The process of drug discovery requires integration of biochemical and genetic tests to analyze the effects of drug molecules on biological systems. Comparative proteomic/lipidomic methods have identified a large number of differentially expressed novel proteins and lipids that can be used as prominent biomarkers for disease classification and drug resistance. Lipidomics or proteomics are not only used for target identification and deconvolution but also for analysis of off–targets and for studying the mode of action of drug molecules. In addition, they play significant roles in toxicity and preclinical trials at very early stages of drug development as well as in analysis of adverse effects of existing drug molecules. Since large-scale ‘omics’ data are now available in the public domain, bioinformatics and statistical analysis tools are needed to decipher knowledge from this vast amount of data. This review gives a brief overview of advancements in technological and computational methods in the area of lipidomics and proteomics based drug design.