Drug discovery and development is a complex, high risk, time consuming and potentially highly rewarding process. Pharmaceutical companies literally burn millions of dollar per drug to bring it to the market. The development of a new drug requires a technological expertise, human resources and huge capital investment. It also requires strict adherence to regulations on testing and manufacturing standards before a new drug comes into market and can be used in the general population, in fact, some time it fails to come into market. All these factors just increase the cost for a new chemical entity research and development. Two branches which made positive impact on drug designing process and reduce the overall cost and risk are Bioinformatics and Pharmacogenomics. Their practice in drug designing process made positive effect on overall process and they can accelerate various steps of drug designing, and reduce the cost and over all time. Current note focusses on the role of bioinformatics and pharmacogenomics in drug discovery and development process.

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Pharmacogenomics is the study of how the genetic makeup determines the response to a therapeutic intervention. It has the capability to revolutionize the practice of medicine by personalized approach for treatment through the use of novel diagnostic tools. Pharmacogenomic based approaches reduce the trial-and-error approach and restrict the exposure of patients to those drugs which are not effective or are toxic for them. Single Nucleotide Polymorphisms (SNPs) hold the key in defining the risk of an individual's susceptibility to various illnesses and response to drugs. There is an ongoing process of identifying the common, biologically relevant SNPs, in particular those that are associated with the risk of disease and adverse drug reaction. The identification and characterization of these SNPs are necessary before their use as genetic tools. Most of the ongoing SNP related studies are biased deliberately towards coding regions and the data generated from them are therefore unlikely to reflect genome wide distribution of SNPs. To avoid this biasing towards the coding regions SNP, SNP consortium protocol was designed. Though, projects like the HapMap increase credibility and use of SNPs, still there are some concern like the required sample (patient) sizes, the number of SNPs required for mapping, number of association studies, the cost of SNP genotyping, and the interpretation and explanation of results are some of the challenges that surround this field.

Phylogenetic footprinting is a method for the discovery of regulatory elements in a set of homologous regulatory regions, usually collected from multiple species. It does so by identifying the best conserved motifs in those homologous regions. There are two popular sets of methods-alignment-based and motif-based, which are generally employed for phylogenetic methods. However, serious efforts have lacked to develop a tool exclusively for phylogenetic footprinting, based on either of these methods. Nevertheless, a number of software and tools exist that can be applied for prediction of phylogenetic footprinting with variable degree of success. The output from these tools may get affected by a number of factors associated with current state of knowledge, techniques and other resources available. We here present a critical apprehension of various phylogenetic approaches with reference to prokaryotes outlining the available resources and also discussing various factors affecting footprinting in order to make a clear idea about the proper use of this approach on prokaryotes.