1
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Lautz LS, Dorne JLCM, Punt A. Application of partition coefficient methods to predict tissue:plasma affinities in common farm animals: Influence of ionisation state. Toxicol Lett 2024; 398:140-149. [PMID: 38925423 DOI: 10.1016/j.toxlet.2024.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 05/17/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024]
Abstract
Tissue affinities are conventionally determined from in vivo steady-state tissue and plasma or plasma-water chemical concentration data. In silico approaches were initially developed for preclinical species but standardly applied and tested in human physiologically-based kinetic (PBK) models. Recently, generic PBK models for farm animals have been made available and require partition coefficients as input parameters. In the current investigation, data for species-specific tissue compositions have been collected, and prediction of chemical distribution in various tissues of livestock species for cattle, chicken, sheep and swine have been performed. Overall, tissue composition was very similar across the four farm animal species. However, small differences were observed in moisture, fat and protein content in the various organs within each species. Such differences could be attributed to factors such as variations in age, breed, and weight of the animals and general conditions of the animal itself. With regards to the predictions of tissue:plasma partition coefficients, 80 %, 71 %, 77 % of the model predictions were within a factor 10 using the methods of Berezhkovskiy (2004), Rodgers and Rowland (2006) and Schmitt (2008). The method of Berezhkovskiy (2004) was often providing the most reliable predictions except for swine, where the method of Schmitt (2008) performed best. In addition, investigation of the impact of chemical classes on prediction performance, all methods had very similar reliability. Notwithstanding, no clear pattern regarding specific chemicals or tissues could be detected for the values predicted outside a 10-fold change in certain chemicals or specific tissues. This manuscript concludes with the need for future research, particularly focusing on lipophilicity and species differences in protein binding.
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Affiliation(s)
- L S Lautz
- Wageningen Food Safety Research, Akkermaalsbos 2, Wageningen, WB 6708, the Netherlands.
| | - J-L C M Dorne
- European Food Safety Authority, Via Carlo Magno 1A, Parma 43126, Italy
| | - A Punt
- Wageningen Food Safety Research, Akkermaalsbos 2, Wageningen, WB 6708, the Netherlands
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2
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Poulin P, Nicolas JM, Bouzom F. A New Version of the Tissue Composition-Based Model for Improving the Mechanism-Based Prediction of Volume of Distribution at Steady-State for Neutral Drugs. J Pharm Sci 2024; 113:118-130. [PMID: 37634869 DOI: 10.1016/j.xphs.2023.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/18/2023] [Accepted: 08/19/2023] [Indexed: 08/29/2023]
Abstract
In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vdss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vdss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vdss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vdss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. And more than 95% of the predictions were within threefold error and patient interindividual differences can be predicted with the TCM-New, greatly exceeding the accuracy of the published models. Overall, the new TCM incorporating BPR significantly improved the Vdss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.
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Affiliation(s)
- Patrick Poulin
- Consultant Patrick Poulin Inc., Québec City, Québec, Canada; School of Public Health, Université de Montréal, Montréal, Québec, Canada.
| | | | - François Bouzom
- DMPK, Development Science, UCB Pharma, Braine I'Alleud, Belgium; Current: Simulations Plus, Inc., 42505 10th Street West, Lancaster, CA 93534, USA
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3
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Langthaler K, Jones CR, Brodin B, Bundgaard C. Assessing extent of brain penetration in vivo (K p,uu,brain) in Göttingen minipig using a diverse set of reference drugs. Eur J Pharm Sci 2023; 190:106554. [PMID: 37543065 DOI: 10.1016/j.ejps.2023.106554] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/02/2023] [Accepted: 08/02/2023] [Indexed: 08/07/2023]
Abstract
The application of Göttingen minipigs for non-rodent pharmacokinetics (PK) and drug safety testing has seen a dramatic increase in recent years. The aim of this study was to determine the total and unbound brain-to-plasma ratios (Kp,brain and Kp,uu,brain) for a diverse set of reference compounds in female Göttingen minipigs and compare these with Kp,uu,brain values from other species to assess the suitability of Göttingen minipigs as a model for CNS drug safety testing and brain PK in clinical translation. The reference set consisted of 17 compounds with varying physico-chemical properties and included known human P-glycoprotein (P-gp) substrates. The results of the study showed, that minipig Kp,brain and Kp,uu,brain values for the tested compounds were in the range 0.03-86 and 0.02-2.4 (n = 3-4) respectively. The Kp,uu,brain values were comparable between minipig and rat for a large proportion of the compounds (71% within 2-fold, n = 17). Comparisons of brain penetration across several species for a subset of reference compounds revealed that minipig values were quite similar to those of rat, dog, monkey and human. The study highlighted that the largest Kp,uu,brain species differences were observed for compounds classified as transporter substrates (e.g. cimetidine, risperidone, Way-100635 and altanserin). In conclusion these brain penetration data add substantially to the available literature on PK and drug disposition for minipigs and support use of Göttingen minipig as a non-rodent drug safety model for CNS drug candidates and as a brain PK model for clinical translation.
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Affiliation(s)
- Kristine Langthaler
- Translational DMPK, H. Lundbeck A/S, Ottiliavej 9, 2500 Valby, Denmark; CNS Drug Delivery and Barrier Modelling, University of Copenhagen, Universitetsparken 2, 2100 København Ø, Denmark
| | - Christopher R Jones
- Translational DMPK, H. Lundbeck A/S, Ottiliavej 9, 2500 Valby, Denmark; PKPD Modelling & Simulation, H. Lundbeck A/S, Ottiliavej 9, 2500 Valby, Denmark.
| | - Birger Brodin
- CNS Drug Delivery and Barrier Modelling, University of Copenhagen, Universitetsparken 2, 2100 København Ø, Denmark
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4
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Langthaler K, Jones CR, Christensen RB, Eneberg E, Brodin B, Bundgaard C. Characterization of intravenous pharmacokinetics in Göttingen minipig and clearance prediction using established in vitro to in vivo extrapolation methodologies. Xenobiotica 2022; 52:591-607. [PMID: 36000364 DOI: 10.1080/00498254.2022.2115425] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Abstract
1. The use of the Göttingen minipig as an animal model for drug safety testing and prediction of human pharmacokinetics (PK) continues to gain momentum in pharmaceutical research and development. The aim of this study was to evaluate in vitro to in vivo extrapolation (IVIVE) methodologies for prediction of hepatic, metabolic clearance (CLhep,met) in Göttingen minipig, using a comprehensive set of compounds.2. In vivo clearance was determined in Göttingen minipig by intravenous cassette dosing and hepatocyte intrinsic clearance, plasma protein binding and non-specific incubation binding were determined in vitro. Prediction of CLhep,met was performed by IVIVE using conventional and adapted formats of the well-stirred liver model.3. The best prediction of in vivo CLhep,met from scaled in vitro kinetic data was achieved using an empirical correction factor based on a 'regression offset' of the IVIV relationship.4. In summary, these results expand the in vitro and in vivo PK knowledge in Göttingen minipig. We show regression corrected IVIVE provides superior prediction of in vivo CLhep,met in minipig offering a practical, unified scaling approach to address systematic under-predictions. Finally, we propose a reference set for researchers to establish their own 'lab-specific' regression correction for IVIVE in minipig.
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Affiliation(s)
- K Langthaler
- Translational DMPK, H. Lundbeck A/S, Copenhagen, Denmark.,CNS Drug Delivery and Barrier Modelling, University of Copenhagen, Copenhagen, Denmark
| | - C R Jones
- Translational DMPK, H. Lundbeck A/S, Copenhagen, Denmark
| | | | - E Eneberg
- Translational DMPK, H. Lundbeck A/S, Copenhagen, Denmark
| | - B Brodin
- CNS Drug Delivery and Barrier Modelling, University of Copenhagen, Copenhagen, Denmark
| | - C Bundgaard
- Translational DMPK, H. Lundbeck A/S, Copenhagen, Denmark
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5
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Gardner I, Xu M, Han C, Wang Y, Jiao X, Jamei M, Khalidi H, Kilford P, Neuhoff S, Southall R, Turner DB, Musther H, Jones B, Taylor S. Non-specific binding of compounds in in vitro metabolism assays: a comparison of microsomal and hepatocyte binding in different species and an assessment of the accuracy of prediction models. Xenobiotica 2022; 52:943-956. [PMID: 36222269 DOI: 10.1080/00498254.2022.2132426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Non-specific binding in in vitro metabolism systems leads to an underestimation of the true intrinsic metabolic clearance of compounds being studied. Therefore in vitro binding needs to be accounted for when extrapolating in vitro data to predict the in vivo metabolic clearance of a compound. While techniques exist for experimentally determining the fraction of a compound unbound in in vitro metabolism systems, early in drug discovery programmes computational approaches are often used to estimate the binding in the in vitro system.Experimental fraction unbound data (n = 60) were generated in liver microsomes (fumic) from five commonly used pre-clinical species (rat, mouse, dog, minipig, monkey) and humans. Unbound fraction in incubations with mouse, rat or human hepatocytes was determined for the same 60 compounds. These data were analysed to determine the relationship between experimentally determined binding in the different matrices and across different species. In hepatocytes there was a good correlation between fraction unbound in human and rat (r2=0.86) or mouse (r2=0.82) hepatocytes. Similar correlations were observed between binding in human liver microsomes and microsomes from rat, mouse, dog, Göttingen minipig or monkey liver microsomes (r2 of >0.89, n = 51 - 52 measurements in different species). Physicochemical parameters (logP, pKa and logD) were predicted for all evaluated compounds. In addition, logP and/or logD were measured for a subset of compounds.Binding to human hepatocytes predicted using 5 different methods was compared to the measured data for a set of 59 compounds. The best methods evaluated used measured microsomal binding in human liver microsomes to predict hepatocyte binding. The collated physicochemical data were used to predict the human fumic using four different in silico models for a set of 53-60 compounds. The correlation (r2) and root mean square error between predicted and observed microsomal binding was 0.69 & 0.20, 0.47 & 0.23, 0.56 & 0.21 and 0.54 & 0.26 for the Turner-Simcyp, Austin, Hallifax-Houston and Poulin models, respectively. These analyses were extended to include measured literature values for binding in human liver microsomes for a larger set of compounds (n=697). For the larger dataset of compounds, microsomal binding was well predicted for neutral compounds (r2=0.67 - 0.70) using the Poulin, Austin, or Turner-Simcyp methods but not for acidic or basic compounds (r2<0.5) using any of the models. While the lipophilicity-based models can be used, the in vitro binding should be measured for compounds where more certainty is needed, using appropriately calibrated assays and possibly established weak, moderate, and strong binders as reference compounds to allow comparison across databases.
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Affiliation(s)
| | - Mandy Xu
- Pharmaron Beijing Co. Ltd., Beijing, China
| | | | - Yi Wang
- Pharmaron Beijing Co. Ltd., Beijing, China
| | | | | | | | - Peter Kilford
- Certara UK Ltd., Sheffield, United Kingdom.,Labcorp Drug Development, Harrogate, United Kingdom
| | | | | | | | | | - Barry Jones
- Pharmaron UK, Hoddesdon, Hertfordshire, United Kingdom
| | - Simon Taylor
- Pharmaron UK, Hoddesdon, Hertfordshire, United Kingdom
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6
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Sherbetjian E, Peters SA, Petersson C. Utility of preclinical species for uncertainty assessment and correction of prediction of human volume of distribution using the Rodgers-Lukacova model. Xenobiotica 2022; 52:661-668. [PMID: 36190773 DOI: 10.1080/00498254.2022.2132427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Prediction of rat, dog, monkey, and human volume of distribution (VDss) by Rodgers-Lukacova model was evaluated using a data set of more than 100 compounds.The prediction accuracy was best for humans followed by monkeys and dogs with 59, 52, and 41% of compounds within 2-fold, respectively.The accuracy of predictions in preclinical species was indicative of the human situation. This was particularly true for monkeys, where 87% of the compounds that were predicted within 2-fold in monkeys were also predicted within 2-fold in humans.The model's tendency to underestimate VDss was higher in rats and dogs compared to humans and monkeys for all ion classes but zwitterions. Hence, correction of human predictions using prediction errors in rats and dogs resulted in overestimation of VDss.The model had a similar degree of underestimation in humans and monkeys. Correction using monkeys improved the accuracy of the human estimate, especially for basic and zwitterion compounds.A strategy is proposed based on the accuracy of prediction in monkey and monkey scalars for prediction and prospective assessment of the accuracy of human VDss.
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Affiliation(s)
- Eva Sherbetjian
- Department of Clinical Pharmacology, Merck Institute for Pharmacometrics (An Affiliate of Merck KGaA), Lausanne, Switzerland
| | - Sheila-Annie Peters
- Department of Translational Medicine and Clinical Pharmacology, Boehringer Ingelheim Pharma GmbH & Co. KG, Ingelheim am Rhein, Germany
| | - Carl Petersson
- NCE DMPK, Discovery & Development Technologies, Merck Healthcare KGaA, Darmstadt, Germany
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7
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Chou WC, Tell LA, Baynes RE, Davis JL, Maunsell FP, Riviere JE, Lin Z. An Interactive Generic Physiologically Based Pharmacokinetic (igPBPK) Modeling Platform to Predict Drug Withdrawal Intervals in Cattle and Swine: A Case Study on Flunixin, Florfenicol and Penicillin G. Toxicol Sci 2022; 188:180-197. [PMID: 35642931 PMCID: PMC9333411 DOI: 10.1093/toxsci/kfac056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Violative chemical residues in edible tissues from food-producing animals are of global public health concern. Great efforts have been made to develop physiologically based pharmacokinetic (PBPK) models for estimating withdrawal intervals (WDIs) for extralabel prescribed drugs in food animals. Existing models are insufficient to address the food safety concern as these models are either limited to 1 specific drug or difficult to be used by non-modelers. This study aimed to develop a user-friendly generic PBPK platform that can predict tissue residues and estimate WDIs for multiple drugs including flunixin, florfenicol, and penicillin G in cattle and swine. Mechanism-based in silico methods were used to predict tissue/plasma partition coefficients and the models were calibrated and evaluated with pharmacokinetic data from Food Animal Residue Avoidance Databank (FARAD). Results showed that model predictions were, in general, within a 2-fold factor of experimental data for all 3 drugs in both species. Following extralabel administration and respective U.S. FDA-approved tolerances, predicted WDIs for both cattle and swine were close to or slightly longer than FDA-approved label withdrawal times (eg, predicted 8, 28, and 7 days vs labeled 4, 28, and 4 days for flunixin, florfenicol, and penicillin G in cattle, respectively). The final model was converted to a web-based interactive generic PBPK platform. This PBPK platform serves as a user-friendly quantitative tool for real-time predictions of WDIs for flunixin, florfenicol, and penicillin G following FDA-approved label or extralabel use in both cattle and swine, and provides a basis for extrapolating to other drugs and species.
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Affiliation(s)
- Wei-Chun Chou
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, 32610, USA.,Center for Environmental and Human Toxicology, University of Florida, FL, 32608, USA
| | - Lisa A Tell
- Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California-Davis, Davis, CA, 95616, USA
| | - Ronald E Baynes
- Center for Chemical Toxicology Research and Pharmacokinetics, Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, 27606, USA
| | - Jennifer L Davis
- Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Blacksburg, VA, 24060, USA
| | - Fiona P Maunsell
- Department of Large Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32608, USA
| | - Jim E Riviere
- Center for Chemical Toxicology Research and Pharmacokinetics, Department of Population Health and Pathobiology, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, 27606, USA.,1Data Consortium,Kansas State University, Olathe, KS, 66061, USA
| | - Zhoumeng Lin
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, 32610, USA.,Center for Environmental and Human Toxicology, University of Florida, FL, 32608, USA
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8
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Ayuso M, Buyssens L, Stroe M, Valenzuela A, Allegaert K, Smits A, Annaert P, Mulder A, Carpentier S, Van Ginneken C, Van Cruchten S. The Neonatal and Juvenile Pig in Pediatric Drug Discovery and Development. Pharmaceutics 2020; 13:44. [PMID: 33396805 PMCID: PMC7823749 DOI: 10.3390/pharmaceutics13010044] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 12/22/2020] [Accepted: 12/22/2020] [Indexed: 02/06/2023] Open
Abstract
Pharmacotherapy in pediatric patients is challenging in view of the maturation of organ systems and processes that affect pharmacokinetics and pharmacodynamics. Especially for the youngest age groups and for pediatric-only indications, neonatal and juvenile animal models can be useful to assess drug safety and to better understand the mechanisms of diseases or conditions. In this respect, the use of neonatal and juvenile pigs in the field of pediatric drug discovery and development is promising, although still limited at this point. This review summarizes the comparative postnatal development of pigs and humans and discusses the advantages of the juvenile pig in view of developmental pharmacology, pediatric diseases, drug discovery and drug safety testing. Furthermore, limitations and unexplored aspects of this large animal model are covered. At this point in time, the potential of the neonatal and juvenile pig as nonclinical safety models for pediatric drug development is underexplored.
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Affiliation(s)
- Miriam Ayuso
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium; (L.B.); (M.S.); (A.V.); (C.V.G.)
| | - Laura Buyssens
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium; (L.B.); (M.S.); (A.V.); (C.V.G.)
| | - Marina Stroe
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium; (L.B.); (M.S.); (A.V.); (C.V.G.)
| | - Allan Valenzuela
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium; (L.B.); (M.S.); (A.V.); (C.V.G.)
| | - Karel Allegaert
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium; (K.A.); (P.A.)
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium;
- Department of Hospital Pharmacy, Erasmus MC Rotterdam, 3000 CA Rotterdam, The Netherlands
| | - Anne Smits
- Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium;
- Neonatal Intensive Care Unit, University Hospitals UZ Leuven, 3000 Leuven, Belgium
| | - Pieter Annaert
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, 3000 Leuven, Belgium; (K.A.); (P.A.)
| | - Antonius Mulder
- Department of Neonatology, University Hospital Antwerp, 2650 Edegem, Belgium;
- Laboratory of Experimental Medicine and Pediatrics, University of Antwerp, 2610 Wilrijk, Belgium
| | | | - Chris Van Ginneken
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium; (L.B.); (M.S.); (A.V.); (C.V.G.)
| | - Steven Van Cruchten
- Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, 2610 Wilrijk, Belgium; (L.B.); (M.S.); (A.V.); (C.V.G.)
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Cheruvu HS, Liu X, Grice JE, Roberts MS. Modeling percutaneous absorption for successful drug discovery and development. Expert Opin Drug Discov 2020; 15:1181-1198. [DOI: 10.1080/17460441.2020.1781085] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Hanumanth Srikanth Cheruvu
- Therapeutics Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Australia
| | - Xin Liu
- Therapeutics Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Australia
| | - Jeffrey E. Grice
- Therapeutics Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Australia
| | - Michael S. Roberts
- Therapeutics Research Centre, The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Australia
- University of South Australia School of Pharmacy and Medical Sciences, The Queen Elizabeth Hospital, Adelaide, Australia
- Therapeutics Research Centre, Basil Hetzel Institute for Translational Health Research, The Queen Elizabeth Hospital, Adelaide, Australia
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10
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Petersson C, Papasouliotis O, Lecomte M, Badolo L, Dolgos H. Prediction of volume of distribution in humans: analysis of eight methods and their application in drug discovery. Xenobiotica 2019; 50:270-279. [DOI: 10.1080/00498254.2019.1625084] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Carl Petersson
- NCE DMPK, Discovery Technology, HealthCare Merck KGaA, Darmstadt, Germany
| | - Orestis Papasouliotis
- Merck Institute for Pharmacometrics (an affiliate of HealthCare Merck KGaA, Darmstadt, Germany), Lausanne, Switzerland)
| | - Marc Lecomte
- NCE DMPK, Discovery Technology, HealthCare Merck KGaA, Darmstadt, Germany
| | - Lassina Badolo
- NCE DMPK, Discovery Technology, HealthCare Merck KGaA, Darmstadt, Germany
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