Evidence map›Paper›PMID 23135927›Full record

ArticleThe AAPS journal2013

Validation of a ligand binding assay using dried blood spot sampling.

Daniel Burns, Laura Brunner, Surendran Rajendran, Beth Johnson, Mark Ma, Jin Wang

Abstract readValidation Study
In one paragraph

Article in The AAPS journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Daniel BurnsPharmacokinetics and Drug Metabolism Department, Amgen Inc., Mail Stop 30E-3-C, One Amgen Center Drive, Thousand Oaks, CA 91320, USA.
Laura Brunner
Surendran Rajendran
Beth Johnson
Mark Ma
Jin Wang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dried blood spots (DBS) technology has been introduced as a microsampling alternative to traditional plasma or serum sampling for pharmacokinetics or toxicokinetics evaluation. The application of DBS has been established for many small molecule drugs at discovery, nonclinical, and clinical stages. However, the application of DBS for large molecule therapeutics development is not yet well-established. This article describes the method validation of a ligand binding assay (LBA) for DBS sampling of a therapeutic monoclonal antibody-AMG 162 (Denosumab). The original serum LBA was modified for the DBS method. A fit-for-purpose method validation was performed to evaluate accuracy and precision, selectivity, dilutional linearity, and stability. In addition, the parameters relevant to DBS, such as spot volume, extraction recovery, whole blood stability, and hematocrit effects, were evaluated. The validation results demonstrated assay robustness with inter-assay precision of ≤ 19%, inter-assay accuracy of ≤ 9%, and total error of ≤ 24%. Selectivity, extraction recovery, dilutional linearity, and stability were demonstrated. The validation results revealed some limitations of the possible effect of blood hematocrit on therapeutic concentration measurements and the caution required using whole blood for standards and quality controls preparation. This is the first article to describe a thorough method validation of an LBA using DBS for a therapeutic monoclonal antibody. The lessons learned can serve as a model process for future method validation of other LBAs for large molecule therapeutics or biomarkers using the DBS sampling method.

Indexed as

Antibodies, Monoclonal, HumanizedBlood PreservationDenosumabDried Blood Spot TestingHematocritHumansLigandsAntibodies, Monoclonal, HumanizedDenosumabLigands

Identifiers

PMID23135927
PMCPMC3535112

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.