Previously we have reported that hepatobiliary transporter expressions in sandwich cultured hepatocytes (SCH) are altered 2- to 5-fold. This change could limit the model's predictive power for in vivo biliary clearance. The present study was designed to better establish in vitro to in vivo correlation (IVIVC) of biliary clearance. Eleven compounds representing the substrates of Mrp2/Abcc2, Bcrp/Abcg2 and Bsep/Abcb11 were tested in the sandwich cultured rat hepatocyte (SCRH) model. Simultaneously, the absolute difference of hepatobiliary transporters between rat livers and SCRH at day 5 post culture was determined by LC-MS/MS. This difference was integrated into the well-stirred hepatic prediction model. A correction factor named "g_factor" was mathematically defined to reflect the difference in hepatobiliary transporter expressions between the SCRH model and in vivo models, as well as the contribution of multiple transporters. When the g_factor correction was applied, the in vivo biliary clearance prediction was significantly improved. In addition, for those compounds which are poorly permeable and/or undergo transporter-dependent active uptake, the known intracellular concentrations of substrates were used to estimate intrinsic bile clearance. This led to further improvement in the prediction of in vivo bile secretion. While the rate-limiting processes of uptake transporters in the SCRH model remain to be further determined, we showed that integration of the absolute difference of hepatobiliary transporter proteins and transport contributions could improve the predictability of SCRH model. This integration is fundamental for increased confidence in the IVIVC of human biliary clearance.
Abstract. Prediction of human pharmacokinetics (PK) can be challenging for monoclonal antibodies (mAbs) exhibiting target-mediated drug disposition (TMDD). In this study, we performed a quantitative analysis of a diverse set of six mAbs exhibiting TMDD to explore translational rules that can be utilized to predict human PK. A TMDD model with rapid-binding approximation was utilized to fit PK and PD (i.e., free and/or total target levels) data, and average absolute fold error (AAFE) was calculated for each model parameter. Based on the comparative analysis, translational rules were developed and applied to a test antibody not included in the original analysis. AAFE of less than two-fold was observed between monkey and human for baseline target levels (R 0 ), body-weight (BW) normalized central elimination rate (K el /BW −0.25 ) and central volume (V c /BW 1.0 ). AAFE of less than three-fold was estimated for the binding affinity constant (K D ). The other four parameters, i.e., complex turnover rate (K int ), target turnover rate (K deg ), central to peripheral distribution rate constant (K pt ) and peripheral to central rate constant (K tp ) were poorly correlated between monkey and human. The projected human PK of test antibody based on the translation rules was in good agreement with the observed nonlinear PK. In conclusion, we recommend a TMDD model-based prediction approach that integrates in vitro human biomeasures and in vivo preclinical data using translation rules developed in this study.
Bispecific antibodies (BAbs) are novel constructs that are under development and show promise as new therapeutic modalities for cancer and autoimmune disorders. The aim of this study is to develop a semi-mechanistic modeling approach to elucidate the disposition of BAbs in plasma and possible sites of action in humans. Here we present two case studies that showcase the use of modeling to guide BAb development. In case one, a BAb is directed against a soluble and a membrane-bound ligand for treating systemic lupus erythematosus, and in case two, a BAb targets two soluble ligands as a potential treatment for ulcerative colitis and asthma. Model simulations revealed important differences between plasma and tissues, when evaluated for drug disposition and target suppression. Target concentrations at tissue sites and type (soluble vs membrane-bound), tissue-site binding, and binding affinity are all major determinants of BAb disposition and subsequently target suppression. For the presented case studies, higher doses and/or frequent dosing regimens are required to achieve 80 % target suppression in site specific tissue (the more relevant matrix) as compared to plasma. Site-specific target-mediated models may serve to guide the selection of first-in-human doses for new BAbs.
Crigler-Najjar syndrome type 1 (CN1) is an autosomal recessive disease caused by a marked decrease in uridine-diphosphate-glucuronosyltransferase (UGT1A1) enzyme activity. Delivery of hUGT1A1-modRNA (a modified messenger RNA encoding for UGT1A1) as a lipid nanoparticle is anticipated to restore hepatic expression of UGT1A1, allowing normal glucuronidation and clearance of bilirubin in patients. To support translation from preclinical to clinical studies, and first-in-human studies, a quantitative systems pharmacology (QSP) model was developed. The QSP model was calibrated to plasma and liver mRNA, and total serum bilirubin in Gunn rats, an animal model of CN1. This QSP model adequately captured the observed plasma and liver biomarker behavior across a range of doses and dose regimens in Gunn rats. First-in-human dose projections made using the translated model indicated that 0.5 mg/kg Q4W dose should provide a clinically meaningful and sustained reduction of >5 mg/dL in total bilirubin levels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.