Stent elution rate determines drug deposition and receptor-mediated effects

Abstract

Drug eluting stent designs abound and yet the dependence of efficacy on drug dose and elution duration remains unclear. We examined these issues within a mathematical framework of arterial drug distribution and receptor binding following stent elution. Model predictions that tissue content linearly tracks stent elution rate were validated in porcine coronary artery sirolimus-eluting stents implants. Arterial content varied for stent types, progressively declining from its Day 1 peak and tracking with rate-limiting drug elution--near zero-order release was three-fold more efficient at depositing drug in the stented lesion than near first-order release. In vivo data were consistent with an overabundance of non-specific sirolimus-binding sites relative to the specific receptors and to the delivered dose. The implication is that the persistence time of receptor saturation and effect is more sensitive to duration of elution than to eluted amount. Consequently, the eluted amount should be sufficiently high to saturate receptors at the target lesion, but dose escalation alone is an inefficient strategy for prolonging the duration of sirolimus deposition. Moreover, receptor saturating drug doses are predicted to be most efficacious when eluted from stents in a constant zero order fashion as this maximizes the duration of elution and receptor saturation.

Fig. 1

Endovascular DES are idealized as phantom interface separating arterial tissue from luminal blood, delivering a fraction f_wall of their drug load to the arterial wall and the remaining fraction 1-f_wall is cleared by luminal blood. Transmural distribution of absorbed sirolimus is governed by transmural convection and diffusion (Eq. (2)), binding to ECM sites (Eq. (3)), binding to pharmacological receptors (Eq. (4)), and adventitial clearance (Eq. (7)).

Fig. 2

In vivo pharmacokinetics of CYPHER^® Stent (blue) and prototype NEVO™ Stent (red) in the porcine coronary artery model. (A) Cumulative sirolimus elution (symbols) versus best fits (lines) of Eq. (1) (Table 1). (B) Tissue content. Asterisks denote statistically significant differences observed between SES at Days 3–30 (p<0.05).

Fig. 3

Regimes of drug binding and receptor mediated efficacy. Intimal free drug concentrations in excess of the receptor’s dissociation constant are highly efficacious (b_REC/b_REC, max>0.5) and encompass binding regimes I and II (Table S1 Online supporting material). Lower intimal free drug concentrations provide marginal (0.5>b_REC/b_REC, max>0.1) or low (b_REC/b_REC, max<0.1) receptor mediated effects. The favoring of specific over non-specific binding implies that regime I will evolve into regime II in an almost straight horizontal trajectory, and that regime II will evolve into regime III via a virtually vertical trajectory.

Fig. 4

Model validation and calibration. (A) In vivo issue content (symbols) of arteries is rendered linear when plotted against the in vivo rate of elution. Linear fits (dashes) exhibit a 2.9-fold higher slope for prototype NEVO™ Stents (red) compared to CYPHER^® Stent (blue) but similar positive intercepts that correspond to the density of sirolimus receptors. In vivo tissue content of coronary arteries stented with prototype NEVO™ Stent (B) or CYPHER^® Stent (C) are normalized to receptor density and contrasted with numerical simulations of Eqs. (2)–(7) with D_wall=1.5×10⁻⁶ cm²/s (dots), D_wall=2.0×10⁻⁶ cm²/s (lines) and D_wall=2.5×10⁻⁶ cm²/s (dashes). Insets depict the predicted fraction of sirolimus-bound receptors (Eq. (8)) and illustrate that tissue contents in excess of receptor density ensure receptor saturation for both SES.

Fig. 5

Receptor binding state is more sensitive to elution kinetics than dose. Eqs. (2)–(7) were simulated for hypothetical stents that elute 74 μg (lines) or 37 μg (dashes) by pure first order (K_fo =0.53 d⁻¹, black lines) or Higuchi (Q_sus=13.22 μg·d^−1/2, gray lines) kinetics (A). Tissue content (B) and receptor binding levels (C) were evaluated by integrating, respectively, the simulated distributions of total drug and receptor-bound drug across the thickness of the arterial wall. All simulations employed the same tissue transport parameter values (f_wall=0.06, D_wall=2.0×10⁻⁶ cm²/s with all other values listed in Table 2).