Using Data Analytics to analyze ADME-T data

Drug Adsorption, Distribution, Metabolism, Excretion, and Toxicity (ADME-T) are critical in determining whether a new molecular entity will become a clinical candidate and subsequently a commercially available drug. Therefore, rules have been developed to describe the relationship between a compound and its corresponding ADME-T properties. The analysis of these relationships is of fundamental importance in understanding the structural determinants of biological activity, and it underpins lead generation for drug development. Small changes in molecular structure and properties can have diverse effects on biological efficacy and potency, bioavailability and metabolic stability. On the other hand, due to the accumulation of large amounts of ADME-T data, visualization & data mining techniques are key aspects of both the analysis and understanding of structure-property data.

Using the public ChEMBL database, we will illustrate how interactive visualizations and data analysis can help scientists to explore available ADME-T data and extract hidden structure-activity patterns. Among multiple applications of exploratory visualizations we will be illustrating in the presented case study:

- Structural properties determining in vivo pharmacokinetics & toxicity,

- Chemical diversity analysis by ADME-T properties,

- Drug metabolism & toxicology profiling.

Presenter:

Ismail Ijjaali, Ph.D | Director, Chemistry Applications, PerkinElmer Informatics