Data Analytics and Computational Modeling for Next Generation Molecular Design

As with numerous scientific disciplines, Computer-Aided Drug Design (CADD) is facing great opportunities and challenges as a consequence of advances in computation and information technology. The 2023 CADD Gordon Conference will shed light on novel computational approaches tightly coupled to modern experimental techniques and applied to practical drug design endeavors.

While small molecule design is still the driving force of CADD, new modalities appear, emphasizing the need for precise chemical models and algorithms resulting in highly efficient computational tools. The conference will present a balanced view on CADD as a research field, focusing on computational methods and their applications. Areas covered include, among others, the modeling of biotherapeutics and large multi-protein complexes, handling of extended, synthetically accessible chemical space and ADMET models beyond statistical learning. Novel experimental techniques such as cryoEM and serial crystallography, DNA-encoded libraries and automated organic synthesis and their consequences for CADD will be discussed. At the same time, advances in computational techniques like machine learning and data science offer new opportunities to transfer data into knowledge. The impact of these technologies to drug design will become a second focal point in the conference.