Evidence map›Paper›PMID 25697964›Full record

ArticleJournal of computer-aided molecular design2015

Time dependent analysis of assay comparability: a novel approach to understand intra- and inter-site variability over time.

Susanne Winiwarter, Brian Middleton, Barry Jones, Paul Courtney, Bo Lindmark, Ken M Page, Alan Clark, Claire Landqvist

Abstract read
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In one paragraph

Article in Journal of computer-aided molecular design, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Interpretation ofACS medicinal chemistry letters · 2018
    Article
  5. 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

8 authors.

Susanne WiniwarterInnovative Medicines, Drug Safety and Metabolism, AstraZeneca R&D Mölndal, Pepparedsleden 1, 431 83, Mölndal, Sweden. susanne.winiwarter@astrazeneca.com.
Brian MiddletonInnovative Medicines, Discovery Sciences, AstraZeneca R&D Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK.
Barry JonesInnovative Medicines, Drug Safety and Metabolism, AstraZeneca R&D Cambridge, Unit 310 - Darwin Building, Cambridge Science Park, Milton Road, Cambridge, CB4 0WG, UK.
Paul CourtneyGlobal Medicines Development, Pharmaceutical Development, AstraZeneca R&D, Charter Way, Silk Road Business Park, Macclesfield, Cheshire, SK10 2NA, UK.
Bo LindmarkInnovative Medicines, Cardiovascular and Metabolic Diseases, AstraZeneca R&D Mölndal, Pepparedsleden 1, 43183, Mölndal, Sweden.
Ken M PageInnovative Medicines, Drug Safety and Metabolism, AstraZeneca R&D Alderley Park, Macclesfield, Cheshire, SK10 4TF, UK.
Alan ClarkInnovative Medicines, Drug Safety and Metabolism, AstraZeneca R&D Boston, 35 Gatehouse Park, Waltham, MA, 01742, USA.
Claire LandqvistInnovative Medicines, Drug Safety and Metabolism, AstraZeneca R&D Mölndal, Pepparedsleden 1, 431 83, Mölndal, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We demonstrate here a novel use of statistical tools to study intra- and inter-site assay variability of five early drug metabolism and pharmacokinetics in vitro assays over time. Firstly, a tool for process control is presented. It shows the overall assay variability but allows also the following of changes due to assay adjustments and can additionally highlight other, potentially unexpected variations. Secondly, we define the minimum discriminatory difference/ratio to support projects to understand how experimental values measured at different sites at a given time can be compared. Such discriminatory values are calculated for 3 month periods and followed over time for each assay. Again assay modifications, especially assay harmonization efforts, can be noted. Both the process control tool and the variability estimates are based on the results of control compounds tested every time an assay is run. Variability estimates for a limited set of project compounds were computed as well and found to be comparable. This analysis reinforces the need to consider assay variability in decision making, compound ranking and in silico modeling.

Indexed as

Data Interpretation, StatisticalPharmacokineticsAnimalsBiological AssayBlood ProteinsDrug Evaluation, PreclinicalHepatocytesHigh-Throughput Screening AssaysHumansInactivation, MetabolicMicrosomes, LiverPharmaceutical PreparationsRatsSolubilityBlood ProteinsPharmaceutical PreparationsADMEDMPKScreening assaySite variabilityVariability

Identifiers

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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.