Data analytics and data visualization for the pharmaceutical industry

In pharmaceutical science, multi-step drug product development processes generate an enormous amount of datasets each day as a part of chemistry, pre-clinical and clinical processes, as well as further drug product approval and pharmacovigilance. In creating useful knowledge from data and information, harnessing data analytics/visualization is a practical step for pharmaceutical researchers. In conjunction with stricter government regulation and increased competition, good data analysis is critical in the 21st century. Pharma data analytics/visualization from immense volumes of data set reveals unexpected connections and cuts through noisy data to join the correct dots to get better outcomes more quickly. A data scientist could play a knowledge bridge between the multiple departments and multidisciplinary teams in the pharmaceutical industry to speed up drug product development and reduce the economic burden. This chapter describes the importance of data analytics and visualization from drug chemistry to drug product development, valuable tools to do so, and real-time examples in the pharmaceutical and clinical world.