ReviewEBioMedicine2021
Perspectives on the translation of in-vitro studies to precision medicine in Cystic Fibrosis.
Review in EBioMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Lung organoids as a human system for Mycobacteria infection modeling and drug testing.The FEBS journal · 2026Review
- Organoids in Cancer Research and Regenerative Medicine: Current Status, Challenges, and Future Prospects.MedComm · 2026Review
- Human-based complexFrontiers in cell and developmental biology · 2025Review
- Reconsidering the Diagnosis: Abnormal Sweat Chloride Tests in Non-CF Bronchiectasis.Pediatric pulmonology · 2025Article
- Cystic fibrosis.Nature reviews. Disease primers · 2024Review
- Animal Research Regulation: Improving Decision-Making and Adopting a Transparent System to Address Concerns around Approval Rate of Experiments.Animals : an open access journal from MDPI · 2024Article
- Air-Liquid interface cultures to model drug delivery through the mucociliary epithelial barrier.Advanced drug delivery reviews · 2023Review
- Who Modifies the Modifiers: A High-Resolution View of the Genetic Modifiers of Cystic Fibrosis.American journal of respiratory and critical care medicine · 2023Article
- Molecular and Functional Characteristics of Airway Epithelium under Chronic Hypoxia.International journal of molecular sciences · 2023Article
- Biomaterials-mediated CRISPR/Cas9 delivery: recent challenges and opportunities in gene therapy.Frontiers in chemistry · 2023Review
- Flow Cytometry Detection of Anthracycline-Treated Breast Cancer Cells: An Optimized Protocol.Current issues in molecular biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent strides towards precision medicine in Cystic Fibrosis (CF) have been made possible by patient-derived in-vitro assays with the potential to predict clinical response to small molecule-based therapies. Here, we discuss the status of primary and stem-cell derived tissues used to evaluate the preclinical efficacy of CFTR modulators highlighting both their potential and limitations. Validation of these assays requires correlation of in-vitro responses to in-vivo measures of clinical biomarkers of disease outcomes. While initial efforts have shown some success, this translation requires methodologies that are sensitive enough to capture treatment responses in a CF population that now predominantly has mild lung disease. Future development of in-vitro and in-vivo biomarkers will facilitate the generation of new therapeutics particularly for those patients with rare mutations where clinical trials are not feasible so that in the future every CF patient will have access to effective targeted therapies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.