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CYP2D6-humanized mice as a model to study altered drug metabolism during pregnancy
Abstracts / Drug Metabolism and Pharmacokinetics 32 (2017) S1eS21
and in their individual modes of regulation and substrate specificities. These differences often preclude the extrapolation of animal pharmacokinetic data to the human situation. Furthermore, they can be confounding factors in the interpretation of drug efficacy studies in animal models. For these reasons we have, in collaboration with Taconic, humanized mice for the major pathways of drug disposition, including the enzymes and transporters directly mediating drug metabolism and disposition and the transcription factors which control their regulation. In addition, we have created a panel of knockout mice where specific gene clusters, for example of the cytochrome P450-dependent monooxygenases, have been deleted alone or in combination. A model has now been developed where most of the murine cytochrome P450s involved in drug metabolism, together with the transcription factors CAR and PXR, have been substituted for their human counterparts. In this model, CYP1A1, CYP1A2, CYP2C9, CYP2D6, CYP3A4 and CYP3A7 are all expressed on an hCAR/hPXR background. This humanized mouse constitutes an extremely powerful tool for understanding the relative roles of different cytochrome P450s in drug metabolism and disposition, for the study and prediction of drug-drug interactions and e where murine efficacy models are available e for understanding pharmacokinetic/pharmacodynamic relationships. The model can also be used to improve the in silico prediction of human responses to drugs. The focus of our research is to utilize these humanized and knockout mouse models to better define the pathways of metabolism and disposition of targeted anti-cancer drugs. In this presentation, examples of how the humanized models can facilitate the more informed design of clinical trials for anti-cancer drugs used alone or in combination will be described. S14 CYP2D6-HUMANIZED MICE AS A MODEL TO STUDY ALTERED DRUG METABOLISM DURING PREGNANCY Hyun-Young Jeong. University of Illinois at Chicago, Chicago, IL, USA Cytochrome P450 2D6 (CYP2D6) is a major drug-metabolizing enzyme, responsible for eliminating ~20% of marketed drugs. CYP2D6 substrate drugs prescribed to pregnant women display increased elimination, but the underlying mechanisms were unknown. This was in part due to a lack of experimental model that recapitulates CYP2D6 induction during pregnancy. In our study, using CYP2D6-humanized transgenic (Tg-CYP2D6) mice, we showed that CYP2D6 expression and activity are significantly increased at term pregnancy. In the mouse livers, expression of a known positive regulator of CYP2D6, hepatocyte nuclear factor 4a (HNF4a), did not change during pregnancy. However, HNF4a activity (i.e., the amount of HNF4a recruited to CYP2D6 promoter) increased at term pregnancy. Of note, this was accompanied by repressed expression of small heterodimer partner (SHP). In HepG2 cells, SHP repressed HNF4a transactivation of CYP2D6 promoter. In Tg-CYP2D6 mice, SHP knockdown led to a significant increase in CYP2D6 expression. Retinoic acid, an endogenous compound that induces SHP, exhibited decreased hepatic levels during pregnancy in Tg-CYP2D6 mice. Administration of all-trans-retinoic acid led to a significant decrease in the expression and activity of hepatic CYP2D6 in TgCYP2D6 mice. In conclusion, these results indicate that altered hepatic retinoid levels and subsequent decreases in SHP expression are potentially responsible for CYP2D6 induction during pregnancy. This study provides key insights into mechanisms underlying altered CYP2D6-mediated drug metabolism during pregnancy and illustrates the usefulness of CYP-humanized mice in studying the regulation of CYP enzymes in a complex biological system such as pregnancy. S15 ABSTRACT UNAVAILABLE S16 GENERAL PK/PD APPROACH IN ONCOLOGY Gerald Fetterly. Clinical Pharmacology and Regulatory Affairs, Athenex, Buffalo, NY, USA Oncology drug development continues to be a challenge. Not only is there a need to develop new drugs or optimize the dosing of older drugs, but also to
S7
improve the speed and efficiency of oncology drug development. The paradigm of establishing the maximum tolerated dose (MTD) leading to the concept that more drug is better, continues to be the cornerstone for all drug development. Drug approval rates in oncology are still among the lowest compared to other therapeutic areas. As a result, optimal dose selection and regimens may be the key for maximizing efficacy while minimizing toxicity. Typically, it may be difficult to characterize the doseeresponse relationship in oncology, because often only one or two doses are studied in the target patient population. There is also typically a narrow therapeutic index in that drug concentrations that cause tumor shrinkage may also cause adverse effects. In recent years, population PKPD modelling has become a key tool towards streamlining oncologic drug development through early understanding, identification and quantification of various doseeresponse relationships. Population PKPD modelling provides a way to develop and assess metrics as “drivers” for various responses to treatment which can then be evaluated as predictors for survival or toxicity endpoints. Cytotoxic drugs, such as paclitaxel, continue to be widely used for the treatment of various carcinomas. Historically, paclitaxel, along with other cytotoxic drugs, have been administered based on a once every three week schedule. The main hypothesis to support this dosing schedule is by establishing an MTD at the highest dose possible that would lead to disruption of tumor growth, while allowing the bone marrow to recover because of the chemotherapy-induced toxicity. Dose dense treatment with drugs like paclitaxel, has various advantages leading to an increase in the exposure (AUC) over a treatment cycle, while balancing the adverse event profile. This concept is consistent with the hypothesis of maintaining sufficient drug concentrations above a threshold target value for an extended duration. Over the past fifteen years, there has been great interest in dose dense therapy, switching from the conventional every three week regimen to administering drugs once weekly. Oral drug delivery can provide an alternative to IV administered drugs mimicking pulse dosing that will lead to maximizing the time that the target concentration will exceed the threshold concentration that relates to a therapeutic outcome. Some key dose-limiting toxicity endpoints are thought to be related to the maximum concentration that is achieved following administration of the MTD at less frequent dosing. In part, one of the hypotheses causing an improvement in efficacy and a wider therapeutic window with pulse dosing, is that dose dense treatment produces sustainable drug concentrations that reach a target threshold for a longer period of time. As a result, pulse dosing seems to provide a more desirable approach to severe adverse events; such as neuropathy, neutropenia, and diarrhea. With a fully integrated PKPD modeling approach, both the benefits and risks of a different dosing strategy can be explored, which is of special importance in oncology. S17 ABSTRACT UNAVAILABLE S18 USE OF PBPK MODELING FOR ASSESSING AND DESIGNING DDI STUDIES FOR ONCOLOGY COMBINATION THERAPIES Rangaraj Narayanan. Celgene, Summit, NJ, USA Cancer is heterogeneous in nature with numerous mechanisms governing the uncontrolled cell growth as well as drug-resistance. In the oncology setting, single agent therapy is therefore seldom successful and combination strategies involving two or more small molecule anti-cancer agents are common practice. Drug interactions in oncology due to combination of drugs are of particular importance owing to the narrow therapeutic index and the inherent toxicity of anticancer agents. Many of the cancer drugs are substrates, inducers, and/or inhibitors of CYP enzyme(s) as well as drug transporters, resulting in the significant potential for drug-drug interactions (DDIs) when combination therapy is employed. Additionally, absorption-related DDIs can occur due to the common use of proton pump inhibitors in oncology patients and the pH-dependent solubility of many cancer drugs. To address these concerns, physiologically based pharmacokinetic (PBPK) modeling can be applied in guiding dose selection for combination therapy, addressing potential DDI liabilities and the effect of pH-mediated solubility. Case studies will be presented that demonstrate the power and utility of the PBPK approaches for predicting and managing DDIs and its limitations and future opportunities will be discussed.
and in their individual modes of regulation and substrate specificities. These differences often preclude the extrapolation of animal pharmacokinetic data to the human situation. Furthermore, they can be confounding factors in the interpretation of drug efficacy studies in animal models. For these reasons we have, in collaboration with Taconic, humanized mice for the major pathways of drug disposition, including the enzymes and transporters directly mediating drug metabolism and disposition and the transcription factors which control their regulation. In addition, we have created a panel of knockout mice where specific gene clusters, for example of the cytochrome P450-dependent monooxygenases, have been deleted alone or in combination. A model has now been developed where most of the murine cytochrome P450s involved in drug metabolism, together with the transcription factors CAR and PXR, have been substituted for their human counterparts. In this model, CYP1A1, CYP1A2, CYP2C9, CYP2D6, CYP3A4 and CYP3A7 are all expressed on an hCAR/hPXR background. This humanized mouse constitutes an extremely powerful tool for understanding the relative roles of different cytochrome P450s in drug metabolism and disposition, for the study and prediction of drug-drug interactions and e where murine efficacy models are available e for understanding pharmacokinetic/pharmacodynamic relationships. The model can also be used to improve the in silico prediction of human responses to drugs. The focus of our research is to utilize these humanized and knockout mouse models to better define the pathways of metabolism and disposition of targeted anti-cancer drugs. In this presentation, examples of how the humanized models can facilitate the more informed design of clinical trials for anti-cancer drugs used alone or in combination will be described. S14 CYP2D6-HUMANIZED MICE AS A MODEL TO STUDY ALTERED DRUG METABOLISM DURING PREGNANCY Hyun-Young Jeong. University of Illinois at Chicago, Chicago, IL, USA Cytochrome P450 2D6 (CYP2D6) is a major drug-metabolizing enzyme, responsible for eliminating ~20% of marketed drugs. CYP2D6 substrate drugs prescribed to pregnant women display increased elimination, but the underlying mechanisms were unknown. This was in part due to a lack of experimental model that recapitulates CYP2D6 induction during pregnancy. In our study, using CYP2D6-humanized transgenic (Tg-CYP2D6) mice, we showed that CYP2D6 expression and activity are significantly increased at term pregnancy. In the mouse livers, expression of a known positive regulator of CYP2D6, hepatocyte nuclear factor 4a (HNF4a), did not change during pregnancy. However, HNF4a activity (i.e., the amount of HNF4a recruited to CYP2D6 promoter) increased at term pregnancy. Of note, this was accompanied by repressed expression of small heterodimer partner (SHP). In HepG2 cells, SHP repressed HNF4a transactivation of CYP2D6 promoter. In Tg-CYP2D6 mice, SHP knockdown led to a significant increase in CYP2D6 expression. Retinoic acid, an endogenous compound that induces SHP, exhibited decreased hepatic levels during pregnancy in Tg-CYP2D6 mice. Administration of all-trans-retinoic acid led to a significant decrease in the expression and activity of hepatic CYP2D6 in TgCYP2D6 mice. In conclusion, these results indicate that altered hepatic retinoid levels and subsequent decreases in SHP expression are potentially responsible for CYP2D6 induction during pregnancy. This study provides key insights into mechanisms underlying altered CYP2D6-mediated drug metabolism during pregnancy and illustrates the usefulness of CYP-humanized mice in studying the regulation of CYP enzymes in a complex biological system such as pregnancy. S15 ABSTRACT UNAVAILABLE S16 GENERAL PK/PD APPROACH IN ONCOLOGY Gerald Fetterly. Clinical Pharmacology and Regulatory Affairs, Athenex, Buffalo, NY, USA Oncology drug development continues to be a challenge. Not only is there a need to develop new drugs or optimize the dosing of older drugs, but also to
S7
improve the speed and efficiency of oncology drug development. The paradigm of establishing the maximum tolerated dose (MTD) leading to the concept that more drug is better, continues to be the cornerstone for all drug development. Drug approval rates in oncology are still among the lowest compared to other therapeutic areas. As a result, optimal dose selection and regimens may be the key for maximizing efficacy while minimizing toxicity. Typically, it may be difficult to characterize the doseeresponse relationship in oncology, because often only one or two doses are studied in the target patient population. There is also typically a narrow therapeutic index in that drug concentrations that cause tumor shrinkage may also cause adverse effects. In recent years, population PKPD modelling has become a key tool towards streamlining oncologic drug development through early understanding, identification and quantification of various doseeresponse relationships. Population PKPD modelling provides a way to develop and assess metrics as “drivers” for various responses to treatment which can then be evaluated as predictors for survival or toxicity endpoints. Cytotoxic drugs, such as paclitaxel, continue to be widely used for the treatment of various carcinomas. Historically, paclitaxel, along with other cytotoxic drugs, have been administered based on a once every three week schedule. The main hypothesis to support this dosing schedule is by establishing an MTD at the highest dose possible that would lead to disruption of tumor growth, while allowing the bone marrow to recover because of the chemotherapy-induced toxicity. Dose dense treatment with drugs like paclitaxel, has various advantages leading to an increase in the exposure (AUC) over a treatment cycle, while balancing the adverse event profile. This concept is consistent with the hypothesis of maintaining sufficient drug concentrations above a threshold target value for an extended duration. Over the past fifteen years, there has been great interest in dose dense therapy, switching from the conventional every three week regimen to administering drugs once weekly. Oral drug delivery can provide an alternative to IV administered drugs mimicking pulse dosing that will lead to maximizing the time that the target concentration will exceed the threshold concentration that relates to a therapeutic outcome. Some key dose-limiting toxicity endpoints are thought to be related to the maximum concentration that is achieved following administration of the MTD at less frequent dosing. In part, one of the hypotheses causing an improvement in efficacy and a wider therapeutic window with pulse dosing, is that dose dense treatment produces sustainable drug concentrations that reach a target threshold for a longer period of time. As a result, pulse dosing seems to provide a more desirable approach to severe adverse events; such as neuropathy, neutropenia, and diarrhea. With a fully integrated PKPD modeling approach, both the benefits and risks of a different dosing strategy can be explored, which is of special importance in oncology. S17 ABSTRACT UNAVAILABLE S18 USE OF PBPK MODELING FOR ASSESSING AND DESIGNING DDI STUDIES FOR ONCOLOGY COMBINATION THERAPIES Rangaraj Narayanan. Celgene, Summit, NJ, USA Cancer is heterogeneous in nature with numerous mechanisms governing the uncontrolled cell growth as well as drug-resistance. In the oncology setting, single agent therapy is therefore seldom successful and combination strategies involving two or more small molecule anti-cancer agents are common practice. Drug interactions in oncology due to combination of drugs are of particular importance owing to the narrow therapeutic index and the inherent toxicity of anticancer agents. Many of the cancer drugs are substrates, inducers, and/or inhibitors of CYP enzyme(s) as well as drug transporters, resulting in the significant potential for drug-drug interactions (DDIs) when combination therapy is employed. Additionally, absorption-related DDIs can occur due to the common use of proton pump inhibitors in oncology patients and the pH-dependent solubility of many cancer drugs. To address these concerns, physiologically based pharmacokinetic (PBPK) modeling can be applied in guiding dose selection for combination therapy, addressing potential DDI liabilities and the effect of pH-mediated solubility. Case studies will be presented that demonstrate the power and utility of the PBPK approaches for predicting and managing DDIs and its limitations and future opportunities will be discussed.