Abstract
Antibody-Drug Conjugates (ADCs) have rapidly expanded in the clinic, with 7 new approvals in 3 years. For solid tumors, high doses of ADCs improve tissue penetration and efficacy. These doses are enabled by lower drug-to-antibody ratios and/or co-administration of unconjugated antibody carrier doses to avoid payload toxicity. While effective for highly expressed targets, these strategies may not maintain efficacy with lower target expression. To address this issue, a carrier dose that adjusts binding in situ according to cellular expression was designed using computational modeling. Previous studies demonstrated that coadministration of unconjugated antibody with the corresponding ADC at an 8:1 ratio improves ADCs efficacy in high HER2 expressing tumors. By designing a High Avidity, Low Affinity (HALA) carrier antibody, ADC binding is partially blocked in high expression cells, improving tissue penetration. In contrast, the HALA antibody cannot compete with the ADC in low expressing cells, allowing ADC binding to the majority of receptors. Thus, the amount of competition from the carrier dose automatically adjusts to expression levels, allowing tailored competition between different patients/metastases. The computational model highlights two dimensionless numbers, the Thiele modulus and a newly defined competition number, to design an optimal HALA antibody carrier dose for any target.
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