The development of the drug discovery process is very important in bioinformatics tools applying bioinformatics methods for the analysis of biological data. They are used to find new targets for drugs through genome analysis, whereby the genetic sequences will be analyzed to determine genes responsible for diseases. Knowing the 3D structure of proteins implicated in disease processes, it helps in designing the drug to interact specifically with targets, stopping the progress of the disease process. Virtual screening techniques will speed up this process by quickly evaluating large compound libraries for compounds that would have potential to bind to target proteins. In the area of bioinformatics, systems biology approaches go another step further in the integration of omics data such as genomics, transcriptomics, and proteomics, and then define complex disease pathways and interlinked networks indicative of new targets of therapy. In the area of personalized medicine, bioinformatics analyzes genetic variations among individuals to predict drug responses that will lead to tailored treatment strategies. It further predicts drug-target interactions with the aid of big data analytics aided by machine learning algorithms and optimizes experimental designs, hence streamlining drug discovery processes. Therefore, Bioinformatic tools can be used in drug delivery and drug discovery.