Combining mathematical modeling, in vitro data and clinical target expression to support bispecific antibody binding...

Area of Science:

• Oncology
• Immunology
• Computational Biology

Background:

• Bispecific costimulatory antibodies activate tumor-specific T cells by engaging tumor targets and T-cell costimulatory receptors.
• Trimeric complex formation, crucial for T-cell activation, follows a dose-dependent bell-shaped curve influenced by antibody binding affinities and target expression.

Purpose of the Study:

• To investigate the impact of fibroblast activation protein alpha (FAP)-binding affinity on the pharmacology of FAP-directed 4-1BB (CD137) bispecific antibodies.
• To quantify the relationship between binding affinity, target receptor requirements, patient population coverage, and effective drug exposure.

Main Methods:

• Utilized mathematical modeling and simulation to explore the pharmacology of FAP-4-1BBL bispecific antibodies.
• Quantified minimum target receptor levels for pharmacological effect and patient population coverage across 19 solid tumor indications.

Main Results:

• A 10-fold increase in FAP-binding affinity (0.7 nM to 0.07 nM K_D) reduced required FAP receptors by 70% (13,400 to 4,000) for maximal effect.
• This affinity enhancement increased predicted patient coverage for colon cancer from 6% to 39%.

Conclusions:

• A workflow integrating preclinical data, modeling, and target expression knowledge can guide the selection of optimal binding affinities for bispecific antibodies.
• Early implementation of this approach can improve the success rate of cancer immunotherapies in clinical development.