Guiding dose selection of monoclonal antibodies using a new parameter (AFTIR) for characterizing ligand binding...

Area of Science:

• Pharmacology and Drug Development
• Quantitative Systems Pharmacology
• Oncology Drug Discovery

Background:

• Monoclonal antibody (mAb) oncology drug dosing relies on predicting tumor receptor occupancy.
• Existing metrics like AFIR characterize target inhibition but lack tissue-specific dynamics.
• Modeling complex drug-target interactions requires accounting for target shedding and tissue distribution.

Purpose of the Study:

• To extend previous target inhibition metrics to incorporate a "target-tissue" compartment and target shedding.
• To derive a new potency metric, average free tissue target to initial target ratio (AFTIR), for steady-state analysis.
• To simplify complex pharmacokinetic/pharmacodynamic (PK/PD) models for better dose selection guidance.

Main Methods:

• Extension of the AFIR (average free inhibitor to receptor) metric to include target-tissue dynamics.
• Derivation of the AFTIR metric, dependent on equilibrium binding constant, target expression fold-change, target biodistribution, and average drug concentration.
• Application of the AFTIR metric for sensitivity analyses and building intuition in target-mediated drug disposition (TMDD) models.

Main Results:

• The AFTIR metric quantifies target inhibition at steady state, considering tissue-specific factors.
• AFTIR depends on four key parameters: binding affinity, target expression change, target biodistribution, and drug concentration.
• The derived metric simplifies complex physiological models, highlighting critical parameters for experimental estimation.

Conclusions:

• The AFTIR metric provides a robust tool for guiding dose selection of mAb oncology drugs.
• It facilitates efficient sensitivity analyses and enhances understanding of TMDD models.
• Reducing model complexity to four key parameters aids in prioritizing experimental efforts for drug development.