Spatial Modeling of Drug Delivery Routes for Treatment of Disseminated Ovarian Cancer

Phase 1b study of intraperitoneal ipilimumab and nivolumab in patients with recurrent gynecologic malignancies with peritoneal carcinomatosis

BACKGROUND

Intravenous immune checkpoint blockade (ICB) has shown poor response rates in recurrent gynecologic malignancies. Intraperitoneal (i.p.) ICB may result in enhanced T cell activation and anti-tumor immunity.

METHODS

In this phase 1b study, registered at Clinical.

TRIALS

gov (NCT03508570), initial cohorts received i.p. nivolumab monotherapy, and subsequent cohorts received combination i.p. nivolumab every 2 weeks and i.p. ipilimumab every 6 weeks, guided by a Bayesian design. The primary objective was determination of the recommended phase 2 dose (RP2D) of the combination. Secondary outcomes included toxicity, objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).

FINDINGS

The trial enrolled 23 patients: 18 with ovarian cancer, 2 with uterine cancer, and 3 with cervical cancer. Study evaluable patients (n = 16) received a median of 2 prior lines of therapy (range: 1-8). Partial response was observed in 2 patients (12.5%; 1 ovarian, 1 uterine), and complete response was observed in 1 patient (6.3%) with cervical cancer, for an ORR of 18.8% (95% confidence interval: 4.0%-45.6%). The median duration of response was 14.8 months (range: 4.1-20.8), with one complete response ongoing. Median PFS and OS were 2.7 months and not reached, respectively. Grade 3 or higher immune-related adverse events occurred in 2 (8.7%) patients.

CONCLUSIONS

i.p. administration of dual ICB is safe and demonstrated durable responses in a subset of patients with advanced gynecologic malignancy. The RP2D is 3 mg/kg i.p. nivolumab every 2 weeks plus 1 mg/kg ipilimumab every 6 weeks.

FUNDING

This work was funded by Bristol Myers Squibb (CA209-9C7), an MD Anderson Cancer Center Support Grant (CA016672), the Ovarian Cancer Moon Shots Program, the Emerson Collective Fund, and a T32 training grant (CA101642).

Image-Based Modeling of Drug Delivery during Intraperitoneal Chemotherapy in a Heterogeneous Tumor Nodule

Intraperitoneal (IP) chemotherapy is a promising treatment approach for patients diagnosed with peritoneal carcinomatosis, allowing the direct delivery of therapeutic agents to the tumor site within the abdominal cavity. Nevertheless, limited drug penetration into the tumor remains a primary drawback of this method. The process of delivering drugs to the tumor entails numerous complications, primarily stemming from the specific pathophysiology of the tumor. Investigating drug delivery during IP chemotherapy and studying the parameters affecting it are challenging due to the limitations of experimental studies. In contrast, mathematical modeling, with its capabilities such as enabling single-parameter studies, and cost and time efficiency, emerges as a potent tool for this purpose. In this study, we developed a numerical model to investigate IP chemotherapy by incorporating an actual image of a tumor with heterogeneous vasculature. The tumor's geometry is reconstructed using image processing techniques. The model also incorporates drug binding and uptake by cancer cells. After 60 min of IP treatment with Doxorubicin, the area under the curve (AUC) of the average free drug concentration versus time curve, serving as an indicator of drug availability to the tumor, reached 295.18 mol·m-3·s-1. Additionally, the half-width parameter W1/2, which reflects drug penetration into the tumor, ranged from 0.11 to 0.14 mm. Furthermore, the treatment resulted in a fraction of killed cells reaching 20.4% by the end of the procedure. Analyzing the spatial distribution of interstitial fluid velocity, pressure, and drug concentration in the tumor revealed that the heterogeneous distribution of tumor vasculature influences the drug delivery process. Our findings underscore the significance of considering the specific vascular network of a tumor when modeling intraperitoneal chemotherapy. The proposed methodology holds promise for application in patient-specific studies.

Agent-based modeling predicts RAC1 is critical for ovarian cancer metastasis

Experimental and computational studies pinpoint rate-limiting step(s) in metastasis governed by Rac1. Using ovarian cancer cell and animal models, Rac1 expression was manipulated, and quantitative measurements of cell-cell and cell-substrate adhesion, cell invasion, mesothelial clearance, and peritoneal tumor growth discriminated the tumor behaviors most highly influenced by Rac1. The experimental data were used to parameterize an agent-based computational model simulating peritoneal niche colonization, intravasation, and hematogenous metastasis to distant organs. Increased ovarian cancer cell survival afforded by the more rapid adhesion and intravasation upon Rac1 overexpression is predicted to increase the numbers of and the rates at which tumor cells are disseminated to distant sites. Surprisingly, crowding of cancer cells along the blood vessel was found to decrease the numbers of cells reaching a distant niche irrespective of Rac1 overexpression or knockdown, suggesting that sites for tumor cell intravasation are rate limiting and become accessible if cells intravasate rapidly or are displaced due to diminished viability. Modeling predictions were confirmed through animal studies of Rac1-dependent metastasis to the lung. Collectively, the experimental and modeling approaches identify cell adhesion, rapid intravasation, and survival in the blood as parameters in the ovarian metastatic cascade that are most critically dependent on Rac1.

A multiscale cell-based model of tumor growth for chemotherapy assessment and tumor-targeted therapy through a 3D computational approach

OBJECTIVES

Computational modeling of biological systems is a powerful tool to clarify diverse processes contributing to cancer. The aim is to clarify the complex biochemical and mechanical interactions between cells, the relevance of intracellular signaling pathways in tumor progression and related events to the cancer treatments, which are largely ignored in previous studies.

MATERIALS AND METHODS

A three-dimensional multiscale cell-based model is developed, covering multiple time and spatial scales, including intracellular, cellular, and extracellular processes. The model generates a realistic representation of the processes involved from an implementation of the signaling transduction network.

RESULTS

Considering a benign tumor development, results are in good agreement with the experimental ones, which identify three different phases in tumor growth. Simulating tumor vascular growth, results predict a highly vascularized tumor morphology in a lobulated form, a consequence of cells' motile behavior. A novel systematic study of chemotherapy intervention, in combination with targeted therapy, is presented to address the capability of the model to evaluate typical clinical protocols. The model also performs a dose comparison study in order to optimize treatment efficacy and surveys the effect of chemotherapy initiation delays and different regimens.

CONCLUSIONS

Results not only provide detailed insights into tumor progression, but also support suggestions for clinical implementation. This is a major step toward the goal of predicting the effects of not only traditional chemotherapy but also tumor-targeted therapies.

Surface-fill hydrogel attenuates the oncogenic signature of complex anatomical surface cancer in a single application

Tumours growing in a sheet-like manner on the surface of organs and tissues with complex topologies represent a difficult-to-treat clinical scenario. Their complete surgical resection is difficult due to the complicated anatomy of the diseased tissue. Residual cancer often responds poorly to systemic therapy and locoregional treatment is hindered by the limited accessibility to microscopic tumour foci. Here we engineered a peptide-based surface-fill hydrogel (SFH) that can be syringe- or spray-delivered to surface cancers during surgery or used as a primary therapy. Once applied, SFH can shape change in response to alterations in tissue morphology that may occur during surgery. Implanted SFH releases nanoparticles composed of microRNA and intrinsically disordered peptides that enter cancer cells attenuating their oncogenic signature. With a single application, SFH shows efficacy in four preclinical models of mesothelioma, demonstrating the therapeutic impact of the local application of tumour-specific microRNA, which might change the treatment paradigm for mesothelioma and possibly other surface cancers.

Maximum Tolerated Dose and Anti-Tumor Activity of Intraperitoneal Cantrixil (TRX-E-002-1) in Patients with Persistent or Recurrent Ovarian Cancer, Fallopian Tube Cancer, or Primary Peritoneal Cancer: Phase I Study Results

Survival outcomes in ovarian cancer are poor. The aims of this Phase I progressive design study (NCT02903771) were to evaluate the maximum tolerated dose (MTD), tolerability, and antitumor activity of Cantrixil-a novel third-generation benzopyran molecule-in patients (n = 25) with advanced, recurrent/persistent epithelial ovarian, primary peritoneal, or fallopian tube cancer. All had completed ≥ 2 prior regimens; 3 (12%) had platinum-refractory disease, and 17 (68%) had platinum-resistant disease. Following intraperitoneal (IP) port placement, patients received weekly IP Cantrixil in 3-week cycles as monotherapy (Cycles 1-2), and then in combination with intravenous (IV) chemotherapy (Cycles 3-8). Part A (dose escalation) enrolled 11 patients in 6 dose-level cohorts. An MTD of 5 mg/kg was established with dose-limiting toxicity of ileus. Most treatment-related adverse events were gastrointestinal. Across Parts A and B (dose expansion), 16 (64%) patients received ≥ 1 3-week Cantrixil cycle, and had ≥ 1 post-baseline efficacy measurement available. The results show promising anti-tumor activity in monotherapy (stable disease rate of 56%) and in combination with IV chemotherapy (objective response rate of 19%, disease control rate of 56%, and median progression-free survival of 13.1 weeks). The molecular target and mechanism of action of Cantrixil are yet to be confirmed. Preliminary analysis of stem cell markers suggests that IP Cantrixil might induce ovarian cancer stem cell death and sensitize cells to standard chemotherapy, warranting further evaluation.

Albumin-based cancer therapeutics for intraperitoneal drug delivery: a review

Albumin is a remarkable carrier protein with multiple cellular receptor and ligand binding sites, which are able to bind and transport numerous endogenous and exogenous compounds. The development of albumin-bound drugs is gaining increased importance in the targeted delivery of cancer therapy. Intraperitoneal (IP) drug delivery represents an attractive strategy for the local treatment of peritoneal metastasis (PM). PM is characterized by the presence of widespread metastatic tumor nodules on the peritoneum, mostly originating from gastro-intestinal or gynaecological cancers. Albumin as a carrier for chemotherapy holds considerable promise for IP delivery in patients with PM. Data from recent (pre)clinical trials suggest that IP albumin-bound chemotherapy may result in superior efficacy in the treatment of PM compared to standard chemotherapy formulations. Here, we review the evidence on albumin-bound chemotherapy with a focus on IP administration and its efficacy in PM.

Quantification of fluorophore distribution and therapeutic response in matched in vivo and ex vivo pancreatic cancer model systems

Therapeutic resistance plagues cancer outcomes, challenging treatment particularly in aggressive disease. A unique method to decipher drug interactions with their targets and inform therapy is to employ fluorescence-based screening tools; however, to implement productive screening assays, adequate model systems must be developed. Patient-derived pancreatic cancer models (e.g., cell culture, patient-derived xenograft mouse models, and organoids) have been traditionally utilized to predict personalized therapeutic response. However, cost, long read out times and the inability to fully recapitulate the tumor microenvironment have rendered most models incompatible with clinical decision making for pancreatic ductal adenocarcinoma (PDAC) patients. Tumor explant cultures, where patient tissue can be kept viable for up to weeks, have garnered interest as a platform for delivering personalized therapeutic prediction on a clinically relevant timeline. To fully explore this ex vivo platform, a series of studies were completed to quantitatively compare in vivo models with tumor explants, examining gemcitabine therapeutic efficacy, small molecule uptake and drug-target engagement using a novel fluorescently-labeled gemcitabine conjugate. This initial work shows promise for patient-specific therapeutic selection, where tumor explant drug distribution and response recapitulated the in vivo behavior and could provide a valuable platform for understanding mechanisms of therapeutic response and resistance.

Ginsenoside Rh2 pretreatment and withdrawal reactivated the pentose phosphate pathway to ameliorate intracellular redox disturbance and promoted intratumoral penetration of adriamycin

Improving the limited penetration, accumulation and therapeutic effects of antitumor drugs in the avascular region of the tumor mass is crucial during chemotherapy. P-gp inhibitors have achieved little success despite significant efforts. Excessive P-gp inhibition disturbed the kinetic balance between intracellular accumulation and intercellular penetration, thus resulting in a more inhomogeneous distribution of substrate drugs. Here, we found that ginsenoside Rh2 pretreatment mildly downregulated P-gp expression through reactivating the pentose phosphate pathway and rebalancing redox status. This mild P-gp inhibition not only significantly increased the growth inhibition effect and accumulation profile of adriamycin (ADR) throughout the multicellular tumor spheroid (MCTS) but also had unique advantages in improving drug penetration. Furthermore, we developed a novel individual-cell-based PK-PD integrated model and proved that metabolic reprogramming and redox rebalancing-based P-gp regulation was sufficient to increase the ADR effect in both central and peripheral cells of MCTS. Thus, a “ginsenoside Rh2-ADR” sequential regimen was proposed and exhibited a potent antitumor effect in vivo. This novel P-gp inhibition via metabolic reprogramming and redox rebalancing provided a new idea for achieving better antitumor effects in the tumor avascular region during chemotherapy.

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Rh2 pretreatment downregulated P-gp expression through metabolic reprogramming and redox rebalancing.

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Rh2-pretreatment improved ADR penetration into the core of MCTS and tumour mass.

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“Ginsenoside Rh2-ADR” sequential regimen exhibited potent antitumor effects in vivo.

A 3D CFD model of the interstitial fluid pressure and drug distribution in heterogeneous tumor nodules during intraperitoneal chemotherapy

Although intraperitoneal chemotherapy (IPC) has evolved into an established treatment modality for patients with peritoneal metastasis (PM), drug penetration into tumor nodules remains limited. Drug transport during IPC is a complex process that depends on a large number of different parameters (e.g. drug, dose, tumor size, tumor pressure, tumor vascularization). Mathematical modeling allows for a better understanding of the processes that underlie drug transport and the relative importance of the parameters influencing it. In this work, we expanded our previously developed 3D Computational Fluid Dynamics (CFD) model of the drug mass transport in idealized tumor nodules during IP chemotherapy to include realistic tumor geometries and spatially varying vascular properties. DCE-MRI imaging made it possible to distinguish between tumorous tissues, healthy surrounding tissues and necrotic zones based on differences in the vascular properties. We found that the resulting interstitial pressure profiles within tumors were highly dependent on the irregular geometries and different zones. The tumor-specific cisplatin penetration depths ranged from 0.32 mm to 0.50 mm. In this work, we found that the positive relationship between tumor size and IFP does not longer hold in the presence of zones with different vascular properties, while we did observe a positive relationship between the percentage of viable tumor tissue and the maximal IFP. Our findings highlight the importance of incorporating both the irregular tumor geometries and different vascular zones in CFD models of IPC.

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

A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.

Establishment of a rat ovarian peritoneal metastasis model to study pressurized intraperitoneal aerosol chemotherapy (PIPAC)

BACKGROUND

pressurized intraperitoneal aerosol chemotherapy (PIPAC), with or without electrostatic precipitation (ePIPAC), was recently introduced in the treatment of peritoneal metastases (PM) from ovarian cancer (OC). Preliminary clinical data are promising, but several methodological issues as well the anticancer efficacy of PIPAC remain unaddressed. Here, we propose a rat ePIPAC model that allows to study these issues in a clinically relevant, reproducible, and high throughput model.

METHODS

laparoscopy and PIPAC were established in healthy Wistar rats. Aerosol properties were measured using laser diffraction spectrometry based granulometric analyses. Electrostatic precipitation was accomplished using a commercially available generator (Ultravision™). A xenograft model of ovarian PM was created in athymic rats using intraperitoneal (IP) injection of SKOV-3 luciferase positive cells. Tumor growth was monitored weekly by in vivo bioluminescence imaging.

RESULTS

PIPAC and electrostatic precipitation were well tolerated using a capnoperitoneum of 8 mmHg. All rats survived the (e)PIPAC procedure and no gas or aerosol leakage was observed over the entire procedure. With an injection pressure of 20 bar, granulometry showed a mean droplet diameter (D(v,0.5)) of 47 μm with a flow rate of 0.5 mL/s, and a significantly lower diameter (30 μm) when a flow rate of 0.8 mL/s was used. Experiments using IP injection of SKOV-3 luciferase positive cells showed that after IP injection of 20 × 10⁶ cells, miliary PM was observed in all animals. PIPAC was feasible and well supported in these tumor bearing animals.

CONCLUSIONS

we propose a reproducible and efficient rodent model to study PIPAC and ePIPAC in OC xenografts with widespread PM. This model allows to characterize and optimize pharmacokinetic and biophysical parameters, and to evaluate the anti-cancer efficacy of (e)PIPAC treatment.

Penetration Efficiency of Antitumor Agents in Ovarian Cancer Spheroids: The Case of Recombinant Targeted Toxin DARPin-LoPE and the Chemotherapy Drug, Doxorubicin

The efficiency of delivering a therapeutic agent into a tumor is among the crucial factors determining the prospects for its clinical use. This problem is particularly acute in the case of targeted antitumor agents since many of them are high-molecular-weight compounds. In this work, the penetration of therapeutic agents of two distinct molecular weights into the spheroids of ovarian adenocarcinoma overexpressing human epidermal growth factor receptor 2 (HER2) was studied. It was shown that the low-molecular-weight chemotherapy drug, doxorubicin (~0.5 kDa), effectively penetrates through almost the entire depth of a 300 to 400 μm spheroid, while the penetration depth of the HER2-specific recombinant targeted toxin, DARPin-LoPE (~42 kDa), is only a few surface layers of cells and does not exceed 70 μm. The low penetration of the targeted toxin into spheroid was shown along with a significant decrease in its efficiency against the three-dimensional tumor spheroid as compared with the two-dimensional monolayer culture. The approaches to increasing the accumulation of agents in the tumor are presented and prospects of their use in order to improve the effectiveness of therapy are discussed.

Modeling three-dimensional invasive solid tumor growth in heterogeneous microenvironment under chemotherapy

A systematic understanding of the evolution and growth dynamics of invasive solid tumors in response to different chemotherapy strategies is crucial for the development of individually optimized oncotherapy. Here, we develop a hybrid three-dimensional (3D) computational model that integrates pharmacokinetic model, continuum diffusion-reaction model and discrete cell automaton model to investigate 3D invasive solid tumor growth in heterogeneous microenvironment under chemotherapy. Specifically, we consider the effects of heterogeneous environment on drug diffusion, tumor growth, invasion and the drug-tumor interaction on individual cell level. We employ the hybrid model to investigate the evolution and growth dynamics of avascular invasive solid tumors under different chemotherapy strategies. Our simulations indicate that constant dosing is generally more effective in suppressing primary tumor growth than periodic dosing, due to the resulting continuous high drug concentration. In highly heterogeneous microenvironment, the malignancy of the tumor is significantly enhanced, leading to inefficiency of chemotherapies. The effects of geometrically-confined microenvironment and non-uniform drug dosing are also investigated. Our computational model, when supplemented with sufficient clinical data, could eventually lead to the development of efficient in silico tools for prognosis and treatment strategy optimization.

Cell-based computational model of early ovarian development in mice

Despite its importance to reproduction, certain mechanisms of early ovarian development remain a mystery. To improve our understanding, we constructed the first cell-based computational model of ovarian development in mice that is divided into two phases: Phase I spans embryonic day 5.5 (E5.5) to E12.5; and Phase II spans E12.5 to postnatal day 2. We used the model to investigate four mechanisms: in Phase I, (i) whether primordial germ cells (PGCs) undergo mitosis during migration; and (ii) if the mechanism for secretion of KIT ligand from the hindgut resembles inductive cell-cell signaling or is secreted in a static manner; and in Phase II, (iii) that changes in cellular adhesion produce germ cell nest breakdown; and (iv) whether localization of primordial follicles in the cortex of the ovary is due to proliferation of granulosa cells. We found that the combination of the first three hypotheses produced results that aligned with experimental images and PGC abundance data. Results from the fourth hypothesis did not match experimental images, which suggests that more detailed processes are involved in follicle localization. Phase I and Phase II of the model reproduce experimentally observed cell counts and morphology well. A sensitivity analysis identified contact energies, mitotic rates, KIT chemotaxis strength, and diffusion rate in Phase I and oocyte death rate in Phase II as parameters with the greatest impact on model predictions. The results demonstrate that the computational model can be used to understand unknown mechanisms, generate new hypotheses, and serve as an educational tool.

MircroRNA-139 sensitizes ovarian cancer cell to cisplatin-based chemotherapy through regulation of ATP7A/B

PURPOSE

Ovarian cancer remains a most malignant female cancer nowadays. The acquisition of chemoresistance to common-used cisplatin-based chemotherapy results in a decreased overall patient survival. The present study is aimed to investigate the role and mechanism by which miR-139/ ATPases7A/B axis modulates the chemoresistance of ovarian cancer to cisplatin-based chemotherapy.

METHODS

The expression of miR-139 in cisplatin-sensitive (n = 23) and cisplatin-resistant (n = 14) ovarian cancer tissues and cell lines (CAOV-3 and SNU119) was determined using real-time PCR assays; its effect on ovarian cancer cell chemoresistance to different concentrations of cisplatin was then assessed by measuring the cell viability using MTT assays. Next, miR-139 binding to the 3'UTR of ATP7A/B was confirmed using luciferase reporter gene assays. Finally, the combined effect of miR-139 and ATP7A/B on the chemoresistance of ovarian cancer cell was assessed.

RESULTS

miR-139 expression was down-regulated in cisplatin-resistant ovarian cancer tissues (**P < 0.01) and reduced by cisplatin treatment in ovarian cell lines (*P < 0.05, **P < 0.01); miR-139 could enhance cisplatin-induced suppression on ovarian cancer cell viability, shown as reduced lC50 values; ATP7A and ATP7B protein levesincreased approximately 2 ~ fold-changein cisplatin-resistant cell lines. MiR-139 directly bound to the 3'UTR of ATP7A/B, respectively; miR-139 inhibition increased lC50 values whereas ATP7A/B knockdown reduced lC50 values of CAOV-3 and SNU119 cell lines under cisplatin treatment; the effect of miR-139 inhibition could be partially attenuated by ATP7A/B knockdown.

CONCLUSIONS

MiR-139/ATP7A/B axis can be a reliable biomarker for ovarian cancer diagnosis, and may affect the chemoresistance of ovarian cancer to cisplatin-based chemotherapy; rescuing miR-139 expression thus to inhibit ATP7A/B might contribute to dealing with the chemoresistance of ovarian cancer.

Targeting Ligand Specificity Linked to Tumor Tissue Topological Heterogeneity via Single-Cell Micro-Pharmacological Modeling

Targeted therapy has held promise to be a successful anticancer treatment due to its specificity towards tumor cells that express the target receptors. However, not all targeting drugs used in the clinic are equally effective in tumor eradication. To examine which biochemical and biophysical properties of targeted agents are pivotal for their effective distribution inside the tumor and their efficient cellular uptake, we combine mathematical micro-pharmacological modeling with in vivo imaging of targeted human xenograft tumors in SCID mice. The mathematical model calibrated to experimental data was used to explore properties of the targeting ligand (diffusion and affinity) and ligand release schemes (rates and concentrations) with a goal to identify the properties of cells and ligands that enable high receptor saturation. By accounting for heterogeneities typical of in vivo tumors, our model was able to identify cell- and tissue-level barriers to efficient drug uptake. This work provides a base for utilizing experimentally measurable properties of a ligand-targeted agent and patient-specific attributes of the tumor tissue to support the development of novel targeted imaging agents and for improvement in their delivery to individual tumor cells.

Micropharmacology: An In Silico Approach for Assessing Drug Efficacy Within a Tumor Tissue

Systemic chemotherapy is one of the main anticancer treatments used for most kinds of clinically diagnosed tumors. However, the efficacy of these drugs can be hampered by the physical attributes of the tumor tissue, such as tortuous vasculature, dense and fibrous extracellular matrix, irregular cellular architecture, tumor metabolic gradients, and non-uniform expression of the cell membrane receptors. This can impede the transport of therapeutic agents to tumor cells in sufficient quantities. In addition, tumor microenvironments undergo dynamic spatio-temporal changes during tumor progression and treatment, which can also obstruct drug efficacy. To examine ways to improve drug delivery on a cell-to-tissue scale (single-cell pharmacology), we developed the microscale pharmacokinetics/pharmacodynamics (microPKPD) modeling framework. Our model is modular and can be adjusted to include only the mathematical equations that are crucial for a biological problem under consideration. This modularity makes the model applicable to a broad range of pharmacological cases. As an illustration, we present two specific applications of the microPKPD methodology that help to identify optimal drug properties. The hypoxia-activated drugs example uses continuous drug concentrations, diffusive-advective transport through the tumor interstitium, and passive transmembrane drug uptake. The targeted therapy example represents drug molecules as discrete particles that move by diffusion and actively bind to cell receptors. The proposed modeling approach takes into account the explicit tumor tissue morphology, its metabolic landscape and/or specific receptor distribution. All these tumor attributes can be assessed from patients' diagnostic biopsies; thus, the proposed methodology can be developed into a tool suitable for personalized medicine, such as neoadjuvant chemotherapy.

Model of Intraperitoneal Targeted α-Particle Therapy Shows That Posttherapy Cold-Antibody Boost Enhances Microtumor Radiation Dose and Treatable Tumor Sizes

Intraperitoneally administered radiolabeled monoclonal antibodies (mAbs) have been tested in several clinical trials, often with promising results, but have never proven curative. Methods: We have previously presented simulations of clinically relevant amounts of intraperitoneal ⁹⁰Y-mAbs for treatment of minimal disease and shown that such treatments are unlikely to eradicate microtumors. Our previous model simulated the kinetics of intraperitoneally infused radiolabeled mAbs in humans and showed the benefit of instead using α-emitters such as ²¹¹At. In the current work, we introduce penetration of mAbs into microtumors with radii of up to 400 μm. Calculations were performed using dynamic simulation software. To determine the radiation dose distribution in nonvascularized microtumors of various sizes after intraperitoneal ²¹¹At-radioimmunotherapy, we used an in-house-developed Monte Carlo program for microdosimetry. Our aim was to find methods that optimize the therapy for as wide a tumor size range as possible. Results: Our results show that high-specific-activity radiolabeled mAbs that are bound to a tumor surface will penetrate slowly compared with the half-lives of ²¹¹At and shorter-lived radionuclides. The inner-core cells of tumors with radii exceeding 100 μm may therefore not be sufficiently irradiated. For lower specific activities, the penetration rate and dose distribution will be more favorable for such tumors, but the dose to smaller microtumors and single cells will be low. Conclusion: Our calculations show that the addition of a boost with unlabeled mAb 1-5 h after therapy results in sufficient absorbed doses both to single cells and throughout microtumors up to approximately 300 μm in radius. This finding should also hold for other high-affinity mAbs and short-lived α-emitters.

Mathematical modeling of intraperitoneal drug delivery: simulation of drug distribution in a single tumor nodule

The intraperitoneal (IP) administration of chemotherapy is an alternative treatment for peritoneal carcinomatosis, allowing for higher intratumor concentrations of the cytotoxic agent compared to intravenous administration. Nevertheless, drug penetration depths are still limited to a few millimeters. It is thus necessary to better understand the limiting factors behind this poor penetration in order to improve IP chemotherapy delivery. By developing a three-dimensional computational fluid dynamics (CFD) model for drug penetration in a tumor nodule, we investigated the impact of a number of key parameters on the drug transport and penetration depth during IP chemotherapy. Overall, smaller tumors showed better penetration than larger ones, which could be attributed to the lower IFP in smaller tumors. Furthermore, the model demonstrated large improvements in penetration depth by subjecting the tumor nodules to vascular normalization therapy, and illustrated the importance of the drug that is used for therapy. Explicitly modeling the necrotic core had a limited effect on the simulated penetration. Similarly, the penetration depth remained virtually constant when the Darcy permeability of the tissue changed. Our findings illustrate that the developed parametrical CFD model is a powerful tool providing more insight in the drug transport and penetration during IP chemotherapy.

A novel individual-cell-based mathematical model based on multicellular tumour spheroids for evaluating doxorubicin-related delivery in avascular regions

BACKGROUND AND PURPOSE

Effective drug delivery in the avascular regions of tumours, which is crucial for the promising antitumour activity of doxorubicin-related therapy, is governed by two inseparable processes: intercellular diffusion and intracellular retention. To accurately evaluate doxorubicin-related delivery in the avascular regions, these two processes should be assessed together. Here we describe a new approach to such an assessment.

EXPERIMENTAL APPROACH

An individual-cell-based mathematical model based on multicellular tumour spheroids was developed that describes the different intercellular diffusion and intracellular retention kinetics of doxorubicin in each cell layer. The different effects of a P-glycoprotein inhibitor (LY335979) and a hypoxia inhibitor (YC-1) were quantitatively evaluated and compared, in vitro (tumour spheroids) and in vivo (HepG2 tumours in mice). This approach was further tested by evaluating in these models, an experimental doxorubicin derivative, INNO 206, which is in Phase II clinical trials.

KEY RESULTS

Inhomogeneous, hypoxia-induced, P-glycoprotein expression compromised active transport of doxorubicin in the central area, that is, far from the vasculature. LY335979 inhibited efflux due to P-glycoprotein but limited levels of doxorubicin outside the inner cells, whereas YC-1 co-administration specifically increased doxorubicin accumulation in the inner cells without affecting the extracellular levels. INNO 206 exhibited a more effective distribution profile than doxorubicin.

CONCLUSIONS AND IMPLICATIONS

The individual-cell-based mathematical model accurately evaluated and predicted doxorubicin-related delivery and regulation in the avascular regions of tumours. The described framework provides a mechanistic basis for the proper development of doxorubicin-related drug co-administration profiles and nanoparticle development and could avoid unnecessary clinical trials.

Modelling drug transport during intraperitoneal chemotherapy

Despite a strong rationale for intraperitoneal (IP) chemotherapy, the actual use of the procedure is limited by the poor penetration depth of the drug into the tissue. Drug penetration into solid tumours is a complex mass transport process that involves multiple parameters not only related to the used cytotoxic agent but also to the tumour tissue properties and even the therapeutic setup. Mathematical modelling can provide unique insights into the different transport barriers that occur during IP chemotherapy as well as offer the possibility to test different protocols or drugs without the need for in vivo experiments. In this work, a distinction is made between three different types of model: the lumped parameter model, the distributed model and the cell-based model. For each model, we discuss which steps of the transport process are included and where assumptions are made. Finally, we focus on the advantages and main limitations of each category and discuss some future perspectives for the modelling of IP chemotherapy.

Mathematical modeling of intraperitoneal drug delivery: simulation of drug distribution in a single tumor nodule

The intraperitoneal (IP) administration of chemotherapy is an alternative treatment for peritoneal carcinomatosis, allowing for higher intratumor concentrations of the cytotoxic agent compared to intravenous administration. Nevertheless, drug penetration depths are still limited to a few millimeters. It is thus necessary to better understand the limiting factors behind this poor penetration in order to improve IP chemotherapy delivery. By developing a three-dimensional computational fluid dynamics (CFD) model for drug penetration in a tumor nodule, we investigated the impact of a number of key parameters on the drug transport and penetration depth during IP chemotherapy. Overall, smaller tumors showed better penetration than larger ones, which could be attributed to the lower IFP in smaller tumors. Furthermore, the model demonstrated large improvements in penetration depth by subjecting the tumor nodules to vascular normalization therapy, and illustrated the importance of the drug that is used for therapy. Explicitly modeling the necrotic core had a limited effect on the simulated penetration. Similarly, the penetration depth remained virtually constant when the Darcy permeability of the tissue changed. Our findings illustrate that the developed parametrical CFD model is a powerful tool providing more insight in the drug transport and penetration during IP chemotherapy.