Design of Optimized Hypoxia-Activated Prodrugs Using Pharmacokinetic/Pharmacodynamic Modeling

Abstract

Hypoxia contributes to resistance of tumors to some cytotoxic drugs and to radiotherapy, but can in principle be exploited with hypoxia-activated prodrugs (HAP). HAP in clinical development fall into two broad groups. Class I HAP (like the benzotriazine N-oxides tirapazamine and SN30000), are activated under relatively mild hypoxia. In contrast, Class II HAP (such as the nitro compounds PR-104A or TH-302) are maximally activated only under extreme hypoxia, but their active metabolites (effectors) diffuse to cells at intermediate O2 and thus also eliminate moderately hypoxic cells. Here, we use a spatially resolved pharmacokinetic/pharmacodynamic (SR-PK/PD) model to compare these two strategies and to identify the features required in an optimal Class II HAP. The model uses a Green’s function approach to calculate spatial and longitudinal gradients of O2, prodrug, and effector concentrations, and resulting killing in a digitized 3D tumor microregion to estimate activity as monotherapy and in combination with radiotherapy. An analogous model for a normal tissue with mild hypoxia and short intervessel distances (based on a cremaster muscle microvessel network) was used to estimate tumor selectivity of cell killing. This showed that Class II HAP offer advantages over Class I including higher tumor selectivity and greater freedom to vary prodrug diffusibility and rate of metabolic activation. The model suggests that the largest gains in class II HAP antitumor activity could be realized by optimizing effector stability and prodrug activation rates. We also use the model to show that diffusion of effector into blood vessels is unlikely to materially increase systemic exposure for realistic tumor burdens and effector clearances. However, we show that the tumor selectivity achievable by hypoxia-dependent prodrug activation alone is limited if dose-limiting normal tissues are even mildly hypoxic.

Pharmacokinetic modeling of ascorbate diffusion through normal and tumor tissue

“…Three-dimensional simulations were performed in a digitized microvascular network previously obtained from a mapped FaDu window chamber xenograft [32] to represent tumor tissue and a mapped rat cremaster muscle microvascular network [33] to represent well-organized normal tissue as previously described for anti-cancer prodrugs [34]. The 3D reaction diffusion equations are solved for oxygen and ascorbate using a Green's function approach [27,33], which calculates the oxygen and intracellular and extracellular ascorbate concentrations at each tissue point and includes extraction from the blood vessels.…”

“…Mapped, digitized microvessel networks of FaDu xenografts from rat window chambers [32] or rat cremaster muscle tissue [33], previously used to simulate drug distribution [34], were used with the ascorbate diffusion model. The vascular network of normal tissue, which has a maximum intervessel distance of 50 μm, is clearly more organized and functional compared to the FaDu tumor tissue vasculature (Fig.…”

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

“…Mathematical models explored how to effectively use HAPs. Foehrenbacher et al [108] used a Green's function approach to calculate tumour response to this treatment and the 3D spatial and longitudinal gradients of oxygen and drug concentrations. The authors showed that, to increase HAPs' antitumour activity, the rates of effector stability and pro-drug activation should be optimized.…”

Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape

“…Multiple HAPs have been evaluated for their clinical potential, both as monotherapies and as part of combination therapies [12,8]. Class I HAPs are activated in moderately hypoxic environments whilst Class II HAPs require more severe hypoxia to undergo the HAP to AHAP bioreduction [23]. One such Class II HAP is evofosfamide, or TH-302, which has been tested in clinical Phase I-III trials [12,1].…”

“…Foehrenbacher et al [30] have deployed a Green's function method, in customised form, and pharmacokinetic/pharmacodynamic (PK/PD) modelling to quantify anticancer bystander effects elicited by the HAP PR-104 in a simulated, three-dimensional tumour comprising a microvascular network. Another concurrent article used similar mathematical concepts to compare Class I HAPs to Class II HAPs and, furthermore, to determine optimal properties for Class II HAPs [23]. Lindsay et al [31] developed a stochastic model to study monotherapies and combination therapies involving HAPs, specifically TH-302, and erlotinib.…”