Leads prioritization

We have developed a rapid and systematic process for isolation and identification of biologically active components from natural products. The process reduces time and cost through application of advanced chromatographic instrumentation. It generates important activity and chemical information and also provides advanced active fraction(s) to accelerate isolation studies. As a result, lead prioritization, project management, and the cycle time of natural product lead discovery have been significantly improved. 

In collecting the data care should be taken to avoid data paralysis (see Part 2 Chapter 14). The various quality tools can be used to prioritize the identified problems and corresponding decisions. As with all data collection tasks, you should show a direct correlation between what you are collecting and the goals to be achieved and all conclusions should lead to positive action, otherwise the effort has been futile. 

The editors have chosen topics from both important therapeutic areas and from work that advances the discipline of medicinal chemistry. For example, cancer, metabolic syndrome and Alzheimer s disease are fields in which academia and industry are heavily invested to discover new drugs because of their considerable unmet medical need. The editors have therefore prioritized covering new developments in medicinal chemistry in these fields. In addition, important advances in the discipline, such as fragment-based drug design and other aspects of new lead-seeking approaches, are also planned for early volumes in this series. Each volume thus offers a unique opportunity to capture the most up-to-date perspective in an area of medicinal chemistry. 

In this chapter, the full BioPrint approach is described, as available from Cerep in terms of both the data set and the ability to have new compounds profiled and the results provided in the context of the BioPrint data set, including the known in vivo side effects of near neighbors in this biological space (see Section 2.5). The results for the differentiation of hit/lead compounds (see Section 2.3.2.1) sometimes use a subset of the 70-100 pharmacological assays that provide the maximum signal. Usually a decision on future work prioritization could be clearly made from the data from these subsets, saving time and money. For key reference/tool compounds, a full profile was used and is recommended to be used, as unexpected off-target activities may be found that cannot usually be predicted. 

This is used for screening in drug discovery and prioritization of lead compounds to improve the quality of compounds selected for development and to reduce total development time and cost. 

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