Iktos Webinar - AI in Oncology Drug Discovery: From Hit Discovery to Advanced nM Lead Design

The integration of artificial intelligence (AI) and machine learning (ML) is reshaping small-molecule drug discovery across the pharmaceutical industry. By combining advanced data analysis, structural modeling, molecular design, binding prediction, retrosynthetic planning, and multi-parameter optimization of physicochemical and DMPK properties, AI has the potential to significantly accelerate and improve the drug discovery process. In parallel, the emergence of AI-driven autonomous synthesis platforms is enabling the rapid, flexible, and efficient production of newly designed compounds, further shortening design–make–test cycles. During this presentation we will illustrate the application of AI in drug discovery with 3 examples of fast hit discovery to H2L with two kinase PIM1 and PKMYT1, and DNA Polymerase Theta (PolQ), PKMYT1 and PolQ being both synthetic lethal targets in oncology. We will also cover PD-L1, an immune checkpoint protein in oncology, making use of Multi-Parametric Optimization (MPO) and Machine Learning (ML) models to discover innovative scaffolds and guide drug design towards advanced nanomolar lead series. We will go through each step of the AI generation and execution of the synthesis using a mix combination of robotic synthesis and bench chemistry to deliver nM inhibitors on the 4 programs with completely novel scaffolds or unprecedented modifications of existing series. Learn more at www.iktos.ai