Evidence map›Paper›PMID 36253394›Full record

ArticleScientific reports2022

A digital platform for the design of patient-centric supply chains.

Niki Triantafyllou, Andrea Bernardi, Matthew Lakelin, Nilay Shah, Maria M Papathanasiou

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. A quest for stakeholder synchronization in the CAR T-cell therapy supply chain.Frontiers in bioengineering and biotechnology · 2024
    Review
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

5 authors at 1 institution in 1 country.

Niki Triantafyllou *Sargent Centre for Process System Engineering, Imperial College London, London, SW7 2AZ, UK.
Andrea Bernardi *Sargent Centre for Process System Engineering, Imperial College London, London, SW7 2AZ, UK.
Matthew LakelinTrakCel Limited, 10/11 Raleigh Walk, Cardiff, CF10 4LN, UK.
Nilay ShahSargent Centre for Process System Engineering, Imperial College London, London, SW7 2AZ, UK.
Maria M PapathanasiouSargent Centre for Process System Engineering, Imperial College London, London, SW7 2AZ, UK. maria.papathanasiou11@imperial.ac.uk.
Imperial College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric Antigen Receptor (CAR) T cell therapies have received increasing attention, showing promising results in the treatment of acute lymphoblastic leukaemia and aggressive B cell lymphoma. Unlike typical cancer treatments, autologous CAR T cell therapies are patient-specific; this makes them a unique therapeutic to manufacture and distribute. In this work, we focus on the development of a computer modelling tool to assist the design and assessment of supply chain structures that can reliably and cost-efficiently deliver autologous CAR T cell therapies. We focus on four demand scales (200, 500, 1000 and 2000 patients annually) and we assess the tool's capabilities with respect to the design of responsive supply chain candidate solutions while minimising cost.

Indexed as

Lymphoma, B-CellPrecursor Cell Lymphoblastic Leukemia-LymphomaReceptors, Chimeric AntigenAntigens, CD19HumansImmunotherapy, AdoptivePatient-Centered CareReceptors, Antigen, T-CellAntigens, CD19Receptors, Antigen, T-CellReceptors, Chimeric Antigen

Identifiers

PMID36253394
PMCPMC9576774
OpenAlexW4306404373

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.