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Chemistry Advancements in Drug Discovery
Advanced chemistry strategies are being used for a faster and smoother path to the clinic
Today, drug hunters employ advanced chemistry strategies such as artificial intelligence (AI), computational approaches, machine learning, and predictive modeling for a faster and smoother path to the clinic.
AI drug discovery methodologies and machine learning techniques are being used at all stages of discovery and optimization of chemical matter, including hit identification, hit-to-lead, and lead optimization to quickly explore novel chemical space and rapidly identify improved compounds. This allows for the optimization against complex, project-specific design criteria such as biochemical potency, cell potency, and DMPK objectives.
Computer-aided (in silico) drug design can also help expedite and enable hit identification, hit-to-lead, and optimize ADME and toxicology profiles as well as anticipate any safety issues. The most effective CADD scientists employ informatics, virtual screening, and molecular modeling, and work closely with screening, medicinal chemistry, structural biology, and DMPK teams to ensure optimum scientific results.
Learn how innovative chemistry methodologies are being used today to generate data and guide decisions for drug discovery projects.