| 1. |
- Darwich, Adam S., et al.
(författare)
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IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 3 : Identifying gaps in system parameters by analysing In Silico performance across different compound classes
- 2017
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 96, s. 626-642
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Tidskriftsartikel (refereegranskat)abstract
- Three Physiologically Based Pharmacokinetic software packages (GI-Sim, Simcyp (R) Simulator, and GastroPlus (TM)) were evaluated as part of the Innovative Medicine Initiative Oral Biopharmaceutics Tools project (OrBiTo) during a blinded "bottom-up" anticipation of human pharmacokinetics. After data analysis of the predicted vs. measured pharmacokinetics parameters, it was found that oral bioavailability (F-oral) was underpredicted for compounds with low permeability, suggesting improper estimates of intestinal surface area, colonic absorption and/or lack of intestinal transporter information. Foralwas also underpredicted for acidic compounds, suggesting overestimation of impact of ionisation on permeation, lack of information on intestinal transporters, or underestimation of solubilisation of weak acids due to less than optimal intestinal model pH settings or underestimation of bile micelle contribution. F-oral was overpredicted for weak bases, suggesting inadequate models for precipitation or lack of in vitro precipitation information to build informed models. Relative bioavailability was underpredicted for both high logP compounds as well as poorly water-soluble compounds, suggesting inadequate models for solubility/dissolution, underperforming bile enhancement models and/or lack of biorelevant solubility measurements. These results indicate areas for improvement in model software, modelling approaches, and generation of applicable input data. However, caution is required when interpreting the impact of drug-specific properties in this exercise, as the availability of input parameters was heterogeneous and highly variable, and the modellers generally used the data "as is" in this blinded bottom-up prediction approach.
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| 2. |
- Galetin, Aleksandra, et al.
(författare)
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Membrane transporters in drug development and as determinants of precision medicine
- 2024
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Ingår i: NATURE REVIEWS DRUG DISCOVERY. - 1474-1776 .- 1474-1784.
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Forskningsöversikt (refereegranskat)abstract
- The effect of membrane transporters on drug disposition, efficacy and safety is now well recognized. Since the initial publication from the International Transporter Consortium, significant progress has been made in understanding the roles and functions of transporters, as well as in the development of tools and models to assess and predict transporter-mediated activity, toxicity and drug-drug interactions (DDIs). Notable advances include an increased understanding of the effects of intrinsic and extrinsic factors on transporter activity, the application of physiologically based pharmacokinetic modelling in predicting transporter-mediated drug disposition, the identification of endogenous biomarkers to assess transporter-mediated DDIs and the determination of the cryogenic electron microscopy structures of SLC and ABC transporters. This article provides an overview of these key developments, highlighting unanswered questions, regulatory considerations and future directions. Significant progress has been made in understanding the influence of membrane transporters in drug disposition and response. Here, the International Transporter Consortium provides an update on the current status of membrane transporters in drug development and regulatory requirements, discusses recent scientific advances in the field and highlights future directions and unanswered questions.
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| 3. |
- Garcia, Luna Prieto, 1988-
(författare)
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Mechanistic Based Pharmacokinetic-Pharmacodynamics models for Drug Interactions and Disease Population Predictions
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Therapeutic dose of a medication refers to the quantity of a drug required to produce a pharmacological effect without causing unacceptable adverse events. Dose selection in the clinical setting is not straight forward due to various factors, including specific patient factors such as age, sex, weight, genetic variants and renal/hepatic function, as well as external factors such as food and co-medication, all of which can influence the efficacy and safety of a drug. In silico mechanistic mathematical models, such as physiologically-based pharmacokinetic (PBPK) models, can aid dose setting by considering all these factors into a mechanistic model. The aim of this thesis was to enhance the application of PBPK modelling in drug development, with specific focus on drug-drug interactions and evaluations of genotype and disease dependencies. Additionally, the thesis assessed the implications of pre-defined PBPK platform differences.PBPK modelling, in conjunction with in vitro generated data, quantitative proteomics, pharmacodynamic models, and/or chronic kidney disease (CKD) population models, were applied to predict drug interactions in various clinically relevant cases. The model drugs used were statins, itraconazole and roxadustat. Additionally, two different PBPK platforms, Simcyp and PK-Sim, were employed throughout the different projects of this thesis providing insights on platform differences and its potential implications.The generated in vitro data and developed PBPK models provided novel insights into: 1) the relative contribution of itraconazole metabolites to the clinical drug-drug interactions, 2) the impact of statins’ distribution to muscle by transporters, 3) the critical pathways involved in the effects of disease on statins and roxadustat pharmacokinetics and drug interactions, 4) the influence of disease not only on statins’ pharmacokinetics but also on their efficacy and safety, 5) differences in software and potential implications when selecting between the Simcyp and PK-Sim platforms. These qualified PBPK models have been successfully applied to predict drug-drug, drug-gene and drug-disease interactions. They can serve as valuables tools in drug discovery and development, guiding dose-adjustments in untested scenarios, particularly in complex drug interactions. For instance, the strategy was used in lieu of clinical trials to identify a suitable dosing strategy for patients with CKD to reduce the risk of side effects or therapeutic failure of statins when combined with roxadustat.
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| 4. |
- Guo, Yingying, et al.
(författare)
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Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches
- 2018
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Ingår i: Clinical Pharmacology and Therapeutics. - : John Wiley & Sons. - 0009-9236 .- 1532-6535. ; 104:5, s. 865-889
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Forskningsöversikt (refereegranskat)abstract
- This white paper examines recent progress, applications, and challenges in predicting unbound and total tissue and intra/subcellular drug concentrations using in vitro and preclinical models, imaging techniques, and physiologically based pharmacokinetic (PBPK) modeling. Published examples, regulatory submissions, and case studies illustrate the application of different types of data in drug development to support modeling and decision making for compounds with transporter-mediated disposition, and likely disconnects between tissue and systemic drug exposure. The goals of this article are to illustrate current best practices and outline practical strategies for selecting appropriate in vitro and in vivo experimental methods to estimate or predict tissue and plasma concentrations, and to use these data in the application of PBPK modeling for human pharmacokinetic (PK), efficacy, and safety assessment in drug development.
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| 5. |
- Kenna, J. Gerry, et al.
(författare)
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Noninvasive preclinical and clinical imaging of liver transporter function relevant to drug-induced liver injury
- 2018
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Ingår i: Methods in Pharmacology and Toxicology. - New York, NY : Springer New York. - 1557-2153 .- 1940-6053. ; , s. 627-651
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Imaging technologies can evaluate many different biological processes in vitro (in cell culture models) and in vivo (in animals and humans), and many are used routinely in investigation of human liver diseases. Some of these methods can help understand liver toxicity caused by drugs in vivo in animals, and drug-induced liver injury (DILI) which arises in susceptible humans. Imaging could aid assessment of the relevance to humans in vivo of toxicity caused by drugs in animals (animal/human translation), plus toxicities observed using in vitro model systems (in vitro/in vivo translation). Technologies and probe substrates for quantitative evaluation of hepatobiliary transporter activities are of particular importance. This is due to the key role played by sinusoidal transporter mediated hepatic uptake in DILI caused by many drugs, plus the strong evidence that inhibition of the hepatic bile salt export pump (BSEP) can initiate DILI. Imaging methods for investigation of these processes are reviewed in this chapter, together with their scientific rationale, and methods of quantitative data analysis. In addition to providing biomarkers for investigation of DILI, such approaches could aid the evaluation of clinically relevant drug–drug interactions mediated via hepatobiliary transporter perturbation.
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| 6. |
- Kostewicz, Edmund S., et al.
(författare)
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PBPK models for the prediction of in vivo performance of oral dosage forms
- 2014
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 57:SI, s. 300-321
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Forskningsöversikt (refereegranskat)abstract
- Drug absorption from the gastrointestinal (GI) tract is a highly complex process dependent upon numerous factors including the physicochemical properties of the drug, characteristics of the formulation and interplay with the underlying physiological properties of the GI tract. The ability to accurately predict oral drug absorption during drug product development is becoming more relevant given the current challenges facing the pharmaceutical industry. Physiologically-based pharmacokinetic (PBPK) modeling provides an approach that enables the plasma concentration time profiles to be predicted from preclinical in vitro and in vivo data and can thus provide a valuable resource to support decisions at various stages of the drug development process. Whilst there have been quite a few successes with PBPK models identifying key issues in the development of new drugs in vivo, there are still many aspects that need to be addressed in order to maximize the utility of the PBPK models to predict drug absorption, including improving our understanding of conditions in the lower small intestine and colon, taking the influence of disease on GI physiology into account and further exploring the reasons behind population variability. Importantly, there is also a need to create more appropriate in vitro models for testing dosage form performance and to streamline data input from these into the PBPK models. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary of the current status of PBPK models available. The current challenges in PBPK set-ups for oral drug absorption including the composition of GI luminal contents, transit and hydrodynamics, permeability and intestinal wall metabolism are discussed in detail. Further, the challenges regarding the appropriate integration of results from in vitro models, such as consideration of appropriate integration! estimation of solubility and the complexity of the in vitro release and precipitation data, are also highlighted as important steps to advancing the application of PBPK models in drug development. It is expected that the "innovative" integration of in vitro data from more appropriate in vitro models and the enhancement of the GI physiology component of PBPK models, arising from the OrBiTo project, will lead to a significant enhancement in the ability of PBPK models to successfully predict oral drug absorption and advance their role in preclinical and clinical development, as well as for regulatory applications.
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| 7. |
- Margolskee, Alison, et al.
(författare)
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IMI - Oral biopharmaceutics tools project - Evaluation of bottom-up PBPK prediction success part 2 : An introduction to the simulation exercise and overview of results
- 2017
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Ingår i: European Journal of Pharmaceutical Sciences. - : Elsevier BV. - 0928-0987 .- 1879-0720. ; 96, s. 610-625
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Tidskriftsartikel (refereegranskat)abstract
- Orally administered drugs are subject to a number of barriers impacting bioavailability (F-oral), causing challenges during drug and formulation development. Physiologically-based pharmacokinetic (PBPK) modelling can help during drug and formulation development by providing quantitative predictions through a systems approach. The performance of three available PBPK software packages (GI-Sim, Simcyp (R), and GastroPlus (TM)) were evaluated by comparing simulated and observed pharmacokinetic (PK) parameters. Since the availability of input parameters was heterogeneous and highly variable, caution is required when interpreting the results of this exercise. Additionally, this prospective simulation exercise may not be representative of prospective modelling in industry, as API information was limited to sparse details. 43 active pharmaceutical ingredients (APIs) from the OrBiTo database were selected for the exercise. Over 4000 simulation output files were generated, representing over 2550 study arm-institution-software combinations and approximately 600 human clinical study arms simulated with overlap. 84% of the simulated study arms represented administration of immediate release formulations, 11% prolonged or delayed release, and 5% intravenous (i.v.). Higher percentages of i.v. predicted area under the curve (AUC) were within two-fold of observed (52.9%) compared to per oral (p.o.) (37.2%), however, F-oral and relative AUC (F-rel) between p.o. formulations and solutions were generally well predicted (64.7% and 75.0%). Predictive performance declined progressing from i.v. to solution and immediate release tablet, indicating the compounding error with each layer of complexity. Overall performance was comparable to previous large-scale evaluations. A general overprediction of AUC was observed with average fold error (AFE) of 1.56 over all simulations. AFE ranged from 0.0361 to 64.0 across the 43 APIs, with 25 showing overpredictions. Discrepancies between software packages were observed for a few APIs, the largest being 606, 171, and 81.7-fold differences in AFE between SimCYP and GI-Sim, however average performance was relatively consistent across the three software platforms.
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| 8. |
- Melillo, Nicola, et al.
(författare)
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Use of In Vivo Imaging and Physiologically-Based Kinetic Modelling to Predict Hepatic Transporter Mediated Drug–Drug Interactions in Rats
- 2023
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Ingår i: Pharmaceutics. - : MDPI AG. - 1999-4923. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- Gadoxetate, a magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 and multidrug resistance-associated protein 2. Six drugs, with varying degrees of transporter inhibition, were used to assess gadoxetate dynamic contrast enhanced MRI biomarkers for transporter inhibition in rats. Prospective prediction of changes in gadoxetate systemic and liver AUC (AUCR), resulting from transporter modulation, were performed by physiologically-based pharmacokinetic (PBPK) modelling. A tracer-kinetic model was used to estimate rate constants for hepatic uptake (khe), and biliary excretion (kbh). The observed median fold-decreases in gadoxetate liver AUC were 3.8- and 1.5-fold for ciclosporin and rifampicin, respectively. Ketoconazole unexpectedly decreased systemic and liver gadoxetate AUCs; the remaining drugs investigated (asunaprevir, bosentan, and pioglitazone) caused marginal changes. Ciclosporin decreased gadoxetate khe and kbh by 3.78 and 0.09 mL/min/mL, while decreases for rifampicin were 7.20 and 0.07 mL/min/mL, respectively. The relative decrease in khe (e.g., 96% for ciclosporin) was similar to PBPK-predicted inhibition of uptake (97–98%). PBPK modelling correctly predicted changes in gadoxetate systemic AUCR, whereas underprediction of decreases in liver AUCs was evident. The current study illustrates the modelling framework and integration of liver imaging data, PBPK, and tracer-kinetic models for prospective quantification of hepatic transporter-mediated DDI in humans.
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| 9. |
- Scotcher, Daniel, et al.
(författare)
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Physiologically Based Pharmacokinetic Modeling of TransporterMediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats
- 2021
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Ingår i: Molecular Pharmaceutics. - : American Chemical Society (ACS). - 1543-8384 .- 1543-8392. ; 18:8, s. 2997-3009
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Tidskriftsartikel (refereegranskat)abstract
- Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug-drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro-in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis-Menten constant (K-m,K-u) of gadoxetate was 106 mu M (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK-IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE-MRI profiles and elimination from the liver. Therefore, in vivo rat DCE-MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE-MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.
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