Establishment of a clinically relevant specification for dissolution testing using physiologically based pharmacokinetic (PBPK) modeling approaches

Kato, Takafumi; Mikkaichi, Tsuyoshi; Miyano, Takuya; Matsumoto, Yoshiaki; Ando, Shuichi

doi:10.1016/j.ejpb.2020.03.012

Cited by 28 publications

(16 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Dn ST (13) where k tr, ST is the gastric transit rate constant (= 1/T ST ). From Equations ( 12) and ( 13), an approximate solution for Fd ST for general cases can be derived as,…”

Section: Fraction Dissolved In the Stomachmentioning

confidence: 99%

See 1 more Smart Citation

Bottom-Up Physiologically Based Oral Absorption Modeling of Free Weak Base Drugs

et al. 2020

View full text Add to dashboard Cite

In this study, we systematically evaluated “bottom-up” physiologically based oral absorption modeling, focusing on free weak base drugs. The gastrointestinal unified theoretical framework (the GUT framework) was employed as a simple and transparent model. The oral absorption of poorly soluble free weak base drugs is affected by gastric pH. Alternation of bulk and solid surface pH by dissolving drug substances was considered in the model. Simple physicochemical properties such as pKa, the intrinsic solubility, and the bile micelle partition coefficient were used as input parameters. The fraction of a dose absorbed (Fa) in vivo was obtained by reanalyzing the pharmacokinetic data in the literature (15 drugs, a total of 85 Fa data). The AUC ratio with/without a gastric acid-reducing agent (AUCr) was collected from the literature (22 data). When gastric dissolution was neglected, Fa was underestimated (absolute average fold error (AAFE) = 1.85, average fold error (AFE) = 0.64). By considering gastric dissolution, predictability was improved (AAFE = 1.40, AFE = 1.04). AUCr was also appropriately predicted (AAFE = 1.54, AFE = 1.04). The Fa values of several drugs were slightly overestimated (less than 1.7-fold), probably due to neglecting particle growth in the small intestine. This modeling strategy will be of great importance for drug discovery and development.

show abstract

“…Dn ST (13) where k tr, ST is the gastric transit rate constant (= 1/T ST ). From Equations ( 12) and ( 13), an approximate solution for Fd ST for general cases can be derived as,…”

Section: Fraction Dissolved In the Stomachmentioning

confidence: 99%

“…Physiologically based pharmacokinetic (PBPK) modeling has been anticipated to be a powerful tool to improve the productivity of drug discovery and development [ 11 ]. There have been many case studies of oral absorption PBPK modeling [ 12 , 13 , 14 , 15 , 16 ]. However, case studies are prone to publication bias.…”

Section: Introductionmentioning

confidence: 99%

Bottom-Up Physiologically Based Oral Absorption Modeling of Free Weak Base Drugs

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In the application of the method in the study of formulations in the comparison of different formulations, Kato et al (2020) evaluated three formulations, A, B, and C, and their PK in oral use. They noted differences between the developed batches, including those that were not bioequivalent.…”

Section: Gastroplus™mentioning

confidence: 99%

Application of in silico methods in clinical research and development of drugs and their formulation: A scoping review

Colli¹,

Cabral²,

Matos³

et al. 2022

J App Pharm Sc

View full text Add to dashboard Cite

The drug regularization process involves many steps that are complex and time-consuming. The demand for new drugs has prompted researchers and regulatory authorities to search for predictive methods that can streamline the development process. Current studies point to innovative computational techniques in a drug's study phases. This study aims to carry out a scoping review of research involving the application of computational methods and in silico studies in the clinical research and development of new drugs. A scoping review was conducted according to the eferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. Online databases from 2001 to 2021 in English were used and the trial registration was 10.17605/OSF.IO/USXCM. The development of protocols and the application of a computational method for researching new drugs and their formulation, published in a peer-reviewed journal, were included. The data extraction and analysis were performed by two independent reviewers. In this study, 312 articles were retrieved, of which 6 were duplicates. After the title was read, only 101 remained for analysis. After the abstracts were read, 34 papers were considered for the scoping review. The use of in silico methodologies has been expanding in terms of research into the development of new drugs and the improvement of existing products.

show abstract

“…Certainly indeed, VBE can also be applied to optimize and waive the bioavailability/bioequivalence studies of innovative drugs . This approach has been broadly applied to support drug development at various stages including but not only limited to (1) informing final formulation specifications such as clinically relevant dissolution standard or particle size standard; − (2) evaluating the influence of pharmaceutical changes (e.g., changing the manufacturing site or formulation specification); , (3) assessing the food effect; (4) waiving specific clinical trials; , and (5) establishing new BE assessment metrics …”

Section: Introductionmentioning

confidence: 99%

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Zhang

Wu³

et al. 2022

Mol. Pharmaceutics

View full text Add to dashboard Cite

To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1−4 were selected. A VBE model (i.e., a physiologically based pharmacokinetic model integrated with dissolution data) based on a B 2 O simulator was applied for pharmacokinetic (PK) prediction in a virtual population. Parameter sensitivity analysis was used for input parameter selection. The predictive performances of PK parameters (i.e., AUC 0−t , C max , and T max ), PK profiles, and bioequivalence (BE) results were evaluated using the twofold error, average fold error (AFE), absolute average fold error (AAFE), and BE reassessment metrics. All models successfully simulated the mean PK profiles, with AAFE < 2 and AFE ranging from 0.58 to 1.66. As for the PK parameters, except for the time of peak concentration, T max , of isosorbide mononitrate, other simulated PK parameters were all within a twofold error. The simulated PK behaviors were comparable to the observed ones, both for test (T) and reference (R) products, and the simulated T/R arithmetic mean ratios were all within 0.88−1.16 of the observed values. These four evaluation metrics were distributed equally among BCS class 1−4 drugs. The VBE model showed powerful performance to predict the PK behavior of orally administered drugs with various combinations of solubility and permeability, irrespective of the BCS category.

show abstract

Establishment of a clinically relevant specification for dissolution testing using physiologically based pharmacokinetic (PBPK) modeling approaches

Cited by 28 publications

References 28 publications

Bottom-Up Physiologically Based Oral Absorption Modeling of Free Weak Base Drugs

Bottom-Up Physiologically Based Oral Absorption Modeling of Free Weak Base Drugs

Application of in silico methods in clinical research and development of drugs and their formulation: A scoping review

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Contact Info

Product

Resources

About