Requisite dose regimen 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 (e.g. candidate nomination, clinical trial design, commercialization).  Although less common, dose predictions at the earliest stages of drug design are perhaps the most useful in that they provide a quantitative 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 preclinical 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.<br/>

Dose predictions in support of clinically-relevant multiparametric optimization in design

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.