Biopharmaceutical companies must collect and analyze an astonishing amount of data to take a product all the way to market. This data is collected by many different groups along the product development pathway. Furthermore, large companies have international teams who need to harmonize experimental conditions so they can combine datasets.
These complexities of product development in the life sciences industry mean that scientists, managers and biopharma executives spend a lot of time trying to understand what their data means. Many are turning to artificial intelligence (AI) and machine learning tools to help shift through reams of data.
AI Can Help Cross-Talk Between Cross-Functional Teams