# Experimental and Mathematical Model of Platelet Hemostasis Kinetics

## TL;DR

This paper combines experiments and math to model how platelets change states during blood clotting, revealing new insights into their activation and inhibition.

## Contribution

A novel integrated experimental and mathematical model of platelet phenotypic transitions with experimentally derived rate constants.

## Key findings

- Platelet aggregation correlates with αIIbβ3 integrin activation measured via laser diffraction.
- Platelet desensitization occurs at multiple stages with distinct kinetics for shape change and integrin deactivation.
- Iloprost inhibits ADP-induced aggregation only if applied before stimulation; otherwise, aggregation becomes irreversible.

## Abstract

Upon activation, platelets undergo rapid phenotypic transitions to maintain hemostasis, yet the kinetics governing these transitions remain poorly quantified. We present an integrated experimental and mathematical model describing platelet transitions between resting, activated, aggregating, inhibited, and exhausted phenotypes, determined by experiment rate constants for these reactions. Theoretical simulations of platelet transitions accurately describe the independently determined experimental read-out. Platelet aggregation under the conditions used directly correlates with the activation of αIIbβ3 integrins, demonstrating that the parameters of platelet aggregation achieved by the laser diffraction technique can be used for the evaluation of the rapid activation and deactivation kinetics of αIIbβ3 integrins. We demonstrate that platelet desensitization occurs at multiple activation stages, with distinct kinetic profiles for shape change and integrin deactivation. We also show that even 5 s of receptor-mediated PKA activation (iloprost) is sufficient for a complete inhibition of ADP-induced platelet aggregation. However, when iloprost was added after platelet stimulation by ADP, platelet activation was not fully inhibited, and after 180 s, aggregation became irreversible. The presented data help to understand the mechanisms of platelet transition between different phenotypes. The model effectively characterizes key physiological phenotypes and can serve as a modular framework for integration into more comprehensive models.