APEX: Approximate but Exhaustive Search for Combinatorial Synthesis Libraries

In the field of drug discovery, combinatorial synthesis libraries (CSLs) have revolutionized the ability to explore an almost infinite chemical space. However, their enormous volume —tens of billions of compounds— imposes severe restrictions on conventional virtual screening processes, which barely manage to evaluate a tiny fraction of the available molecules. The APEX method (approximate but exhaustive search) emerges as a disruptive solution that combines neural networks as a surrogate for scoring functions with a complete enumeration on GPU, managing to identify the most promising compounds in less than a minute. This approach not only accelerates decision-making but also offers the possibility of reusing the calculation when the constraints or objectives of the study change, an aspect often overlooked. From a business perspective, the integration of AI for businesses as proposed by APEX allows transforming virtual screening into an agile and scalable process, ideal for R&D departments looking to maximize their computational budget. At Q2BSTUDIO, as a software development and technology company, we apply these principles to the creation of custom applications that integrate artificial intelligence, AWS and Azure cloud services, and business intelligence services with Power BI, offering organizations robust tools to face complex challenges. Additionally, the use of AI agents and cybersecurity techniques ensures that sensitive data flows remain protected throughout the process. APEX's efficiency demonstrates that, with the right architecture, it is possible to perform exhaustive searches without sacrificing precision, a balance that every pharmaceutical or biotechnology company should consider when designing their virtual screening strategies. The combination of custom software and machine learning models not only optimizes times but also opens the door to discoveries that were previously hidden in the vast ocean of combinatorial chemistry.