A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP
The application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-01-01
|
Series: | Pharmaceutics |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4923/12/1/74 |
_version_ | 1798006407128154112 |
---|---|
author | Marival Bermejo Bart Hens Joseph Dickens Deanna Mudie Paulo Paixão Yasuhiro Tsume Kerby Shedden Gordon L. Amidon |
author_facet | Marival Bermejo Bart Hens Joseph Dickens Deanna Mudie Paulo Paixão Yasuhiro Tsume Kerby Shedden Gordon L. Amidon |
author_sort | Marival Bermejo |
collection | DOAJ |
description | The application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted outcomes. The aim of this study was to predict the systemic concentrations of ibuprofen after oral administration of an 800 mg immediate-release (IR) tablet to healthy subjects in fasted-state conditions. A mechanistic oral absorption model coupled with a two-compartmental pharmacokinetic (PK) model was built in Phoenix WinNonlinWinNonlin<sup>®</sup> software and in the GastroPlus™ simulator. It should be noted that all simulations were performed in an ideal framework as we were in possession of a plethora of in vivo data (e.g., motility, pH, luminal and systemic concentrations) in order to evaluate and optimize these models. All this work refers to the fact that important, yet crucial, gastrointestinal (GI) variables should be integrated into biopredictive dissolution testing (low buffer capacity media, considering phosphate versus bicarbonate buffer, hydrodynamics) to account for a valuable input for physiologically-based pharmacokinetic (PBPK) platform programs. While simulations can be performed and mechanistic insights can be gained from such simulations from current software, we need to move from correlations to predictions (IVIVC → IVIVP) and, moreover, we need to further determine the dynamics of the GI variables controlling the dosage form transit, disintegration, dissolution, absorption and metabolism along the human GI tract. Establishing the link between biopredictive in vitro dissolution testing and mechanistic oral absorption modeling (i.e., physiologically-based biopharmaceutics modeling (PBBM)) creates an opportunity to potentially request biowaivers in the near future for orally administered drug products, regardless of its classification according to the Biopharmaceutics Classification System (BCS). |
first_indexed | 2024-04-11T12:54:16Z |
format | Article |
id | doaj.art-a4bc408226ec492db48b0753b8ec0a6f |
institution | Directory Open Access Journal |
issn | 1999-4923 |
language | English |
last_indexed | 2024-04-11T12:54:16Z |
publishDate | 2020-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Pharmaceutics |
spelling | doaj.art-a4bc408226ec492db48b0753b8ec0a6f2022-12-22T04:23:06ZengMDPI AGPharmaceutics1999-49232020-01-011217410.3390/pharmaceutics12010074pharmaceutics12010074A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVPMarival Bermejo0Bart Hens1Joseph Dickens2Deanna Mudie3Paulo Paixão4Yasuhiro Tsume5Kerby Shedden6Gordon L. Amidon7Department of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USADepartment of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USADepartment of Statistics, University of Michigan, Ann Arbor, MI 48109, USADepartment of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USADepartment of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USADepartment of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USADepartment of Statistics, University of Michigan, Ann Arbor, MI 48109, USADepartment of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, 428 Church Street, Ann Arbor, MI 48109-1065, USAThe application of in silico modeling to predict the in vivo outcome of an oral drug product is gaining a lot of interest. Fully relying on these models as a surrogate tool requires continuous optimization and validation. To do so, intraluminal and systemic data are desirable to judge the predicted outcomes. The aim of this study was to predict the systemic concentrations of ibuprofen after oral administration of an 800 mg immediate-release (IR) tablet to healthy subjects in fasted-state conditions. A mechanistic oral absorption model coupled with a two-compartmental pharmacokinetic (PK) model was built in Phoenix WinNonlinWinNonlin<sup>®</sup> software and in the GastroPlus™ simulator. It should be noted that all simulations were performed in an ideal framework as we were in possession of a plethora of in vivo data (e.g., motility, pH, luminal and systemic concentrations) in order to evaluate and optimize these models. All this work refers to the fact that important, yet crucial, gastrointestinal (GI) variables should be integrated into biopredictive dissolution testing (low buffer capacity media, considering phosphate versus bicarbonate buffer, hydrodynamics) to account for a valuable input for physiologically-based pharmacokinetic (PBPK) platform programs. While simulations can be performed and mechanistic insights can be gained from such simulations from current software, we need to move from correlations to predictions (IVIVC → IVIVP) and, moreover, we need to further determine the dynamics of the GI variables controlling the dosage form transit, disintegration, dissolution, absorption and metabolism along the human GI tract. Establishing the link between biopredictive in vitro dissolution testing and mechanistic oral absorption modeling (i.e., physiologically-based biopharmaceutics modeling (PBBM)) creates an opportunity to potentially request biowaivers in the near future for orally administered drug products, regardless of its classification according to the Biopharmaceutics Classification System (BCS).https://www.mdpi.com/1999-4923/12/1/74oral absorptionin silico modelinggastroplusphoenix winnonlinpharmacokineticsclinical studiesibuprofenmanometrygastrointestinalmechanistic modelingpbpkpbbm |
spellingShingle | Marival Bermejo Bart Hens Joseph Dickens Deanna Mudie Paulo Paixão Yasuhiro Tsume Kerby Shedden Gordon L. Amidon A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP Pharmaceutics oral absorption in silico modeling gastroplus phoenix winnonlin pharmacokinetics clinical studies ibuprofen manometry gastrointestinal mechanistic modeling pbpk pbbm |
title | A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP |
title_full | A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP |
title_fullStr | A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP |
title_full_unstemmed | A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP |
title_short | A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP |
title_sort | mechanistic physiologically based biopharmaceutics modeling pbbm approach to assess the in vivo performance of an orally administered drug product from ivivc to ivivp |
topic | oral absorption in silico modeling gastroplus phoenix winnonlin pharmacokinetics clinical studies ibuprofen manometry gastrointestinal mechanistic modeling pbpk pbbm |
url | https://www.mdpi.com/1999-4923/12/1/74 |
work_keys_str_mv | AT marivalbermejo amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT barthens amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT josephdickens amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT deannamudie amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT paulopaixao amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT yasuhirotsume amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT kerbyshedden amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT gordonlamidon amechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT marivalbermejo mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT barthens mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT josephdickens mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT deannamudie mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT paulopaixao mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT yasuhirotsume mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT kerbyshedden mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp AT gordonlamidon mechanisticphysiologicallybasedbiopharmaceuticsmodelingpbbmapproachtoassesstheinvivoperformanceofanorallyadministereddrugproductfromivivctoivivp |