High-throughput screening is an early critical step in drug discovery. Its aim is to screen a large number of diverse chemical compounds to identify candidate 'hits' rapidly and accurately. Few statistical tools are currently available, however, to detect quality hits with a high degree of confidence. We examine statistical aspects of data preprocessing and hit identification for primary screens. We focus on concerns related to positional effects of wells within plates, choice of hit threshold and the importance of minimizing false-positive and false-negative rates. We argue that replicate measurements are needed to verify assumptions of current methods and to suggest data analysis strategies when assumptions are not met. The integration of replicates with robust statistical methods in primary screens will facilitate the discovery of reliable hits, ultimately improving the sensitivity and specificity of the screening process.

/pdf/statistical-practice-in-high-throughput-screening-data-ibtjwxsp2n.pdf

Statistical practice in high-throughput screening data analysis

https://sites.bu.edu/chenlab/files/2014/01/22_BhadrirajuDDT02.pdf

Engineering cellular microenvironments to improve cell-based drug testing.

Natural products historically have been a rich source of lead molecules in drug discovery, based on their capability to create unique and diverse chemical structures However, it is also true that the vast number of metabolites typically present in natural products and their huge dynamic range results in the loss of many possibly bioactive natural compounds, becoming an inextricable obstacle for drug development Recently, new strategies which favour a holistic approach as opposed to the traditional reductionist methods used previously, have been introduced with the purpose of overcoming the bottlenecks in natural product research This approach is based on the application of new technologies, including metabolomics, for example Metabolomics allows a systematic study of a complex mixture such as a phytochemical preparation, which can be linked to observations obtained through biological testing systems without the need for isolating active principles This may put drug discovery from natural products back in the limelight again In this review paper, the description of some examples of successful metabolomics applications in several important fields related to drug discovery from natural sources aims at raising the potential of metabolomics in reducing the gap between natural products (NP) and modern drug discovery demand

/pdf/metabolomics-for-bioactivity-assessment-of-natural-products-yk1e31uxm8.pdf

Metabolomics for bioactivity assessment of natural products

Increasing insight into the genetics and molecular biology of cancer has resulted in the identification of an increasing number of potential molecular targets for anti-cancer drug discovery and development. These targets can be approached through exploitation of emerging structural biology,”rational“ drug design, screening of chemical libraries, or a combination of these methods. In this article we discuss the application of high-throughput screening to anti-cancer drug discovery, with special reference to approaches used at the U.S. National Cancer Institute.

Application of high-throughput, molecular-targeted screening to anticancer drug discovery.

https://www.cell.com/trends/biotechnology/pdf/S0167-7799(02)01906-6.pdf

Edward J. Hunnicutt

Papers

HTS in the new millennium: the role of pharmacology and flexibility.