Abstract
The information flow in pharmaceutical research before data interpretation
and management was largely manual and simple, with limited application of
technology. Establishing the research objective, designing the study, collecting data,
analyzing data, and interpreting the result were laborious, tedious, and time-consuming
processes. Manually entering and sorting a large amount of data made researchers more
prone to human errors, leading to incorrect and invalid results. The chapter draws on
data mining, data abstracting, and intelligent data analysis to collectively improve the
quality of drug discovery and delivery methods. To develop new drugs and improve
existing treatments, software can be used to analyze large datasets and identify patterns
that help understand how drugs interact with the body. Virtual models of organs and
cells are employed to study the effects of drugs, automate drug testing, and predict
adverse drug reactions. Pharmaceutical management tools, such as pharmacy
management software, electronic prescription software, inventory management
software, and automated dispensing systems, are highly valuable for managing
inventory, tracking patient prescriptions, monitoring drug interactions, maintaining
patient information and history, and providing up-to-date drug information. The main
objective of this chapter is to highlight the various tools and software solutions
available and how they can facilitate the research process to ensure compliance with
relevant regulations and laws regarding human healthcare safety.