The emergence of ‘techbio’ organizations and the constant development of new digital technologies in the drug discovery space, like artificial intelligence (AI) and machine learning (ML), are motivating a move to more data-driven drug discovery processes. The need to use new techniques such as predictive modeling and proteomics, or new drug modalities such as antibodies, oncolytic viruses, and proteolysistargeting chimeras (PROTAC), to stay competitive means it is often necessary for companies to partner with several different CROs to take advantage of diverse skillsets and to get the best services at each stage of the drug discovery life cycle. This change in focus has been reflected in recent strategic collaborations, as biopharma competes to partner with companies offering AI-based technologies. Indeed, many smaller, specialized biotech companies are now outsourcing their technologies and know-how alongside their own pipeline of development candidates.