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Mechanistically Weighted Metric to Predict In Vivo Antibody-Receptor Occupancy: An Analytical Approach.

Eshita Khera1, Jaeyeon Kim1, Andrew Stein1

  • 1Departments of Chemical Engineering (E.K., M.R., G.M.T.) and Biomedical Engineering (G.M.T.), University of Michigan, Ann Arbor, Michigan; and Novartis Institute for BioMedical Research, Cambridge, Massachusetts (J.K., A.S.).

The Journal of Pharmacology and Experimental Therapeutics
|April 27, 2023
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A new mathematical model accurately predicts antibody receptor occupancy in solid tumors, improving drug dosing and therapeutic design. This generalized metric, the mechanistically weighted global average free tissue target to initial target ratio (AFTIR), works across various doses and tumor properties.

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Area of Science:

  • Pharmacology and Pharmaceutical Sciences
  • Mathematical Biology
  • Biophysics

Background:

  • In situ clinical measurement of receptor occupancy (RO) is difficult, especially in solid tumors.
  • Existing mathematical models and potency metrics like average free tissue target to initial target ratio (AFTIR) have limitations, particularly at subsaturating antibody doses and in heterogeneous tumors.

Purpose of the Study:

  • To develop a more accurate and generalized analytical metric for predicting tumor receptor occupancy (RO) across diverse dosing regimens.
  • To improve the rational design of antibody-based therapeutics and aid clinical dose decisions.

Main Methods:

  • Employed a partial differential equation (PDE) Krogh cylinder model to simulate spatiotemporal RO.
  • Derived an analytical solution, the mechanistically weighted global AFTIR, incorporating absolute receptor density as a key parameter.
  • Validated the metric using global and local sensitivity analysis.

Main Results:

  • The generalized AFTIR metric accurately predicts RO regardless of dosing regimen, overcoming limitations of previous models.
  • The metric incorporates absolute receptor density, influencing intratumoral drug concentration and antibody penetration depth.
  • The model provides mechanistic RO predictions guided by Thiele Modulus and local saturation potential.

Conclusions:

  • The generalized AFTIR serves as a more accurate analytical metric for clinical dose decisions and antibody-based therapeutic design.
  • This simplified analytical model obviates the need for complex PDE simulations while maintaining mathematical rigor.
  • The approach accurately predicts RO across a range of drug, tumor, and dosing parameters.