ArticlePloS one2011
Predicting in vivo anti-hepatofibrotic drug efficacy based on in vitro high-content analysis.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Modeling drug-induced liver injury and screening for anti-hepatofibrotic compounds using human PSC-derived organoids.Cell regeneration (London, England) · 2023Article
- Targeting metabolic dysregulation for fibrosis therapy.Nature reviews. Drug discovery · 2020Review
- Potential drug mechanism(s) targeting the contractile status of hepatic stellate cells.Frontiers in pharmacology · 2012Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsMany anti-fibrotic drugs with high in vitro efficacies fail to produce significant effects in vivo. The aim of this work is to use a statistical approach to design a numerical predictor that correlates better with in vivo outcomes.
methodsHigh-content analysis (HCA) was performed with 49 drugs on hepatic stellate cells (HSCs) LX-2 stained with 10 fibrotic markers. ~0.3 billion feature values from all cells in >150,000 images were quantified to reflect the drug effects. A systematic literature search on the in vivo effects of all 49 drugs on hepatofibrotic rats yields 28 papers with histological scores. The in vivo and in vitro datasets were used to compute a single efficacy predictor (E(predict)).
resultsWe used in vivo data from one context (CCl(4) rats with drug treatments) to optimize the computation of E(predict). This optimized relationship was independently validated using in vivo data from two different contexts (treatment of DMN rats and prevention of CCl(4) induction). A linear in vitro-in vivo correlation was consistently observed in all the three contexts. We used E(predict) values to cluster drugs according to efficacy; and found that high-efficacy drugs tended to target proliferation, apoptosis and contractility of HSCs.
conclusionsThe E(predict) statistic, based on a prioritized combination of in vitro features, provides a better correlation between in vitro and in vivo drug response than any of the traditional in vitro markers considered.
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