HESI Translating in vitro mechanistic findings to in vivo toxicity outcomes
Translating in vitro mechanistic findings to in vivo toxicity outcomes: A case study of Usnic acid hepatotoxicity Abstract: New Approach Methodologies (NAMs) utilizing cellular models provide mechanistic insight into chemical hazards, but their utility in human health risk assessment depends on demonstrating how effectively in vitro findings translate to real-world outcomes. Quantitative in-vitro–to–in-vivo extrapolation (QIVIVE), supported by physiologically based pharmacokinetic (PBPK) modeling, enables this translation by linking in vitro concentration–response data to in vivo dose–response relationships. Here, we evaluated QIVIVE performance using usnic acid as a model compound. Usnic acid was selected because in vitro data and clinical case reports are available, enabling direct assessment of translational accuracy. Bayesian Benchmark Doses (BBMDs) were derived from in vitro toxicity data spanning thirteen endpoints in three hepatic cell models. Freely dissolved concentrations were estimated using a mass balance distribution model and incorporated into QIVIVE to predict equivalent administered doses (EADs), the in vivo doses expected to reproduce observed in vitro effects. Three PBPK platforms (GastroPlus, Berkeley Madonna, and httk R package) were applied. Predicted EADs aligned with reported exposure levels associated with hepatotoxicity, supporting the translational relevance of QIVIVE. Results indicated activation of multiple hepatotoxicity pathways, including redox disturbance, stress response, and DNA damage, across 1–384 mg oral doses. At human relevant intake levels, these mechanisms may explain the progression to liver injury in consumers of usnic acid. This study demonstrates that QIVIVE has the potential to translate in vitro mechanisms into possible human health outcomes, offering more mechanistically informed evidence for safety assessments of botanical constituents. Original publication: Lui et al., 2026. Translating in vitro mechanistic findings to in vivo toxicity outcomes: A case study of Usnic acid hepatotoxicity. Toxicology and Applied Pharmacology. https://doi.org/10.1016/j.taap.2026.1...

HESI: Recall bias in population-based case-control studies of ovarian cancer and genital talc use

HESI Global Webinar Benchmark Dose BMD Modeling for Risk Assessment

Introduction to Genomic Biomarkers in Radiation Oncology

HESI: Quantitative Bias Analysis: the good, the bad, and the ugly.

Introduction to Suture

Shade Tree Used Car Lot Strikes AGAIN! (Customer JUST BOUGHT this CAR) 2007 Kia Optima 2.4

She Was Trying to Cut It With Scissors and The Grass Was Taller Than My Mowers

HESI: A flexible Monte Carlo quantitative bias analysis for unmeasured confounding

Electricity Does Not "Split" H₂O. And That's VERY Useful.

How ASML Makes Chips Faster With Its New $400 Million High NA Machine

AI Is Creating A Rare Opportunity For Investors. How Jim Roppel Is Playing It. | Investing With IBD

Out of Sync: Sleep, Circadian Rhythms & Shift Work in Paramedics - Laura Hirello

HESI (eSTAR) Committee 2025 Annual Meeting: Error Corrected Sequencing

We Completely Changed Our BRAND NEW Van… First Full Tour

The Crystal That Could Destroy All Medicine

What do tech pioneers think about the AI revolution? - The Engineers, BBC World Service

"Using Omics in Biomedical Research" & "Data Asset Management in the Era of Collaborative Science"

AI 최후의 승자 이래서 구글입니다 (KAIST 전자및전기공학부 김정호 교수)

Why birth rates are falling everywhere all at once | FT

