Evidence map›Paper›PMID 34269079›Full record

ArticleSLAS discovery : advancing life sciences R & D2021

Operationalizing the Use of Biofabricated Tissue Models as Preclinical Screening Platforms for Drug Discovery and Development.

Olive Jung, Min Jae Song, Marc Ferrer

Abstract read
In one paragraph

Article in SLAS discovery : advancing life sciences R & D, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. 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

3 authors.

Olive Jung3D Tissue Bioprinting Laboratory (3DTBL), Division of Pre-clinical Innovation (DPI), National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, MD, USA.
Min Jae Song3D Tissue Bioprinting Laboratory (3DTBL), Division of Pre-clinical Innovation (DPI), National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, MD, USA.
Marc Ferrer3D Tissue Bioprinting Laboratory (3DTBL), Division of Pre-clinical Innovation (DPI), National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, MD, USA.

Funding

Intramural NIH HHS Z99 TR999999
6 · The paper itself

Abstract

A wide range of complex in vitro models (CIVMs) are being developed for scientific research and preclinical drug efficacy and safety testing. The hope is that these CIVMs will mimic human physiology and pathology and predict clinical responses more accurately than the current cellular models. The integration of these CIVMs into the drug discovery and development pipeline requires rigorous scientific validation, including cellular, morphological, and functional characterization; benchmarking of clinical biomarkers; and operationalization as robust and reproducible screening platforms. It will be critical to establish the degree of physiological complexity that is needed in each CIVM to accurately reproduce native-like homeostasis and disease phenotypes, as well as clinical pharmacological responses. Choosing which CIVM to use at each stage of the drug discovery and development pipeline will be driven by a fit-for-purpose approach, based on the specific disease pathomechanism to model and screening throughput needed. Among the different CIVMs, biofabricated tissue equivalents are emerging as robust and versatile cellular assay platforms. Biofabrication technologies, including bioprinting approaches with hydrogels and biomaterials, have enabled the production of tissues with a range of physiological complexity and controlled spatial arrangements in multiwell plate platforms, which make them amenable for medium-throughput screening. However, operationalization of such 3D biofabricated models using existing automation screening platforms comes with a unique set of challenges. These challenges will be discussed in this perspective, including examples and thoughts coming from a laboratory dedicated to designing and developing assays for automated screening.

Indexed as

Drug Evaluation, PreclinicalTissue EngineeringAnimalsAutomationDrug DevelopmentDrug DiscoveryHumans3Dbiofabricated tissuesbiological complexitybioprintingclinical predictabilitycomplex in vitro modelsdisease modelingdomain of validitydrug developmentdrug discoveryoperationalizationphysiological relevancethroughput

Identifiers

PMID34269079
PMCPMC9527638

What OpenQuestion holds

Textmetadata
LicenceTDM
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.