drexplorer

drexplorer analyzes dose-response relationships and assesses drug–drug interactions to quantify drug potency metrics (e.g., IC50 and other IC values) in anti-cancer drug studies.

Key Features:

• Model Evaluation and Reproducibility: Assesses reproducibility of replicate experiments to evaluate model robustness.
• Outlier Detection: Identifies outlier data points within dose-response datasets.
• Model Fitting and Selection: Fits various nonlinear dose-response models and selects models based on statistical criteria.
• IC Value Estimation: Estimates IC values at different percentiles, including IC50.
• Drug-Drug Interaction Assessment: Analyzes interactions between drugs to characterize synergistic or antagonistic effects in combination therapies.

Scientific Applications:

• Oncology drug evaluation: Quantifies potency and interaction profiles of anti-cancer drugs to inform dosage and combination optimization.
• Dose-response experiment analysis: Supports validation of replicate experiments and robust estimation of pharmacological parameters from dose-response data.

Methodology:

Implemented as an R package that fits nonlinear dose-response models, performs model selection using statistical criteria, detects outliers, estimates IC values at multiple percentiles, assesses reproducibility of replicates, and analyzes drug-drug interactions.