Evidence map›Paper›PMID 41136840›Full record

ArticleAdvances in experimental medicine and biology2025

Development of a Manufacturing Process for Clinical Autologous hiPSC-Derived Retinal Pigment Epithelium.

Shekhar Jha, Fang Hua, Roba Dejene, Sarmila Sarkar, Ruchi Sharma, Kapil Bharti

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Article in Advances in experimental medicine and biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Cell therapy for age-related macular degeneration.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    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

6 authors.

Shekhar JhaNational Eye Institute, NIH, Bethesda, MD, USA.
Fang HuaNational Eye Institute, NIH, Bethesda, MD, USA.
Roba DejeneCenter for Cellular Engineering, NIH, Bethesda, MD, USA.
Sarmila SarkarCenter for Cellular Engineering, NIH, Bethesda, MD, USA.
Ruchi SharmaNational Eye Institute, NIH, Bethesda, MD, USA. fnu.ruchi2@nih.gov.
Kapil BhartiNational Eye Institute, NIH, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss. The disease progresses through early, intermediate, and advanced stages, with late forms including dry AMD (geographic atrophy) and wet AMD (choroidal neovascularization). Currently, there is no cure for dry AMD, which results from retinal pigment epithelium (RPE) cell loss. Induced pluripotent stem cell (iPSC)-based transplants offer a potential therapy by replacing atrophied RPE. This chapter outlines the manufacturing process, key parameters, and challenges of developing iPSC-derived RPE therapy. We engineered a clinical-grade iPSC-RPE patch using autologous cells from AMD patients. Starting from the patient blood, CD34+ cells were isolated, expanded, and reprogrammed using episomal plasmids. Twelve iPSC clones were generated, quality-tested, and three were selected for differentiation into mature RPE on a biodegradable scaffold. The final patch underwent QC assays for donor identity, sterility, and phenotype confirmation before transplantation. This work has led to a Phase I/IIa clinical trial to evaluate the safety and feasibility of auto-iPSC-RPE patches in AMD patients.

Indexed as

Induced Pluripotent Stem CellsMacular DegenerationRetinal Pigment EpitheliumCell DifferentiationHumansTissue EngineeringTransplantation, AutologousAMDAutologousCell therapyClinical trialGeographic atrophyiPS cell therapyManufacturing processRetinal degenerationRetinal pigment epitheliumRPEScaffold

Identifiers

PMID41136840

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.