Trial reportPharmacology research & perspectives2019
Quantitative systems toxicology (QST) reproduces species differences in PF-04895162 liver safety due to combined mitochondrial and bile acid toxicity.
Trial report in Pharmacology research & perspectives, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01691274 (A Double Blind), which is not on this map. Cited by 11 papers.
What it found
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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.
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.
A Double Blind (3rd Party Open) Randomized, Placebo Controlled, Parallel Group Dose Escalation Study To Investigate The Safety, Toleration And Pharmacokinetics Of Multiple Oral Doses Of Pf-04895162 In Healthy Subjects
Who cites it
11 citing papers in PubMed, 22 citations in OpenAlex.
- Quantitative systems toxicology (QST) reproduces species differences in PF-04895162 liver safety due to combined mitochondrial and bile acid toxicity.Pharmacology research & perspectives · 2019Trial
- Quantitative Systems Toxicology Modeling with DILIsym to Support Phase 3 Dose Selection for Fezolinetant.Clinical pharmacology and therapeutics · 2026Article
- Quantitative systems toxicology: modelling to mechanistically understand and predict drug safety.Nature reviews. Drug discovery · 2026Review
- Drug metabolizing enzymes and transporters, and their roles for the development of drug-induced liver injury.Expert opinion on drug metabolism & toxicology · 2025Review
- Review
- Targeting Kv7 Potassium Channels for Epilepsy.CNS drugs · 2025Review
- The estimation and translation uncertainties in applying NOAEL to clinical dose escalation.Clinical and translational science · 2024Article
- Review
- Investigating bile acid-mediated cholestatic drug-induced liver injury using a mechanistic model of multidrug resistance protein 3 (MDR3) inhibition.Frontiers in pharmacology · 2022Article
- The Combination of Cell Cultured Technology and In Silico Model to Inform the Drug Development.Pharmaceutics · 2021Review
- Micropillar/Microwell Chip Assessment for Detoxification of Bisphenol A with Korean Pear (Micromachines · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many compounds that appear promising in preclinical species, fail in human clinical trials due to safety concerns. The FDA has strongly encouraged the application of modeling in drug development to improve product safety. This study illustrates how DILIsym, a computational representation of liver injury, was able to reproduce species differences in liver toxicity due to PF-04895162 (ICA-105665). PF-04895162, a drug in development for the treatment of epilepsy, was terminated after transaminase elevations were observed in healthy volunteers (NCT01691274). Liver safety concerns had not been raised in preclinical safety studies. DILIsym, which integrates in vitro data on mechanisms of hepatotoxicity with predicted in vivo liver exposure, reproduced clinical hepatotoxicity and the absence of hepatotoxicity observed in the rat. Simulated differences were multifactorial. Simulated liver exposure was greater in humans than rats. The simulated human hepatotoxicity was demonstrated to be due to the interaction between mitochondrial toxicity and bile acid transporter inhibition; elimination of either mechanism from the simulations abrogated injury. The bile acid contribution occurred despite the fact that the IC
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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.