Mass spectrometry methods and mathematical PK/PD model for decision tree-guided covalent drug development.

Abstract

Covalent drug discovery efforts are growing rapidly but have major unaddressed limitations. These include high false positive rates during hit-to-lead identification; the inherent uncoupling of covalent drug concentration and effect [i.e., uncoupling of pharmacokinetics (PK) and pharmacodynamics (PD)]; and a lack of bioanalytical and modeling methods for determining PK and PD parameters. We present a covalent drug discovery workflow that addresses these limitations. Our bioanalytical methods are based upon a mass spectrometry (MS) assay that can measure the percentage of drug-target protein conjugation (% target engagement) in biological matrices. Further we develop an intact protein PK/PD model (iPK/PD) that outputs PK parameters (absorption and distribution) as well as PD parameters (mechanism of action, protein metabolic half-lives, dose, regimen, effect) based on time-dependent target engagement data. Notably, the iPK/PD model is applicable to any measurement (e.g., bottom-up MS and other drug binding studies) that yields % of target engaged. A Decision Tree is presented to guide researchers through the covalent drug development process. Our bioanalytical methods and the Decision Tree are applied to two approved drugs (ibrutinib and sotorasib); the most common plasma off-target, human serum albumin; three protein targets (KRAS, BTK, SOD1), and to a promising SOD1-targeting ALS drug candidates.