Evidence map›Paper›PMID 29600249›Full record

ArticleFrontiers in medicine2018

Human-Induced Pluripotent Stem Cells Manufactured Using a Current Good Manufacturing Practice-Compliant Process Differentiate Into Clinically Relevant Cells From Three Germ Layers.

Mehdi Shafa, Fan Yang, Thomas Fellner, Mahendra S Rao, Behnam Ahmadian Baghbaderani

Abstract read
In one paragraph

Article in Frontiers in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  16. End-to-End Platform for Human Pluripotent Stem Cell Manufacturing.International journal of molecular sciences · 2019
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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

5 authors.

Mehdi ShafaLonza Walkersville, Inc., Walkersville, MD, United States.
Fan YangLonza Walkersville, Inc., Walkersville, MD, United States.
Thomas FellnerLonza Walkersville, Inc., Walkersville, MD, United States.
Mahendra S RaoNxCell Inc, Novato, CA, United States.
Behnam Ahmadian BaghbaderaniLonza Walkersville, Inc., Walkersville, MD, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery of reprogramming and generation of human-induced pluripotent stem cells (iPSCs) has revolutionized the field of regenerative medicine and opened new opportunities in cell replacement therapies. While generation of iPSCs represents a significant breakthrough, the clinical relevance of iPSCs for cell-based therapies requires generation of high-quality specialized cells through robust and reproducible directed differentiation protocols. We have recently reported manufacturing of human iPSC master cell banks (MCB) under current good manufacturing practices (cGMPs). Here, we describe the clinical potential of human iPSCs generated using this cGMP-compliant process by differentiating them into the cells from all three embryonic germ layers including ectoderm, endoderm, and mesoderm. Most importantly, we have shown that our iPSC manufacturing process and cell culture system is not biased toward a specific lineage. Following controlled induction into a specific differentiation lineage, specialized cells with morphological and cellular characteristics of neural stem cells, definitive endoderm, and cardiomyocytes were developed. We believe that these cGMP-compliant iPSCs have the potential to make various clinically relevant products suitable for cell therapy applications.

Indexed as

cell therapycurrent good manufacturing practicesdifferentiationinduced pluripotent stem cellsregenerative medicine

Identifiers

PMID29600249
PMCPMC5862873

What OpenQuestion holds

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LicenceCC BY
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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.