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Ryu S, Burchett W, Zhang S, Jia X, Modaresi SMS, Agudelo Areiza J, Rodrigues D, Zhu H, Sunderland EM, Fischer FC, Slitt AL. Unbound Fractions of PFAS in Human and Rodent Tissues: Rat Liver a Suitable Proxy for Evaluating Emerging PFAS? ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:14641-14650. [PMID: 39161261 DOI: 10.1021/acs.est.4c04050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/21/2024]
Abstract
Adverse health effects associated with exposures to perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a concern for public health and are driven by their elimination half-lives and accumulation in specific tissues. However, data on PFAS binding in human tissues are limited. Accumulation of PFAS in human tissues has been linked to interactions with specific proteins and lipids in target organs. Additional data on PFAS binding and unbound fractions (funbound) in whole human tissues are urgently needed. Here, we address this gap by using rapid equilibrium dialysis to measure the binding and funbound of 16 PFAS with 3 to 13 perfluorinated carbon atoms (ηpfc = 3-13) and several functional headgroups in human liver, lung, kidney, heart, and brain tissue. We compare results to mouse (C57BL/6 and CD-1) and rat tissues. Results show that funbound decreases with increasing fluorinated carbon chain length and hydrophobicity. Among human tissues, PFAS binding was generally greatest in brain > liver ≈ kidneys ≈ heart > lungs. A correlation analysis among human and rodent tissues identified rat liver as a suitable surrogate for predicting funbound for PFAS in human tissues (R2 ≥ 0.98). The funbound data resulting from this work and the rat liver prediction method offer input parameters and tools for toxicokinetic models for legacy and emerging PFAS.
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Affiliation(s)
- Sangwoo Ryu
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, Rhode Island 02881, United States
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Incorporated, Groton, Connecticut 06340, United States
| | - Woodrow Burchett
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Incorporated, Groton, Connecticut 06340, United States
| | - Sam Zhang
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Incorporated, Groton, Connecticut 06340, United States
| | - Xuelian Jia
- Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States
- Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, Louisiana 70112, United States
| | - Seyed Mohamad Sadegh Modaresi
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, Rhode Island 02881, United States
| | - Juliana Agudelo Areiza
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, Rhode Island 02881, United States
| | - David Rodrigues
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Incorporated, Groton, Connecticut 06340, United States
| | - Hao Zhu
- Department of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States
- Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, Louisiana 70112, United States
| | - Elsie M Sunderland
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Fabian Christoph Fischer
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, Rhode Island 02881, United States
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Angela L Slitt
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, Rhode Island 02881, United States
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Pihlaja T, Oksanen T, Vinkvist N, Sikanen T. Many human pharmaceuticals are weak inhibitors of the cytochrome P450 system in rainbow trout ( Oncorhynchus mykiss) liver S9 fractions. FRONTIERS IN TOXICOLOGY 2024; 6:1406942. [PMID: 39077557 PMCID: PMC11284600 DOI: 10.3389/ftox.2024.1406942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 06/14/2024] [Indexed: 07/31/2024] Open
Abstract
Introduction Pharmaceutical residues are widely detected in aquatic environment and can be taken up by nontarget species such as fish. The cytochromes P450 (CYP) represent an important detoxification mechanism in fish, like in humans. In the present study, we assessed the correlation of the substrate selectivities of rainbow trout CYP1A and CYP3A homologues with those of human, through determination of the half-maximal inhibitory concentrations (IC50) of a total sixteen human pharmaceuticals toward CYP1A-like ethoxyresorufin O-deethylase (EROD) and CYP3A-like 7-benzyloxy-4-trifluoromethylcoumarin O-debenzylase (BFCOD) in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (RT-S9). Methods The inhibitory impacts (IC50) of atomoxetine, atorvastatin, azelastine, bimatoprost, clomethiazole, clozapine, desloratadine, disulfiram, esomeprazole, felbinac, flecainide, orphenadrine, prazosin, quetiapine, sulpiride, and zolmitriptan toward the EROD and BFCOD activities in RT-S9 were determined using the IC50 shift assay, capable of identifying time-dependent inhibitors (TDI). Additionally, the nonspecific binding of the test pharmaceuticals to RT-S9 was assessed using equilibrium dialysis. Results Most test pharmaceuticals were moderate to weak inhibitors of both EROD and BFCOD activity in RT-S9, even if most are noninhibitors of human CYP1A or CYP3A. Only bimatoprost, clomethiazole, felbinac, sulpiride, and zolmitriptan did not inhibit either activity in RT-S9. EROD inhibition was generally stronger than that of BFCOD and some substances (atomoxetine, flecainide, and prazosin) inhibited selectively only EROD activity. The strongest EROD inhibition was detected with azelastine and esomeprazole (unbound IC50 of 3.8 ± 0.5 µM and 3.0 ± 0.8 µM, respectively). None of the test substances were TDIs of BFCOD, but esomeprazole was a TDI of EROD. Apart from clomethiazole and disulfiram, the nonspecific binding of the test pharmaceuticals to the RT-S9 was extensive (unbound fractions <0.5) and correlated well (R 2 = 0.7135) with their water-octanol distribution coefficients. Discussion The results indicate that the P450 interactions in RT-S9 cannot be explicitly predicted based on human data, but the in vitro data reported herein can shed light on the substrate selectivity of rainbow trout CYP1A1 and CYP3A27 in comparison to their human homologues. The IC50 concentrations are however many orders of magnitude higher than average environmental concentrations of pharmaceuticals. The time-dependent EROD inhibition by esomeprazole could warrant further research to evaluate its possible interlinkages with hepatotoxic impacts on fish.
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Affiliation(s)
- Tea Pihlaja
- Faculty of Pharmacy, Drug Research Program, University of Helsinki, Helsinki, Finland
- Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, Finland
| | - Timo Oksanen
- Faculty of Pharmacy, Drug Research Program, University of Helsinki, Helsinki, Finland
| | - Netta Vinkvist
- Faculty of Pharmacy, Drug Research Program, University of Helsinki, Helsinki, Finland
| | - Tiina Sikanen
- Faculty of Pharmacy, Drug Research Program, University of Helsinki, Helsinki, Finland
- Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, Finland
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Ja’afaru SC, Uzairu A, Bayil I, Sallau MS, Ndukwe GI, Ibrahim MT, Moin AT, Mollah AKMM, Absar N. Unveiling potent inhibitors for schistosomiasis through ligand-based drug design, molecular docking, molecular dynamics simulations and pharmacokinetics predictions. PLoS One 2024; 19:e0302390. [PMID: 38923997 PMCID: PMC11207139 DOI: 10.1371/journal.pone.0302390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 04/02/2024] [Indexed: 06/28/2024] Open
Abstract
Schistosomiasis is a neglected tropical disease which imposes a considerable and enduring impact on affected regions, leading to persistent morbidity, hindering child development, diminishing productivity, and imposing economic burdens. Due to the emergence of drug resistance and limited management options, there is need to develop additional effective inhibitors for schistosomiasis. In view of this, quantitative structure-activity relationship studies, molecular docking, molecular dynamics simulations, drug-likeness and pharmacokinetics predictions were applied to 39 Schistosoma mansoni Thioredoxin Glutathione Reductase (SmTGR) inhibitors. The chosen QSAR model demonstrated robust statistical parameters, including an R2 of 0.798, R2adj of 0.767, Q2cv of 0.681, LOF of 0.930, R2test of 0.776, and cR2p of 0.746, confirming its reliability. The most active derivative (compound 40) was identified as a lead candidate for the development of new potential non-covalent inhibitors through ligand-based design. Subsequently, 12 novel compounds (40a-40l) were designed with enhanced anti-schistosomiasis activity and binding affinity. Molecular docking studies revealed strong and stable interactions, including hydrogen bonding, between the designed compounds and the target receptor. Molecular dynamics simulations over 100 nanoseconds and MM-PBSA free binding energy (ΔGbind) calculations validated the stability of the two best-designed molecules. Furthermore, drug-likeness and pharmacokinetics prediction analyses affirmed the potential of these designed compounds, suggesting their promise as innovative agents for the treatment of schistosomiasis.
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Affiliation(s)
- Saudatu Chinade Ja’afaru
- Department of Chemistry Ahmadu Bello University Zaria, Zaria, Nigeria
- Department of Chemistry, Aliko Dangote University of Science and Technology, Wudil, Kano, Nigeria
| | - Adamu Uzairu
- Department of Chemistry Ahmadu Bello University Zaria, Zaria, Nigeria
| | - Imren Bayil
- Department of Bioinformatics and Computational Biology, Gaziantep University, Gaziantep, Turkey
| | | | | | | | - Abu Tayab Moin
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chattogram, Bangladesh
| | | | - Nurul Absar
- Department of Biochemistry and Biotechnology, Faculty of Basic Medical and Pharmaceutical Sciences, University of Science & Technology Chittagong, Khulshi, Chittagong, Bangladesh
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Wang M, Kuldharan S, Shenoy A, Reddy S, Rex K, Osgood T, Wahlstrom J, Dahal UP. Xenografted Tumors Share Comparable Fraction Unbound and Can Be Surrogated by Mouse Lung Tissue. Drug Metab Dispos 2024; 52:644-653. [PMID: 38670798 DOI: 10.1124/dmd.124.001698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 04/21/2024] [Accepted: 04/24/2024] [Indexed: 04/28/2024] Open
Abstract
Free (unbound) drug concentration at the site of action is the key determinant of biologic activity since only unbound drugs can exert pharmacological and toxicological effects. Unbound drug concentration in tumors for solid cancers is needed to understand/explain/predict pharmacokinetics, pharmacodynamics, and efficacy relations. Fraction unbound (fu ) in tumors is usually determined across several xenografted tumors derived from various cell lines in the drug discovery stage, which is time consuming and a resource burden. In this study, we determined the fu values for a set of diverse compounds (comprising acid, base, neutral, zwitterion, and covalent drugs) across five different xenografted tumors and five commercially available mouse tissues to explore the correlation of fu between tumors and the possibility of surrogate tissue(s) for tumor fu (fu,tumor) determination. The crosstumor comparison showed that fu,tumor values across tumors are largely comparable, and systematic tissue versus tumor comparison demonstrated that only lung tissue had comparable fu to all five tumors (fu values within twofold change for >80% compounds in both comparisons). These results indicated that mouse lung tissue can be used as a surrogate matrix for a fu,tumor assay. This study will increase efficiency in fu,tumor assessment and reduce animal use (adapting the replace, reduce, and refine principle) in drug discovery. SIGNIFICANCE STATEMENT: The free drug concept is a well accepted principle in drug discovery research. Currently, tumor fraction unbound (fu,tumor) is determined in several tumors derived from different cell lines to estimate free drug concentrations of a compound. The results from this study indicated that fu,tumor across xenografted tumors is comparable, and fu,tumor can be estimated using a surrogate tissue, mouse lung. The results will increase efficiency in fu,tumor assessment and reduce animal use in drug discovery.
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Affiliation(s)
- Min Wang
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Sandip Kuldharan
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Aravind Shenoy
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Satyanarayana Reddy
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Karen Rex
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Tao Osgood
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Jan Wahlstrom
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
| | - Upendra P Dahal
- Pharmacokinetics and Drug Metabolism, Amgen Inc., South San Francisco, California (M.W., U.P.D.); Pharmacokinetics and Drug Metabolism, Syngene Amgen Research & Development Center, Bangalore, India (S.K., A.S., S.R.); and Amgen Research (K.R., T.O.) and Pharmacokinetics and Drug Metabolism (J.W.), Amgen Inc., Thousand Oaks, California
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Ryu S, Burchett W, Zhang S, Modaresi SMS, Agudelo Areiza J, Kaye E, Fischer FC, Slitt AL. Species-Specific Unbound Fraction Differences in Highly Bound PFAS: A Comparative Study across Human, Rat, and Mouse Plasma and Albumin. TOXICS 2024; 12:253. [PMID: 38668476 PMCID: PMC11054487 DOI: 10.3390/toxics12040253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/17/2024] [Accepted: 03/22/2024] [Indexed: 04/29/2024]
Abstract
Per- and polyfluoroalkyl substances (PFAS) are a diverse group of fluorinated compounds which have yet to undergo comprehensive investigation regarding potential adverse health effects and bioaccumulative properties. With long half-lives and accumulative properties, PFAS have been linked to several toxic effects in both non-clinical species such as rat and mouse as well as human. Although biological impacts and specific protein binding of PFAS have been examined, there is no study focusing on the species-specific fraction unbound (fu) in plasma and related toxicokinetics. Herein, a presaturation equilibrium dialysis method was used to measure and validate the binding of 14 individual PFAS with carbon chains containing 4 to 12 perfluorinated carbon atoms and several functional head-groups to albumin and plasma of mouse (C57BL/6 and CD-1), rat, and human. Equivalence testing between each species-matrix combination showed positive correlation between rat and human when comparing fu in plasma and binding to albumin. Similar trends in binding were also observed for mouse plasma and albumin. Relatively high Spearman correlations for all combinations indicate high concordance of PFAS binding regardless of matrix. Physiochemical properties of PFAS such as molecular weight, chain length, and lipophilicity were found to have important roles in plasma protein binding of PFAS.
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Affiliation(s)
- Sangwoo Ryu
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI 02881, USA; (S.R.); (S.M.S.M.); (J.A.A.); (E.K.)
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Inc., Groton, CT 06340, USA; (W.B.); (S.Z.)
| | - Woodrow Burchett
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Inc., Groton, CT 06340, USA; (W.B.); (S.Z.)
| | - Sam Zhang
- Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research & Development, Pfizer Inc., Groton, CT 06340, USA; (W.B.); (S.Z.)
| | - Seyed Mohamad Sadegh Modaresi
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI 02881, USA; (S.R.); (S.M.S.M.); (J.A.A.); (E.K.)
| | - Juliana Agudelo Areiza
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI 02881, USA; (S.R.); (S.M.S.M.); (J.A.A.); (E.K.)
| | - Emily Kaye
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI 02881, USA; (S.R.); (S.M.S.M.); (J.A.A.); (E.K.)
| | - Fabian Christoph Fischer
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI 02881, USA; (S.R.); (S.M.S.M.); (J.A.A.); (E.K.)
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Angela L. Slitt
- Department of Biomedical and Pharmaceutical Sciences, University of Rhode Island, Kingston, RI 02881, USA; (S.R.); (S.M.S.M.); (J.A.A.); (E.K.)
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Pardridge WM. Physiologically Based Pharmacokinetic Model of Brain Delivery of Plasma Protein Bound Drugs. Pharm Res 2023; 40:661-674. [PMID: 36829100 PMCID: PMC10036418 DOI: 10.1007/s11095-023-03484-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/10/2023] [Indexed: 02/26/2023]
Abstract
INTRODUCTION A physiologically based pharmacokinetic (PBPK) model is developed that focuses on the kinetic parameters of drug association and dissociation with albumin, alpha-1 acid glycoprotein (AGP), and brain tissue proteins, as well as drug permeability at the blood-brain barrier, drug metabolism, and brain blood flow. GOAL The model evaluates the extent to which plasma protein-mediated uptake (PMU) of drugs by brain influences the concentration of free drug both within the brain capillary compartment in vivo and the brain compartment. The model also studies the effect of drug binding to brain tissue proteins on the concentration of free drug in brain. METHODS The steady state and non-steady state PBPK models are comprised of 11-12 variables, and 18-23 parameters, respectively. Two model drugs are analyzed: propranolol, which undergoes modest PMU from the AGP-bound pool, and imipramine, which undergoes a high degree of PMU from both the albumin-bound and AGP-bound pools in plasma. RESULTS The free propranolol concentration in brain is under-estimated 2- to fourfold by in vitro measurements of free plasma propranolol, and the free imipramine concentration in brain is under-estimated by 18- to 31-fold by in vitro measurements of free imipramine in plasma. The free drug concentration in brain in vivo is independent of drug binding to brain tissue proteins. CONCLUSIONS In vitro measurement of free drug concentration in plasma under-estimates the free drug in brain in vivo if PMU in vivo from either the albumin and/or the AGP pools in plasma takes place at the BBB surface.
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Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction. Int J Mol Sci 2023; 24:ijms24031815. [PMID: 36768139 PMCID: PMC9915725 DOI: 10.3390/ijms24031815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 01/19/2023] Open
Abstract
Drug distribution is an important process in pharmacokinetics because it has the potential to influence both the amount of medicine reaching the active sites and the effectiveness as well as safety of the drug. The main causes of 90% of drug failures in clinical development are lack of efficacy and uncontrolled toxicity. In recent years, several advances and promising developments in drug distribution property prediction have been achieved, especially in silico, which helped to drastically reduce the time and expense of screening undesired drug candidates. In this study, we provide comprehensive knowledge of drug distribution background, influencing factors, and artificial intelligence-based distribution property prediction models from 2019 to the present. Additionally, we gathered and analyzed public databases and datasets commonly utilized by the scientific community for distribution prediction. The distribution property prediction performance of five large ADMET prediction tools is mentioned as a benchmark for future research. On this basis, we also offer future challenges in drug distribution prediction and research directions. We hope that this review will provide researchers with helpful insight into distribution prediction, thus facilitating the development of innovative approaches for drug discovery.
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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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Petersson C, Zhou X, Berghausen J, Cebrian D, Davies M, DeMent K, Eddershaw P, Riedmaier AE, Leblanc AF, Manveski N, Marathe P, Mavroudis PD, McDougall R, Parrott N, Reichel A, Rotter C, Tess D, Volak LP, Xiao G, Yang Z, Baker J. Current Approaches for Predicting Human PK for Small Molecule Development Candidates: Findings from the IQ Human PK Prediction Working Group Survey. AAPS J 2022; 24:85. [DOI: 10.1208/s12248-022-00735-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/05/2022] [Indexed: 11/30/2022] Open
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Hernandez‐Jerez AF, Adriaanse P, Aldrich A, Berny P, Coja T, Duquesne S, Focks A, Marinovich M, Millet M, Pelkonen O, Pieper S, Tiktak A, Topping CJ, Widenfalk A, Wilks M, Wolterink G, Gundert‐Remy U, Louisse J, Rudaz S, Testai E, Lostia A, Dorne J, Parra Morte JM. Scientific Opinion of the Scientific Panel on Plant Protection Products and their Residues (PPR Panel) on testing and interpretation of comparative in vitro metabolism studies. EFSA J 2021; 19:e06970. [PMID: 34987623 PMCID: PMC8696562 DOI: 10.2903/j.efsa.2021.6970] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
EFSA asked the Panel on Plant Protection Products and their residues to deliver a Scientific Opinion on testing and interpretation of comparative in vitro metabolism studies for both new active substances and existing ones. The main aim of comparative in vitro metabolism studies of pesticide active substances is to evaluate whether all significant metabolites formed in the human in vitro test system, as a surrogate of the in vivo situation, are also present at comparable level in animal species tested in toxicological studies and, therefore, if their potential toxicity has been appropriately covered by animal studies. The studies may also help to decide which animal model, with regard to a particular compound, is the most relevant for humans. In the experimental strategy, primary hepatocytes in suspension or culture are recommended since hepatocytes are considered the most representative in vitro system for prediction of in vivo metabolites. The experimental design of 3 × 3 × 3 (concentrations, time points, technical replicates, on pooled hepatocytes) will maximise the chance to identify unique (UHM) and disproportionate (DHM) human metabolites. When DHM and UHM are being assessed, test item-related radioactivity recovery and metabolite profile are the most important parameters. Subsequently, structural characterisation of the assigned metabolites is performed with appropriate analytical techniques. In toxicological assessment of metabolites, the uncertainty factor approach is the first alternative to testing option, followed by new approach methodologies (QSAR, read-across, in vitro methods), and only if these fail, in vivo animal toxicity studies may be performed. Knowledge of in vitro metabolites in human and animal hepatocytes would enable toxicological evaluation of all metabolites of concern, and, furthermore, add useful pieces of information for detection and evaluation of metabolites in different matrices (crops, livestock, environment), improve biomonitoring efforts via better toxicokinetic understanding, and ultimately, develop regulatory schemes employing physiologically based or physiology-mimicking in silico and/or in vitro test systems to anticipate the exposure of humans to potentially hazardous substances in plant protection products.
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