Quality Over Quantity: Rethinking AI-Driven Drug Discovery
- Highlight the data fallacy in AI drug discovery and why the common belief that “more data means better models” can actually mislead R&D efforts in pharmaceutical AI
- Elevate how the power of model design and well-designed AI architectures can efficiently learn from smaller, high-quality datasets to enable meaningful insights without massive data volumes
- Demonstrate a path towards smarter discovery and how shifting focus from data quantity to data quality and model integrity leads to more reliable predictions, faster iterations, and ultimately better drug candidates