Bispecific drugs have great potential to improve tissue selectivity through avid binding interactions, but introduce non-trivial drug design parameters that must be considered as part of target selection and lead identification.
This case study demonstrates how to use Applied BioMath Assess™ to identify the level of avidity required for a drug to have a favorable efficacy and therapeutic index. It also illustrates how drug design decisions can benefit from modeling and simulation due to non-trivial impacts on drug behavior.
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