Arvinas has deployed AI and machine learning in its PROTAC Discovery Engine for pharmacokinetic prediction, structural biology modeling, and ligand identification.
“As part of our continuous effort to be innovative and increase efficiency throughout our business, we have incorporated artificial intelligence (“AI”) and machine learning solutions in applications that are important to our operations and our drug discovery processes, including our PROTAC Discovery Engine, which is an interlocking suite of tools and expertise that assists with our goal of creating and advancing our programs. Specifically, we have deployed AI and machine learning tools in the prediction of preclinical pharmacokinetic properties to find drug-like PROTACs early in the discovery process, structural biology modeling, and ligand identification. While AI and machine learning present opportunities for enhanced productivity and innovation, they also introduce cybersecurity, data privacy, information technology (“IT”), intellectual property, regulatory, legal, operational, competitive, reputational and other risks that could adversely impact our business. Specifically, risks related to AI hallucinations, rogue AI agent behaviors, targeted attacks (including model poisoning or data poisoning), misinformation, data leakage, bias, discrimination, harmful content, fraud, scams, surveillance, inequality, environmental harms, and other harms may flow from our development, use, or deployment of AI or machine learning technologies. If the data used to train AI or the content, analyses, or recommendations that AI applications assist in producing are or are alleged to be deficie”