ArticlePharmaceutical research2022
In Vitro - in Vivo Extrapolation of Hepatic Clearance in Preclinical Species.
Article in Pharmaceutical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 30 citations in OpenAlex.
- Physiologically Based Pharmacokinetic Modeling to Predict Human Starting Dose and Pharmacokinetics for Rocbrutinib.Clinical and translational science · 2026Article
- High-Throughput Physiologically Based Pharmacokinetic Model for Rodent Pharmacokinetics Prediction Using Machine Learning-Predicted Inputs and a LargeMolecular pharmaceutics · 2026Article
- Target Abundance in Pharmacological Target-Mediated Drug Disposition (TMDD) for Small Molecules - A Proteomics Approach.The AAPS journal · 2026Article
- Machine learning-based unified models for predicting drug clearance from pharmacokinetic animal and study design variables.PloS one · 2026Article
- Exploiting Pharmacokinetic/Pharmacodynamic Methods for Optimizing and Accelerating Drug Development of Innovative Anti-Infectives.ChemMedChem · 2026Review
- Optimization of Species-Selective Reversible Proteasome Inhibitors for the Treatment of Malaria.Journal of medicinal chemistry · 2025Article
- Structure-Based Discovery and Development of Highly Potent Dihydroorotate Dehydrogenase Inhibitors for Malaria Chemoprevention.Journal of medicinal chemistry · 2025Article
- Identification of potent and reversible piperidine carboxamides that are species-selective orally active proteasome inhibitors to treat malaria.Cell chemical biology · 2024Article
- Data set of fraction unbound values in the in vitro incubations for metabolic studies for better prediction of human clearance.Database : the journal of biological databases and curation · 2024Article
- Characterization and Applications of Permeabilized Hepatocytes in Drug Discovery.The AAPS journal · 2024Article
- A Complete Extension of Classical Hepatic Clearance Models Using Fractional Distribution Parameter fJournal of pharmaceutical sciences · 2024Article
- Quantitative Translation of Substrate Intrinsic Clearance from Recombinant CYP1A1 to Humans.The AAPS journal · 2023Article
- Utility of Minimal Physiologically Based Pharmacokinetic Models for Assessing Fractional Distribution, Oral Absorption, and Series-Compartment Models of Hepatic Clearance.Drug metabolism and disposition: the biological fate of chemicals · 2023Article
- Exploring the inhibitory potential of novel piperidine-derivatives against main protease (MJournal of molecular liquids · 2023Article
- Assessing Boron-Pleuromutilin AN11251 for the Development of Antibacterial Agents.Molecules (Basel, Switzerland) · 2023Article
- Exploring the Pharmacokinetic Mysteries of the Liver: Application of Series Compartment Models of Hepatic Elimination.Drug metabolism and disposition: the biological fate of chemicals · 2023Article
- In Vitro-In Vivo Extrapolation and Scaling Factors for Clearance of Human and Preclinical Species with Liver Microsomes and Hepatocytes.The AAPS journal · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate prediction of human clearance is of critical importance in drug discovery. In this study, in vitro - in vivo extrapolation (IVIVE) of hepatic clearance was established using large sets of compounds for four preclinical species (mouse, rat, dog, and non-human primate) to enable better understanding of clearance mechanisms and human translation. In vitro intrinsic clearances were obtained using pooled liver microsomes (LMs) or hepatocytes (HEPs) and scaled to hepatic clearance using the parallel-tube and well-stirred models. Subsequently, IVIVE scaling factors (SFs) were derived to best predict in vivo clearance. The SFs for extended clearance classification system (ECCS) class 2/4 compounds, involving metabolic clearance, were generally small (≤ 2.6) using both LMs and HEPs with parallel-tube model, with the exception of the rodents (~ 2.4-4.6), suggesting in vitro reagents represent in vivo reasonably well. SFs for ECCS class 1A and 1B are generally higher than class 2/4 across the species, likely due to the contribution of transporter-mediated clearance that is under-represented with in vitro reagents. The parallel-tube model offered lower variability in clearance predictions over the well-stirred model. For compounds that likely demonstrate passive permeability-limited clearance in vitro, rat LM predicted in vivo clearance more accurately than HEP. This comprehensive analysis demonstrated reliable IVIVE can be achieved using LMs and HEPs. Evaluation of clearance IVIVE in preclinical species helps to better understand clearance mechanisms, establish more reliable IVIVE in human, and enhance our confidence in human clearance and PK prediction, while considering species differences in drug metabolizing enzymes and transporters.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.