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Alternatively, the target can be part of the cellular machinery of a pathogen the role of the drug in this case is to kill the pathogen by interrupting the drug target. The target is a human molecule that a drug recognizes and modifies to achieve an intended therapeutic effect. It typically begins with target identification. The traditional drug discovery workflow is shown in Figure 1 in red.

PK, pharmacokinetics PD, pharmcodynamics ADME, absorption, distribution, metabolism and excretion. These include chemical structure and property prediction structure–activity relationships molecular similarity and diversity analysis compound classification and selection chemical data collection, analysis and management virtual drug screening and prediction of in vivo compound characteristics. Chemical informatics comprises a wide range of approaches from computational and combinatorial chemistry that model lead properties and their interaction with targets. *We do not emphasize chemical informatics in the main text because it relates to issues from chemistry and not biology. The impact of each computational technique on each stage of drug discovery is classified into three categories: actively or heavily used (large black dot), less actively used (small black dot) and our suggestion (small gray dot). For example, sequence analysis relies on pattern recognition and classification text mining, terminologies and knowledge engineering are entwined, as are pattern recognition and classification. Blue lines illustrate how each method is related to others. Biomarkers and analysis of the tissue distribution of target molecules are the most recently introduced checkpoints and are not required by the FDA.Ĭomputational biology methods discussed in the main text* are listed along the top row. Red arrows indicate the traditional process and yellow dashed arrows suggest novel workflows that are increasingly adopted by pharmaceutical and biotechnological companies to increase productivity. We note that the traditional linear process is shifting to become more parallel, simultaneous and cyclical. The various stages of the drug discovery process (See Box 1 for detailed background on each step) are listed in the left column. This figure summarizes how computational biology can impact drug discovery. Role of computational technologies in the drug discovery process. Here we provide an overview of what computational biology and sociology have to offer and what problems need to be solved so that these approaches can support drug discovery. Socially, we lack models that accurately capture the link between successful discovery and the dynamic organization of researchers and resources that underpins it.Ĭomputational approaches, if applied wisely, hold the potential to substantially reduce the cost of drug development by broadening the set of viable targets and by identifying novel therapeutic strategies and institutional approaches to drug discovery. Biologically, the bottleneck is our poor knowledge of molecular mechanisms underlying complex human phenotypes. In the search for new drugs there are numerous sources of error stemming from our limited understanding of the biology of drug action and the sociology of innovation. The identification of chemical agents to enhance the human physiological state – drug discovery – involves coordination of highly complex chemical, biological and social systems and requires staggering capital investment, estimated at between $100 million and $1.7 billion per drug.

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