About scDrugMap

scDrugMap is a scalable and user-friendly framework for predicting drug responses in single-cell transcriptomics data using large-scale foundation models. It supports both a Python command-line tool and an interactive web interface (scdrugmap.com) to facilitate drug discovery and translational research.

Overview

Drug resistance remains a major challenge in cancer treatment. Single-cell profiling provides critical insights into cellular heterogeneity and drug sensitivity, but high dimensionality and data sparsity can complicate downstream analysis.

scDrugMap evaluates and integrates the predictive power of eight single-cell foundation models and two natural language models across diverse cancer types and treatment regimens. It supports:

• Pooled-data and cross-data model evaluation
• Layer freezing and LoRA fine-tuning
• Zero-shot and fine-tuned inference
• Single-cell resolution predictions across 326,000+ cells and 36+ datasets