Evidence map›Paper›PMID 32779124›Full record

ArticleClinical pharmacokinetics2021

Simple Approach to Accurately Predict Pharmacokinetics of Therapeutic Monoclonal Antibodies after Subcutaneous Injection in Humans.

Kenta Haraya, Tatsuhiko Tachibana

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Article in Clinical pharmacokinetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. A Quantitative Prediction Method for the Human Pharmacokinetics of Fc-Fusion Proteins.European journal of drug metabolism and pharmacokinetics · 2023
    Article
  4. Review
  5. Review
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Kenta HarayaChugai Pharmaceuticals Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan. haraya.kenta@chugai-pharm.co.jp.ORCID 0000-0002-9142-5607
Tatsuhiko TachibanaChugai Pharmaceuticals Co., Ltd., 1-135 Komakado, Gotemba, Shizuoka, 412-8513, Japan.
Chugai Pharma (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe subcutaneous injection of therapeutic monoclonal antibodies is increasingly used in the treatment of several diseases because of its convenience. Thus, a simple and accurate method of predicting the pharmacokinetics of monoclonal antibodies after a subcutaneous injection in humans would be a valuable tool for preclinical/clinical development. In this study, we investigated whether the pharmacokinetics of monoclonal antibodies after a subcutaneous injection in humans can be predicted using only pharmacokinetic data after a subcutaneous injection in cynomolgus monkeys.

methodsFirst, we compared the accuracy of three approaches to predict the apparent clearance (CL/F) and apparent volume of distribution (V

resultsIn a comparison of approaches, the first approach showed the best prediction accuracy for CL/F with an exponent of 0.9 (100% and 73% prediction accuracy within 2- and 1.5-fold of the observed value),and the third approach was the best for V

conclusionThis simple approach can be applied in preclinical and clinical settings to predict the pharmacokinetics of monoclonal antibodies after subcutaneous injections in humans. Further, this approach requires only CL/F after a subcutaneous injection in cynomolgus monkeys, contributing to animal welfare and reducing costs.

Indexed as

Antibodies, MonoclonalAntineoplastic Agents, ImmunologicalAnimalsHumansInjections, SubcutaneousMacaca fascicularisModels, BiologicalPharmacokineticsAntibodies, MonoclonalAntineoplastic Agents, Immunological

Identifiers

PMID32779124
OpenAlexW3048394778

What OpenQuestion holds

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Registered trials

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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.