Description / Abstract: This cientific approach intends to be a system that could save billions of dollars in the implementation of high-throughput drug discovery and advanced materials engineering. Current R&D pipelines for pharmaceuticals suffer from a critical bottleneck: the computational cost of simulating molecular interactions is incredibly high, leading to slow time-to-market and expensive failures. The Chaotic Vortex Score (CVS) is a high-efficiency classification engine designed to eliminate this bottleneck. By replacing slow, legacy analysis methods with a streamlined scoring system, we achieve processing rates of ~293,000 interactions per second on standard, low-cost hardware. This extreme throughput allows organizations to: Slash Compute Costs: Process massive datasets on commodity devices instead of expensive supercomputing clusters. Accelerate Time-to-Market: Screen entire molecular libraries in seconds rather than weeks. Reduce Failure Rates: Identify and discard non-viable drug candidates immediately, before investing in costly trials. This paper presents the methodology and the engine capable of driving this efficiency at scale.
Pirolo Andres Sebastian (Wed,) studied this question.