Challenging Interchangeability: Dynamic Dose-Response Modelling of Botulinum Toxin A Products

Area of Science:

• Pharmacology
• Computational Biology
• Aesthetics and Therapeutics

Background:

• Current Botulinum Neurotoxin type A (BoNT-A) dose conversions are empirical and lack precision.
• Significant pharmacodynamic variability exists among different BoNT-A formulations.
• A need exists for dynamic, time-resolved dose equivalence estimates for improved clinical application.

Purpose of the Study:

• To generate dynamic, time-resolved dose equivalence estimates for six FDA-approved BoNT-A formulations.
• To compare the clinical performance and temporal efficacy of onabotulinumtoxinA (ONA), abobotulinumtoxinA (ABO), incobotulinumtoxinA (INCO), daxibotulinumtoxinA (DAXI), prabotulinumtoxinA (PRABO), and letibotulinumtoxinA (LETI).
• To establish a robust framework for effect-based dose equivalence.

Main Methods:

• Development of a hybrid, time-resolved in silico pharmacodynamic model.
• Simulation of onset, peak effect, and decay kinetics in 10,000 virtual patients per formulation.
• Determination of dose equivalence using Area Under the Response Curve (AURC) and time above efficacy threshold, with external validation.

Main Results:

• Simulated durations varied from 10.6 weeks (ABO) to 14.5 weeks (PRABO).
• Significant temporal drift in conversion ratios observed, with ABO and LETI showing increasing ratios and DAXI/PRABO showing decreasing ratios.
• PRABO and DAXI demonstrated highest efficiency (AURC/unit), while decay rate (koff) was the primary determinant of efficacy duration.

Conclusions:

• Static dose conversion ratios are inadequate for representing BoNT-A formulation dynamics.
• The simulation-based approach accurately reproduces clinical outcomes and provides a reliable method for dose equivalence.
• This data-driven framework enhances precision in product substitution and personalized treatment planning for BoNT-A therapies.