” and to establish a physiologically based pharmacokinetic (PBPK) model that includes the transporter-mediated membrane transport and enzyme-mediated metabolism processes and to investigate the effect of changes in transporter (influx, efflux) function and metabolizing enzyme function on the pharmacokinetics of drugs in the blood and the liver and, ultimately, the pharmacological and/or toxicological effects. For drugs, the target molecule of which is inside the cells, the efflux transporter is the determinant for their pharmacological effect or adverse reactions even though it had negligible impact in the plasma concentrations. Because of difficulty in quantitative evaluation of the subsequent efflux process, the transporters playing key roles in the efflux process remains unclear in humans. Development of probe substrates applicable to the PET imaging will elucidate the quantitative relationship between the transport activities and drug response. Recently, many studies on genetic polymorphisms(PGx) in drug transporters and transporter-mediated drug-drug interactions(DDI) have been published, and these are part of mechanisms of interindividual difference in drug response. It is important to predict such interindividual difference at early stage of drug development. This presentation will provide a brief overview of extended “clearance concept” and a PBPK model that includes the transporter-mediated transport processes in the liver. With such concept and model, the effect of changes in transporter function on the pharmacokinetics and, ultimately, the pharmacological and/ or toxicological effects will be predicted. 1. Giacomini K.M. and Sugiyama Y. Membrane transporters and drug response, in “Goodman & Gilman's The Pharmacological Basis of Therapeutics 12th Edition”, (Brunton LL, Chabner BA, Knollman B, eds) Chapter 5, McGraw-Hill Companies, New York, NY, pp 89-122 (2011). 2. Kusuhara H., Maeda K. and Sugiyama Y.. “Impact of Drug Transporters in the Pharmacological and Adverse Reactions of Drugs” pp563-598 In New Horizons in Predictive Toxicology: Current Status and Application, Ed. by Wilson AGE (2011). 3. Yoshida K., Maeda K., Sugiyama Y. Hepatic and Intestinal Drug Transporters: Prediction of Pharmacokinetic Effects Caused by Drug-Drug