Method Profile

Multiparametric Liver-Injury Hazard Flags and Random-Forest Classification

Human liver-cell toxicity, mitochondrial respiration, bile-salt transport and drug properties are combined in interpretable flags and separately trained classifiers.

LiverComputational Models
Phase-contrast microscopic image of a culture of HepG2 cells.
HepG2 cells in phase-contrast microscopy. (User:SubtleGuest, CC BY 2.5)

Research Applications

Prioritize small molecules for mechanistic follow-up during early drug discovery and lead optimization.

Model & Design

170 reference drugs: 80 clinically DILI-positive and 90 DILI-negative; 2D primary human hepatocytes, 3D human liver microtissues, HepG2 respiration and BSEP vesicles.

Experimental Format

48-hour 2D viability, seven-day 3D repeated exposure, short mitochondrial-respiration testing and BSEP inhibition; exposure-inclusive and exposure-free random forests.

Model Components

  • Component

    Human liver systems

    Description

    BioIVT primary human hepatocytes and InSphero microtissues containing pooled hepatocytes from 10 donors plus non-parenchymal cells; ATP viability measured against vehicle.

  • Component

    Mechanistic assays

    Description

    HepG2 oxygen-consumption testing and BSEP taurocholate transport in vesicles; additional metabolism, physicochemical and glutathione-trapping features.

  • Component

    Reference data

    Description

    Literature/curated clinical DILI classification and total clinical Cmax, or Css where Cmax was unavailable.

Measurements & Endpoints

  • ATP-based IC50
  • Basal/maximal respiration inhibition
  • BSEP IC50
  • Exposure-normalized assay margins
  • Hazard-category count
  • Cross-validated DILI classification

Analysis

Treat 2D/3D cytotoxicity as one hazard category alongside mitochondrial and BSEP categories. Evaluate random forests with 100 repetitions of stratified tenfold cross-validation and explicitly retain each probability threshold.

Published Evidence

  • Study Design

    Compare hazard combinations and two classifier feature sets against clinical labels within the 170-drug reference set.

    Study Sample

    80 DILI-positive and 90 DILI-negative reference drugs; each molecule appears in 100 held-out test folds across repeated cross-validation.

    Comparison

    Clinical reference labels; exposure-inclusive versus exposure-free models; single versus multiple hazard categories.

    Finding

    At least two hazard categories gave 98% specificity and 40% sensitivity. At probability 0.50, exposure-inclusive RF balanced accuracy/sensitivity/specificity were 0.72/0.71/0.72, versus 0.60/0.55/0.66 without exposure.

    Interpretation & Limits
    • Repeated folds are internal validation of one reference set.
    • Reference labels emphasize severe clinical DILI and do not reproduce its prevalence in discovery.
    • Immune-mediated liability and individual susceptibility are incompletely represented.
  • Study Design

    Apply the assay and model framework to internal drug-development examples with differing evidence availability.

    Study Sample

    Eight Genentech compounds, four with known clinical DILI; other examples have limited clinical or preclinical information.

    Comparison

    Mechanistic flags, RF probabilities and the available development outcomes for each compound.

    Finding

    The exposure-free model classified all eight positive; the exposure-inclusive model classified five positive and three negative at 0.50, including a known clinical DILI compound with probability 0.47.

    Interpretation & Limits
    • Unknown clinical categories and preclinical attrition preclude a simple eight-compound clinical accuracy estimate.

Sources

  1. A multiparametric in vitro strategy for small molecule drug-induced liver injury risk mitigation in early drug development. Toxicological Sciences (2026). ↗