Transforming Pharma with Data Science, AI and Machine Learning
Harry C. Yang · 2022
This chapter provides an overview of transformative changes occurring in pharma engendered by big data and artificial intelligence (AI) and discusses the importance of data strategy in realizing full potential of these technology advances in the lifecycle of drug development. To be competitive, it is paramount for pharmaceutical companies to develop and implement a robust data strategy that includes data governance, infrastructure, advanced analytics, and data science. In general, new technological platforms and specialized analytical techniques such as machine learning (ML) algorithms are needed for the curation, control, and analysis of big data. The redesign of the current drug development and healthcare paradigm lies in successful applications of AI and ML in several key areas, including drug discovery, clinical trials, manufacturing, and comparative evidence generation to support treatment decisions and market access. The transition to a patient-centric approach can be challenging as it requires changing existing mindsets, culture, and regulatory policies.