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.
Presented by
Ismail Ijjaali, Ph.D.,
Director, Chemistry Applications, Informatics
Ismail Ijjaali received his Ph.D. in chemistry from Henri-Poincaré University, Nancy, France. After his post-doctoral fellowship at Northwestern University Chicago and a diploma in Computational Chemistry, Ismail spent 8 years at Aureus Sciences (now part of Elsevier) where he was involved in consulting activities for their chemical/biological knowledge databases and managing several funded European projects in drug discovery. Ismail joined PerkinElmer in 2012 and is responsible for consulting for Research Analytics.
