Using Avidity to Optimize the Therapeutic Index of Bispecific Drugs


An advantage of monoclonal antibodies (mAbs) as drugs is their high potency and specificity for their target.  This greatly reduces the chance of off-target toxicity common to small molecules, where toxicity is often caused by interacting similar targets.  As a result, toxicity for large molecules is often driven by on-target off-tissue toxicology where the target of the drug is expressed not just on the target cell type, but in other tissues where the same pharmacology is undesirable.  Because of their high potency even low expression of the target in other tissues can lead to dose limiting toxicities.

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. Applied BioMath Assess for Biologics with the Avidity model pack, supports early feasibility assessment for bispecific modalities. This case study demonstrates how to use 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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