Clearance prediction for Amgen molecules against Extended Clearance Classification System (ECCS) and future directions. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Agarwal, Prashant; Ishida, Kazuya; Reid, Darren L.; Gupta, Anshul
• Is Part Of: Drug discovery today. Volume 26:Issue 1(2021)
• Page Start: 10
• Page End: 16
• Publication Date: 2021-01
• Subjects: Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2020.10.008
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: Early prediction of elimination pathway for new chemical entities is important. ECCS framework can help in elimination pathway prediction but with limited applicability. PSA, cLogP and ionization state are the most influential in classifying molecules based on their elimination pathway. Revision of ECCS is warranted to reflect the changing physicochemical space of molecules. Abstract : Early prediction of elimination pathways for new chemical entities can have a profound impact on drug discovery programs. The recently proposed Extended Clearance Classification System (ECCS) is a step in the right direction, providing a framework to help identify the major elimination pathway of a drug. A list of 42 Amgen small molecules was evaluated against the ECCS framework to assess its performance in retrospectively predicting their major elimination pathway. Here, we present a critical analysis of the chemical space defined by the ECCS framework with the aim of identifying its applicability and constraints. This evaluation highlights the critical need for periodic review and revision of ECCS, given that target constraints are moving molecules away from the traditional 'drug-like' physicochemical space.