Small molecule drug discovery aims to find clinical candidates that are safe and efficacious. ADME properties such as rate of metabolic elimination, drug half-life and absorption are key aspect of the drug safety and efficacy profile. The optimal pharmacokinetic profile is a function of the PKPD relationship; inhibitors of targets requiring continuous drug exposure over the minimum efficacious plasma concentration during the entire dosing interval, warrant optimization strategies that are different from those suited for inhibitors of targets modulated via threshold (Cmax) effect.  Nevertheless the concept of "drug-likeness", which has been pivotal in educating Medicinal Chemistry on the importance of ADME modulation, reduces the lead optimization exercise to a one size-fits all approach. In silico computational ADME, a field at the interface between machine learning, PBPK and computational chemistry offers a more suitable description of the lead optimization challenge. This presentation seeks to discuss strategies to optimize drug dose leveraging PK modeling, data mining and computational chemistry.

Dose optimization concepts in drug design

2019 Fall National Meeting

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