Apicomplexan parasite diseases cause severe health consequences in humans and livestock. This chapter reviews some of the methods used for unraveling the parasite adaptation dynamics and suggests how they can be used for identification, selection, and validation of drug targets. These methods include omics based approaches, biochemical experiments, and mathematical modeling. The chapter discusses glycerophospholipid metabolism in Plasmodium where several drug targets have been identified and validated. Different omics‐based approaches such as epigenomics, transcriptomics, proteomics, metabolomics, and fluxomics have been used to identify biomarkers that indicate a specific physiological state of parasites. Data mining and machine learning designate a wide range of mathematical techniques for automatic extraction of information and knowledge production out of experimental data. Combining omics data to mathematical models along with the experiments would allow for optimizing the drug discovery process via an in‐depth analysis of biological systems and novel metabolism‐targeted therapeutics.