First pass intestinal and liver metabolism of paracetamol in a microfluidic platform coupled with a mathematical modeling as a means of evaluating ADME processes in humans
Abstract
We developed a microfluidic platform to investigate paracetamol intestinal and liver first pass metabolism. This approach was coupled with a mathematical model to estimate intrinsic in vitro parameters and to predict in vivo processes. The kinetic modeling estimated the paracetamol and paracetamol sulfate permeabilities, the sulfate and glucuronide effluxes in the intestine compartment. Based on a gut model, we estimated intrinsic intestinal clearance of between 26 and 77 L/h for paracetamol in humans, a permeability of 10 L/h, and a gut availability between 0.17 and 0.53 (compared to 0.95—1 in vivo). The role played by the liver in paracetamol metabolism was estimated via in vitro intrinsic clearances of 7.6, 13.6, and 11.5 µL/min/10 6 cells for HepG2/C3a, rat primary hepatocytes, and human primary hepatocytes, respectively. Based on a parallel tube model to describe the liver, the paracetamol hepatic clearance, and the paracetamol hepatic availability in humans were estimated at 6.5 mL/min/kg of bodyweight (BDW) and 0.7, respectively (when compared to 5 mL/min/kg of BDW and 0.77 to 0.88 for in vivo values, respectively). The drug availability was predicted ranging between 0.24 and 0.41 (0.88 in vivo). The overall approach provided a first step in an integrated strategy combining in silico/in vitro methods based on microfluidic for evaluating drug absorption, distribution and metabolism processes. Biotechnol. Bioeng. 2014;111: 2027–2040. © 2014 Wiley Periodicals, Inc.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A number of MPSs as an in vitro GLA model (GLA-MPS) have been reported, such as GLA for metabolism and inflammation axes.
“Thus far, a number of MPSs as an in vitro GLA model (GLA-MPS) have been reported, such as GLA for metabolism and inflammation axess.3,7- 11”
From Gut-liver-axis microphysiological system for studying cellular fluidic shear stress and inter-tissue interaction (2022) · cites this paper as [3]
GLA regulates the absorption/prevention of exogenous agents at the gut barrier and metabolic processes in the liver.
“that regulates the absorption/prevention of exogenous agents at the gut barrier and metabolic processes in the liver.2,3”
From Gut-liver-axis microphysiological system for studying cellular fluidic shear stress and inter-tissue interaction (2022) · cites this paper as [3]
Reported GLA-MPSs showed better predictive capabilities of organ-to-organ interaction compared to normal static cell-culture models.
“They showed better predictive capabilities of organ to organ interaction, compared to normal static cell-culture models.”
From Gut-liver-axis microphysiological system for studying cellular fluidic shear stress and inter-tissue interaction (2022) · cites this paper as [3]
In other GLA-MPSs, the exchange ratio is approximately 0.25% to 1% in 1 min.
“In other GLA-MPSs, 3,7 the exchange ratio is approximately 0.25% to 1% in 1 min.”
From Gut-liver-axis microphysiological system for studying cellular fluidic shear stress and inter-tissue interaction (2022) · cites this paper as [3]
Cites
Pang, K. S., & Rowland, M. (1977) · Journal of Pharmacokinetics and Biopharmaceutics · doi:10.1007/bf01059688 · Cited by 797 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Interconnected Microphysiological Systems for Quantitative Biology and Pharmacology Studies
Edington, C. D., Chen, W. L. K., Geishecker, E., Kassis, T., Soenksen, L. R., Bhushan, B. M., Freake, D., Kirschner, J., Maass, C., Tsamandouras, N., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-22749-0 · Cited by 487 · see citing works
Marx, U. (2016) · ALTEX · doi:10.14573/altex.1603161 · Cited by 295 · see citing works
Tsamandouras, N., Chen, W. L. K., Edington, C. D., Stokes, C. L., Griffith, L. G., & Cirit, M. (2017) · The AAPS Journal · doi:10.1208/s12248-017-0122-4 · Cited by 222 · see citing works
Satoh, T., Sugiura, S., Shin, K., Onuki-Nagasaki, R., Ishida, S., Kikuchi, K., Kakiki, M., & Kanamori, T. (2018) · Lab on a Chip · doi:10.1039/c7lc00952f · Cited by 181 · see citing works
Prantil-Baun, R., Novak, R., Das, D., Somayaji, M. R., Przekwas, A., & Ingber, D. E. (2018) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010716-104748 · Cited by 176 · see citing works
Organ-Tumor-on-a-Chip for Chemosensitivity Assay: A Critical Review
Kashaninejad, N., Nikmaneshi, M., Moghadas, H., Kiyoumarsi Oskouei, A., Rismanian, M., Barisam, M., Saidi, M., & Firoozabadi, B. (2016) · Micromachines · doi:10.3390/mi7080130 · Cited by 79 · see citing works
Sung, J. H., Wang, Y., & Shuler, M. L. (2019) · APL Bioengineering · doi:10.1063/1.5097675 · Cited by 66 · see citing works
Farewell to Animal Testing: Innovations on Human Intestinal Microphysiological Systems
Kang, T., & Kim, H. (2016) · Micromachines · doi:10.3390/mi7070107 · Cited by 40 · see citing works
Yang, J., Hirai, Y., Imamura, S., Tsuchiya, T., Tabata, O., & Kamei, K.-I. (2022) · doi:10.1101/2022.01.31.478467 · Cited by 21 · see citing works
Myszczyszyn, A., Muench, A., Lehmann, V., Sinnige, T., van Steenbeek, F. G., Bouwmeester, M., Samsom, R.-A., Keuper-Navis, M., van der Made, T. K., Kogan, D., et al. (2025) · Biofabrication · doi:10.1088/1758-5090/adc3ce · Cited by 14 · see citing works
Boussommier-Calleja, A. (2020) · Bioengineering Innovative Solutions for Cancer · doi:10.1016/b978-0-12-813886-1.00013-9 · Cited by 10 · see citing works
- Authors
- Prot, J. M., Maciel, L., Bricks, T., Merlier, F., Cotton, J., Paullier, P., Bois, F. Y., & Leclerc, E.
- Affiliations
- CNRS UMR 7338 Laboratoire de Biomécanique et Bio ingénierie, Université de Technologie de Compiègne Compiegne Picardie France
- CNRS EA Laboratoire de Génie enzymatique et Cellulaire, Université de Technologie de Compiègne Compiegne Picardie France
- Profilomic Boulogne‐Billancourt Ile de France France
- INERIS Unité Modèles pour la toxicologie (METO) Verneuil‐en‐Halatte Picardie France
- Venue
- Biotechnology and Bioengineering
- Publisher
- Wiley
- Published
- 2014-06-24
- Volume
- 111
- Issue
- 10
- Pages
- 2027-2040
- ISSN
- 0006-3592
- 1097-0290
- Cited by
- 89
- References
- 1
- Language
- en
- Funders
- Fondation pour la Recherche et l'Innovation” from the Université de Technologie in Compiègne (ToxOnChip project)
- ERASMUS exchange program
- 189-post Grenelle program via the Activism project
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review