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Di L. Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds. Expert Opin Drug Discov 2023; 18:1209-1219. [PMID: 37526497 DOI: 10.1080/17460441.2023.2238606] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 07/17/2023] [Indexed: 08/02/2023]
Abstract
INTRODUCTION Low metabolic clearance is usually a highly desirable property of drug candidates in order to reduce dose and dosing frequency. However, measurement of low clearance can be challenging in drug discovery. A number of new tools have recently been developed to address the gaps in the measurement of intrinsic clearance, identification of metabolites, and reaction phenotyping of low clearance compounds. AREAS COVERED The new methodologies of low clearance measurements are discussed, including the hepatocyte relay, HepatoPac®, HμREL®, and spheroid systems. In addition, metabolite formation rate determination and in vivo allometric scaling approaches are covered as alternative methods for low clearance measurements. With these new methods, measurement of ~ 20-fold lower limit of intrinsic clearance can be achieved. The advantages and limitations of each approach are highlighted. EXPERT OPINION Although several novel methods have been developed in recent years to address the challenges of low clearance, these assays tend to be time and labor intensive and costly. Future innovations focusing on developing systems with high enzymatic activities, ultra-sensitive universal quantifiable detectors, and artificial intelligence will further enhance our ability to explore the low clearance space.
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Affiliation(s)
- Li Di
- Research Fellow, Pharmacokinetics, Dynamics and Metabolism, Pfizer Worldwide Research and Development, Groton, CT, USA
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Grebenyuk S, Abdel Fattah AR, Kumar M, Toprakhisar B, Rustandi G, Vananroye A, Salmon I, Verfaillie C, Grillo M, Ranga A. Large-scale perfused tissues via synthetic 3D soft microfluidics. Nat Commun 2023; 14:193. [PMID: 36635264 PMCID: PMC9837048 DOI: 10.1038/s41467-022-35619-1] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 12/13/2022] [Indexed: 01/14/2023] Open
Abstract
The vascularization of engineered tissues and organoids has remained a major unresolved challenge in regenerative medicine. While multiple approaches have been developed to vascularize in vitro tissues, it has thus far not been possible to generate sufficiently dense networks of small-scale vessels to perfuse large de novo tissues. Here, we achieve the perfusion of multi-mm3 tissue constructs by generating networks of synthetic capillary-scale 3D vessels. Our 3D soft microfluidic strategy is uniquely enabled by a 3D-printable 2-photon-polymerizable hydrogel formulation, which allows for precise microvessel printing at scales below the diffusion limit of living tissues. We demonstrate that these large-scale engineered tissues are viable, proliferative and exhibit complex morphogenesis during long-term in-vitro culture, while avoiding hypoxia and necrosis. We show by scRNAseq and immunohistochemistry that neural differentiation is significantly accelerated in perfused neural constructs. Additionally, we illustrate the versatility of this platform by demonstrating long-term perfusion of developing neural and liver tissue. This fully synthetic vascularization platform opens the door to the generation of human tissue models at unprecedented scale and complexity.
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Affiliation(s)
- Sergei Grebenyuk
- Laboratory of Bioengineering and Morphogenesis, Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium.
| | - Abdel Rahman Abdel Fattah
- Laboratory of Bioengineering and Morphogenesis, Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Manoj Kumar
- Stem Cell Institute Leuven and Department of Development and Regeneration, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Burak Toprakhisar
- Stem Cell Institute Leuven and Department of Development and Regeneration, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Gregorius Rustandi
- Laboratory of Bioengineering and Morphogenesis, Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Anja Vananroye
- Laboratory of Soft Matter, Rheology and Technology, Department of Chemical Engineering, KU Leuven, Leuven, Belgium
| | - Idris Salmon
- Laboratory of Bioengineering and Morphogenesis, Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
| | - Catherine Verfaillie
- Stem Cell Institute Leuven and Department of Development and Regeneration, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Mark Grillo
- Grillo Consulting Inc., San Francisco, CA, USA
| | - Adrian Ranga
- Laboratory of Bioengineering and Morphogenesis, Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium.
- Leuven Brain Institute, KU Leuven, Leuven, Belgium.
- Leuven Institute for Single Cell Omics, KU Leuven, Leuven, Belgium.
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Klammers F, Goetschi A, Ekiciler A, Walter I, Parrott N, Fowler S, Umehara K. Estimation of Fraction Metabolized by Cytochrome P450 Enzymes Using Long-Term Cocultured Human Hepatocytes. Drug Metab Dispos 2022; 50:566-575. [PMID: 35246464 DOI: 10.1124/dmd.121.000765] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 02/25/2022] [Indexed: 11/22/2022] Open
Abstract
Estimation of the fraction of a drug metabolized by individual hepatic CYP enzymes relative to hepatic metabolism (fm,CYP) or total clearance h as been challenging for low turnover compounds due to insufficient resolution of the intrinsic clearance (CLint) measurement in vitro and difficulties in quantifying the formation of low abundance metabolites. To overcome this gap, inhibition of drug depletion or selective metabolite formation for 7 marker CYP substrates was investigated using chemical inhibitors and a micro-patterned hepatocyte coculture system (HepatoPac). The use of 3 μM itraconazole was successfully validated for estimation of fm,CYP3A4 by demonstration of fm values within a 2-fold of in vivo estimates for 10 out of 13 CYP3A4 substrates in a reference set of marketed drugs. Other CYP3A4 inhibitors (ketoconazole and posaconazole) were not optimal for estimation of fm,CYP3A4 for low turnover compounds due to their high CLint. The current study also demonstrated that selective inhibition sufficient for fm calculation was achieved by inhibitors of CYP1A2 (20 μM furafylline), CYP2C8 (40 μM montelukast), CYP2C9 (40 μM sulfaphenazole), CYP2C19 [3 μM (-)N-3-benzyl-phenobarbital], and CYP2D6 (5 μM quinidine). Good estimation of fm,CYP2B6 was not possible in this study due to the poor selectivity of the tested inhibitor (20 μM ticlopidine). The approach verified in this study can result in an improved fm estimation that is aligned with the regulatory agencies' guidance and can support a victim drug-drug interaction risk assessment strategy for low clearance discovery and development drug candidates. SIGNIFICANCE STATEMENT: Successful qualification of a chemical inhibition assay for estimation of fraction metabolized requires chemical inhibitors that retain sufficient unbound concentrations over time in the incubates. The current cocultured hepatocyte assay enabled estimation of fraction metabolized, especially by CYP3A4, during the drug discovery phase where metabolite quantification methods may not be available. The method enables the assessment of pharmacokinetic variability and victim drug-drug interaction risks due to enzyme polymorphism or inhibition/induction with more confidence, especially for low clearance drug candidates.
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Affiliation(s)
- Florian Klammers
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Andreas Goetschi
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Aynur Ekiciler
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Isabelle Walter
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Neil Parrott
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Stephen Fowler
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Kenichi Umehara
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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Docci L, Klammers F, Ekiciler A, Molitor B, Umehara K, Walter I, Krähenbühl S, Parrott N, Fowler S. In Vitro to In Vivo Extrapolation of Metabolic Clearance for UGT Substrates Using Short-Term Suspension and Long-Term Co-cultured Human Hepatocytes. AAPS JOURNAL 2020; 22:131. [DOI: 10.1208/s12248-020-00482-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 07/10/2020] [Indexed: 01/08/2023]
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Umehara K, Cantrill C, Wittwer MB, Di Lenarda E, Klammers F, Ekiciler A, Parrott N, Fowler S, Ullah M. Application of the Extended Clearance Classification System (ECCS) in Drug Discovery and Development: Selection of Appropriate In Vitro Tools and Clearance Prediction. Drug Metab Dispos 2020; 48:849-860. [PMID: 32739889 DOI: 10.1124/dmd.120.000133] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 07/20/2020] [Indexed: 12/17/2022] Open
Abstract
In vitro to in vivo extrapolation (IVIVE) to predict human hepatic clearance, including metabolism and transport, requires extensive experimental resources. In addition, there may be technical challenges to measure low clearance values. Therefore, prospective identification of rate-determining step(s) in hepatic clearance through application of the Extended Clearance Classification System (ECCS) could be beneficial for optimal compound characterization. IVIVE for hepatic intrinsic clearance (CLint,h) prediction is conducted for a set of 36 marketed drugs with low-to-high in vivo clearance, which are substrates of metabolic enzymes and active uptake transporters in the liver. The compounds were assigned to the ECCS classes, and CLint,h, estimated with HepatoPac (a micropatterned hepatocyte coculture system), was compared with values calculated based on suspended hepatocyte incubates. An apparent permeability threshold (apical to basal) of 50 nm/s in LLC-PK1 cells proved optimal for ECCS classification. A reasonable performance of the IVIVE for compounds across multiple classes using HepatoPac was achieved (with 2-3-fold error), except for substrates of uptake transporters (class 3b), for which scaling of uptake clearance using plated hepatocytes is more appropriate. Irrespective of the ECCS assignment, metabolic clearance can be estimated well using HepatoPac. The validation and approach elaborated in the present study can result in proposed decision trees for the selection of the optimal in vitro assays guided by ECCS class assignment, to support compound optimization and candidate selection. SIGNIFICANCE STATEMENT: Characterization of the rate-determining step(s) in hepatic elimination could be on the critical path of compound optimization during drug discovery. This study demonstrated that HepatoPac and plated hepatocytes are suitable tools for the estimation of metabolic and active uptake clearance, respectively, for a larger set of marketed drugs, supporting a comprehensive strategy to select optimal in vitro tools and to achieve Extended Clearance Classification System-dependent in vitro to in vivo extrapolation for human clearance prediction.
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Affiliation(s)
- Kenichi Umehara
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Carina Cantrill
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Matthias Beat Wittwer
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Elisa Di Lenarda
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Florian Klammers
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Aynur Ekiciler
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Neil Parrott
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Stephen Fowler
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
| | - Mohammed Ullah
- Pharmaceutical Sciences, Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Basel, Switzerland
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