Andrew Anderson, VP of innovation and informatics strategy at ACD/Labs, is at the forefront of the exciting intersection of AI and machine learning in the pharmaceutical industry. In a recent interview with Pharmaceutical Executive, Anderson discussed the potential of these technologies in revolutionizing drug development.
Anderson highlighted the importance of data in AI and ML algorithms, emphasizing that not all data is created equal. He noted that while structured training sets can lead to insightful models, the volume, variety, and disposition of training data remain significant challenges in scientific applications.
One area where Anderson sees great potential for AI and ML is in pharmaceutical development. He discussed how these technologies can be applied to streamline processes for making clinical trial materials, ensuring reproducibility and reliability in production.
In addition, Anderson pointed out the industry’s focus on applying AI principles to process development and the need for large amounts of training data in accessible formats. He emphasized the importance of data engineering in reducing the overall cost of implementing AI and ML efforts.
Anderson also highlighted the evolving landscape of AI technologies, particularly in the realm of generative AI and large language models. He expressed excitement about the possibilities these advancements bring to the pharmaceutical industry and society as a whole.
Overall, Anderson’s insights shed light on the transformative potential of AI and machine learning in drug development, signaling an exciting time for innovation in the pharmaceutical industry.