Dose is perhaps the most quantitative and holistic metric reflecting the therapeutic potential of a given molecule. Accordingly, dose is predicted at many stages across pharmaceutical research and development in support of candidate development. Although less common, dose predictions at the earliest stages of drug design are perhaps the most useful in that they provide a clinically-relevant line of sight into the balance of properties necessary for clinical success. Dose predictions at this stage can identify critical drug properties for a viable dose regimen and provide clinically-relevant translational context to data used in lead optimization. However, there are several scientific and operational challenges that are unique to this space of application that must be considered. In this session, an overview of the opportunity and challenges associated with dose predictions for design will be presented. Several general considerations, approaches and case examples will also be provided.

Dose predictions in support of clinically relevant multiparametric lead optimization

ACS Spring Meeting 2021

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