 Big data has become increasingly important in the field of biomedicine due to advances in technology and open data initiatives. Data volume and diversity have grown exponentially, allowing for more accurate analysis of targets, mechanisms of action, and lead and drug candidate identification. Computational tools and databases are being utilized to facilitate this process, but there is still room for improvement. To make big data more cost-effective and focused on personalized medicine, we suggest combining information technologies and chemoinformatics tools to take advantage of their synergistic potential.