Evidence map›Paper›PMID 35086847›Full record

ArticleDrug metabolism and disposition: the biological fate of chemicals2022

Does Addition of Protein to Hepatocyte or Microsomal In Vitro Incubations Provide a Useful Improvement in In Vitro-In Vivo Extrapolation Predictability?

Tsubasa Kameyama, Jasleen K Sodhi, Leslie Z Benet

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in Drug metabolism and disposition: the biological fate of chemicals, 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 30% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Response to the commentary on "are all measures of liver KpEuropean journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2025
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Tsubasa KameyamaDepartment of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California.
Jasleen K SodhiDepartment of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California.
Leslie Z BenetDepartment of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California leslie.benet@ucsf.edu.
University of California, San Francisco · US

Funding

UCSF Liver Core CenterP30DK026743 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Holger Willenbring · 1986 to 2026
$30.7M
Maximizing Opportunities for Research Excellence - Evaluation Training SupplementR25GM056847 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DUNCAN, D'ANNE S., SELLO, JASON K · 1998 to 2023
$14.1M
PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
NIDDK NIH HHS P30 DK026743NIGMS NIH HHS T32 GM007175
6 · The paper itself

Abstract

Accurate prediction of in vivo hepatic clearance is an essential part of successful and efficient drug development; however, many investigators have recognized that there are significant limitations in the predictability of clearance with a tendency for underprediction for primarily metabolized drugs. Here, we examine the impact of adding serum or albumin into hepatocyte and microsomal incubations on the predictability of in vivo hepatic clearance. The addition of protein into hepatocyte incubations has been reported to improve the predictability for high clearance (extraction ratio) drugs and highly protein-bound drugs. Analyzing published data for 60 different drugs and 97 experimental comparisons (with 17 drugs being investigated from two to seven) we confirmed the marked underprediction of clearance. However, we could not validate any relevant improved predictability within twofold by the addition of serum to hepatocyte incubations or albumin to microsomal incubations. This was the case when investigating all measurements, or when subdividing analyses by extraction ratio, degree of protein binding, Biopharmaceutics Drug Disposition Classification System class, examining Extended Clearance Classification System class 1B drugs only, or drug charge. Manipulating characteristics of small data sets of like compounds and adding scaling factors can appear to yield good predictability, but the carryover of these methods to alternate drug classes and different laboratories is not evident. Improvement in predictability of poorly soluble compounds is greater than that for soluble compounds, but not to a meaningful extent. Overall, we cannot confirm that protein addition improves in vitro-in vivo extrapolation predictability to any clinically meaningful degree when considering all drugs and different subsets. SIGNIFICANCE STATEMENT: The addition of protein into microsomal or hepatocyte incubations has been widely proposed to improve hepatic clearance predictions. To date, studies examining this phenomenon have not included appropriate negative controls where predictability is achieved without protein addition and have been conducted with small data sets of similar compounds that don't apply to alternate drug classes. Here, an extensive analysis of published data for 60 drugs and 97 experimental comparisons couldn't validate any relevant clinically improved clearance predictability with protein addition.

Indexed as

HepatocytesModels, BiologicalKineticsLiverMetabolic Clearance RateMicrosomes, LiverPharmaceutical PreparationsPharmaceutical Preparations

Identifiers

PMID35086847
PMCPMC11022888
OpenAlexW4210375637

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.