Using pharmacokinetic and pharmacodynamic modeling and simulation to evaluate importance of schedule in topotecan therapy for pediatric neuroblastoma

Topotecan clearance based on a single sample and a population pharmacokinetic model: Application to a pediatric high-risk neuroblastoma clinical trial

BACKGROUND

Topotecan, an antitumor drug with systemic exposure (SE)-dependent activity against many pediatric tumors has wide interpatient pharmacokinetic variability, making it challenging to attain the desired topotecan SE. The study objectives were to update our topotecan population pharmacokinetic model, to evaluate the feasibility of determining individual topotecan clearance using a single blood sample, and to apply this approach to topotecan data from a neuroblastoma trial to explore exposure-response relationships.

PROCEDURE

Our previous population pharmacokinetic and covariate model was updated using data from 13 clinical pediatric studies. A simulation-based Bayesian analysis was performed to determine if a single blood sample could be sufficient to estimate individual topotecan clearance. Following the Bayesian approach, single pharmacokinetic samples collected from a Children's Oncology Group Phase III clinical trial (ANBL0532; NCT0056767) were analyzed to estimate individual topotecan SE. Associations between topotecan SE and toxicity or early response were then evaluated.

RESULTS

The updated population model included the impact of patient body surface area (BSA), age, and renal function on topotecan clearance. The Bayesian analysis with the updated model and single plasma samples showed that individual topotecan clearance values were estimated with good precision (mean absolute prediction error ≤16.2%) and low bias (mean prediction error ≤7.2%). Using the same approach, topotecan SE was derived in patients from ANBL0532. The exposure-response analysis showed an increased early response after concomitant cyclophosphamide and topotecan up to a topotecan SE of 45 h ng/mL.

CONCLUSIONS

A simple single-sample approach during topotecan therapy could guide dosing for patients, resulting in more patients reaching target attainment.

Mechanistic characterization of oscillatory patterns in unperturbed tumor growth dynamics: The interplay between cancer cells and components of tumor microenvironment

Mathematical modeling of unperturbed and perturbed tumor growth dynamics (TGD) in preclinical experiments provides an opportunity to establish translational frameworks. The most commonly used unperturbed tumor growth models (i.e. linear, exponential, Gompertz and Simeoni) describe a monotonic increase and although they capture the mean trend of the data reasonably well, systematic model misspecifications can be identified. This represents an opportunity to investigate possible underlying mechanisms controlling tumor growth dynamics through a mathematical framework. The overall goal of this work is to develop a data-driven semi-mechanistic model describing non-monotonic tumor growth in untreated mice. For this purpose, longitudinal tumor volume profiles from different tumor types and cell lines were pooled together and analyzed using the population approach. After characterizing the oscillatory patterns (oscillator half-periods between 8-11 days) and confirming that they were systematically observed across the different preclinical experiments available (p<10-9), a tumor growth model was built including the interplay between resources (i.e. oxygen or nutrients), angiogenesis and cancer cells. The new structure, in addition to improving the model diagnostic compared to the previously used tumor growth models (i.e. AIC reduction of 71.48 and absence of autocorrelation in the residuals (p>0.05)), allows the evaluation of the different oncologic treatments in a mechanistic way. Drug effects can potentially, be included in relevant processes taking place during tumor growth. In brief, the new model, in addition to describing non-monotonic tumor growth and the interaction between biological factors of the tumor microenvironment, can be used to explore different drug scenarios in monotherapy or combination during preclinical drug development.

Mathematical Model of Clonal Evolution Proposes a Personalised Multi-Modal Therapy for High-Risk Neuroblastoma

Neuroblastoma is the most common extra-cranial solid tumour in children. Despite multi-modal therapy, over half of the high-risk patients will succumb. One contributing factor is the one-size-fits-all nature of multi-modal therapy. For example, during the first step (induction chemotherapy), the standard regimen (rapid COJEC) administers fixed doses of chemotherapeutic agents in eight two-week cycles. Perhaps because of differences in resistance, this standard regimen results in highly heterogeneous outcomes in different tumours. In this study, we formulated a mathematical model comprising ordinary differential equations. The equations describe the clonal evolution within a neuroblastoma tumour being treated with vincristine and cyclophosphamide, which are used in the rapid COJEC regimen, including genetically conferred and phenotypic drug resistance. The equations also describe the agents’ pharmacokinetics. We devised an optimisation algorithm to find the best chemotherapy schedules for tumours with different pre-treatment clonal compositions. The optimised chemotherapy schedules exploit the cytotoxic difference between the two drugs and intra-tumoural clonal competition to shrink the tumours as much as possible during induction chemotherapy and before surgical removal. They indicate that induction chemotherapy can be improved by finding and using personalised schedules. More broadly, we propose that the overall multi-modal therapy can be enhanced by employing targeted therapies against the mutations and oncogenic pathways enriched and activated by the chemotherapeutic agents. To translate the proposed personalised multi-modal therapy into clinical use, patient-specific model calibration and treatment optimisation are necessary. This entails a decision support system informed by emerging medical technologies such as multi-region sequencing and liquid biopsies. The results and tools presented in this paper could be the foundation of this decision support system.

On tumoural growth and treatment under cellular dedifferentiation

Differentiated cancer cells may regain stem cell characteristics; however, the effects of such a cellular dedifferentiation on tumoural growth and treatment are currently understudied. Thus, we here extend a mathematical model of cancer stem cell (CSC) driven tumour growth to also include dedifferentiation. We show that dedifferentiation increases the likelihood of tumorigenesis and the speed of tumoural growth, both modulated by the proliferative potential of the non-stem cancer cells (NSCCs). We demonstrate that dedifferentiation also may lead to treatment evasion, especially when a treatment solely targets CSCs. Conversely, targeting both CSCs and NSCCs in parallel is shown to be more robust to dedifferentiation. Despite dedifferentiation, perturbing CSC-related parameters continues to exert the largest relative effect on tumoural growth; however, we show the existence of synergies between specific CSC- and NSCC-directed treatments which cause superadditive reductions of tumoural growth. Overall, our study demonstrates various effects of dedifferentiation on growth and treatment of tumoural lesions, and we anticipate our results to be helpful in guiding future molecular and clinical research on limiting tumoural growth in vivo.

Treatment of Retinoblastoma: What Is the Latest and What Is the Future

The management of retinoblastoma, the most common intraocular malignancy in children, has changed drastically over the last decade. Landmark developments in local drug delivery, namely, safer techniques for intravitreal chemotherapy injection and ophthalmic artery chemosurgery, have resulted in eye globe salvages that were not previously attainable using systemic chemotherapy or external beam irradiation. Novel drugs, oncolytic viruses, and immunotherapy are promising approaches in the treatment of intraocular retinoblastoma. Importantly, emerging studies of the pattern of tumor dissemination and local drug delivery may provide the first steps toward new treatments for metastatic disease. Here, we review recent advances in retinoblastoma treatment, especially with regard to local drug delivery, that have enabled successful conservative management of intraocular retinoblastoma. We also review emerging data from preclinical and clinical studies on innovative approaches that promise to lead to further improvement in outcomes, namely, the mechanisms and potential uses of new and repurposed drugs and non-chemotherapy treatments, and discuss future directions for therapeutic development.

Semi-Mechanistic Model for the Antitumor Response of a Combination Cocktail of Immuno-Modulators in Non-Inflamed (Cold) Tumors

Simple Summary

The clinical efficacy of immunotherapies when treating cold tumors is still low, and different treatment combinations are needed when dealing with this challenging scenario. In this work, a middle-out strategy was followed to develop a model describing the antitumor efficacy of different immune-modulator combinations, including an antigen, a toll-like receptor-3 agonist, and an immune checkpoint inhibitor in mice treated with non-inflamed tumor cells. Our results support that clinical response requires antigen-presenting cell activation and also relies on the amount of CD8 T cells and tumor resistance mechanisms present. This mathematical model is a very useful platform to evaluate different immuno-oncology combinations in both preclinical and clinical settings.

Abstract

Immune checkpoint inhibitors, administered as single agents, have demonstrated clinical efficacy. However, when treating cold tumors, different combination strategies are needed. This work aims to develop a semi-mechanistic model describing the antitumor efficacy of immunotherapy combinations in cold tumors. Tumor size of mice treated with TC-1/A9 non-inflamed tumors and the drug effects of an antigen, a toll-like receptor-3 agonist (PIC), and an immune checkpoint inhibitor (anti-programmed cell death 1 antibody) were modeled using Monolix and following a middle-out strategy. Tumor growth was best characterized by an exponential model with an estimated initial tumor size of 19.5 mm³ and a doubling time of 3.6 days. In the treatment groups, contrary to the lack of response observed in monotherapy, combinations including the antigen were able to induce an antitumor response. The final model successfully captured the 23% increase in the probability of cure from bi-therapy to triple-therapy. Moreover, our work supports that CD8⁺ T lymphocytes and resistance mechanisms are strongly related to the clinical outcome. The activation of antigen-presenting cells might be needed to achieve an antitumor response in reduced immunogenic tumors when combined with other immunotherapies. These models can be used as a platform to evaluate different immuno-oncology combinations in preclinical and clinical scenarios.

Tumor growth inhibition modeling of individual lesion dynamics and interorgan variability in HER2-negative breast cancer patients treated with docetaxel

Information on individual lesion dynamics and organ location are often ignored in pharmacometric modeling analyses of tumor response. Typically, the sum of their longest diameters is utilized. Herein, a tumor growth inhibition model was developed for describing the individual lesion time-course data from 183 patients with metastatic HER2-negative breast cancer receiving docetaxel. The interindividual variability (IIV), interlesion variability (ILV), and interorgan variability of parameters describing the lesion time-courses were evaluated. Additionally, a model describing the probability of new lesion appearance and a time-to-event model for overall survival (OS), were developed. Before treatment initiation, the lesions were largest in the soft tissues and smallest in the lungs, and associated with a significant IIV and ILV. The tumor growth rate was 2.6 times higher in the breasts and liver, compared with other metastatic sites. The docetaxel drug effect in the liver, breasts, and soft tissues was greater than or equal to 1.2 times higher compared with other organs. The time-course of the largest lesion, the presence of at least 3 liver lesions, and the time since study enrollment, increased the probability of new lesion appearance. New lesion appearance, along with the time to growth and time-course of the largest lesion at baseline, were identified as the best predictors of OS. This tumor modeling approach, incorporating individual lesion dynamics, provided a more complete understanding of heterogeneity in tumor growth and drug effect in different organs. Thus, there may be potential to tailor treatments based on lesion location, lesion size, and early lesion response to provide better clinical outcomes.

Modelling Cell Invasion: A Review of What JD Murray and the Embryo Can Teach Us

Cell invasion and cell plasticity are critical to human development but are also striking features of cancer metastasis. By distributing a multipotent cell type from a place of birth to distal locations, the vertebrate embryo builds organs. In comparison, metastatic tumor cells often acquire a de-differentiated phenotype and migrate away from a primary site to inhabit new microenvironments, disrupting normal organ function. Countless observations of both embryonic cell migration and tumor metastasis have demonstrated complex cell signaling and interactive behaviors that have long confounded scientist and clinician alike. James D. Murray realized the important role of mathematics in biology and developed a unique strategy to address complex biological questions such as these. His work offers a practical template for constructing clear, logical, direct and verifiable models that help to explain complex cell behaviors and direct new experiments. His pioneering work at the interface of development and cancer made significant contributions to glioblastoma cancer and embryonic pattern formation using often simple models with tremendous predictive potential. Here, we provide a brief overview of advances in cell invasion and cell plasticity using the embryonic neural crest and its ancestral relationship to aggressive cancers that put into current context the timeless aspects of his work.

Modelling of neutrophil dynamics in children receiving busulfan or treosulfan for haematopoietic stem cell transplant conditioning

AIMS

Busulfan and treosulfan are cytotoxic agents used in the conditioning regime prior to paediatric haematopoietic stem cell transplantation (HSCT). These agents cause suppression of myeloid cells leaving patients severely immunocompromised in the early post-HSCT period. The main objectives were: (i) to establish a mechanistic pharmacokinetic-pharmacodynamic (PKPD) model for the treatment and engraftment effects on neutrophil counts comparing busulfan and treosulfan-based conditioning, and (ii) to explore current dosing schedules with respect to time to HSCT.

METHODS

Data on 126 patients, 72 receiving busulfan (7 months-18 years, 5.1-47.0 kg) and 54 treosulfan (4 months-17 years, 3.8-35.8 kg), were collected. In total, 8935 neutrophil count observations were recorded during the study period in addition to drug concentrations to develop a mechanistic PKPD model. Absolute neutrophil count profiles were modelled semimechanistically, accounting for transplant effects and differing set points pre- and post-transplant.

RESULTS

PK were best described by 2-compartment models for both drugs. The Friberg semimechanistic neutropenia model was applied with a linear model for busulfan and a maximum efficacy model for treosulfan describing drug effects at various stages of neutrophil maturation. System parameters were consistent across both drugs. The HSCT was represented by an amount of progenitor cells enhancing the neutrophils' proliferation and maturation compartments. Alemtuzumab was found to enhance the proliferative rate under which the absolute neutrophil count begin to grow after HSCT.

CONCLUSION

A semimechanistic PKPD model linking exposure to either busulfan or treosulfan to the neutrophil reconstitution dynamics was successfully built. Alemtuzumab coadministration enhanced the neutrophil proliferative rate after HSCT. Treosulfan administration was suggested to be delayed with respect to time to HSCT, leaving less time between the end of the administration and stem cell infusion.

A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors

Increasing knowledge of intertumor heterogeneity, intratumor heterogeneity, and cancer evolution has improved the understanding of anticancer treatment resistance. A better characterization of cancer evolution and subsequent use of this knowledge for personalized treatment would increase the chance to overcome cancer treatment resistance. Model‐based approaches may help achieve this goal. In this review, we comprehensively summarized mathematical models of tumor dynamics for solid tumors and of drug resistance evolution. Models displayed by ordinary differential equations, algebraic equations, and partial differential equations for characterizing tumor burden dynamics are introduced and discussed. As for tumor resistance evolution, stochastic and deterministic models are introduced and discussed. The results may facilitate a novel model‐based analysis on anticancer treatment response and the occurrence of resistance, which incorporates both tumor dynamics and resistance evolution. The opportunities of a model‐based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.

Role of vascular normalization in benefit from metronomic chemotherapy

Metronomic dosing of chemotherapy-defined as frequent administration at lower doses-has been shown to be more efficacious than maximum tolerated dose treatment in preclinical studies, and is currently being tested in the clinic. Although multiple mechanisms of benefit from metronomic chemotherapy have been proposed, how these mechanisms are related to one another and which one is dominant for a given tumor-drug combination is not known. To this end, we have developed a mathematical model that incorporates various proposed mechanisms, and report here that improved function of tumor vessels is a key determinant of benefit from metronomic chemotherapy. In our analysis, we used multiple dosage schedules and incorporated interactions among cancer cells, stem-like cancer cells, immune cells, and the tumor vasculature. We found that metronomic chemotherapy induces functional normalization of tumor blood vessels, resulting in improved tumor perfusion. Improved perfusion alleviates hypoxia, which reprograms the immunosuppressive tumor microenvironment toward immunostimulation and improves drug delivery and therapeutic outcomes. Indeed, in our model, improved vessel function enhanced the delivery of oxygen and drugs, increased the number of effector immune cells, and decreased the number of regulatory T cells, which in turn killed a larger number of cancer cells, including cancer stem-like cells. Vessel function was further improved owing to decompression of intratumoral vessels as a result of increased killing of cancer cells, setting up a positive feedback loop. Our model enables evaluation of the relative importance of these mechanisms, and suggests guidelines for the optimal use of metronomic therapy.

Novel phase I study combining G1 phase, S phase, and G2/M phase cell cycle inhibitors in patients with advanced malignancies

PURPOSE

Cancer is a manifestation of aberrant cellular proliferation, and the cell cycle is one of the most successfully drugged targets in oncology. No prior study has been reported that simultaneously targets the 3 principal cell cycle phases populated by proliferating cells--G1, S, and G2/M.

METHODS

Temsirolimus (G1 inhibitor), topotecan (S inhibitor), and bortezomib (G2/M inhibitor) were administered in combination to patients with advanced malignancies using a 3+3 dose escalation schedule to assess the safety and establish the maximum tolerated dose (primary endpoints) of this cell cycle targeting approach. An in silico pharmacodynamic model using established effects of each of these agents on the cell cycle was used to validate the regimen and to guide the dosing regimen.

RESULTS

Sixty-two subjects were enrolled. The most common adverse events and dose-limiting toxicities were cytopenias, consistent with the cell cycle targeting approach employed. All cytopenias resolved to baseline values upon holding study drug administration. The maximum tolerated dose was temsirolimus 15 mg/kg IV D1, 8, 15; topotecan 2.8 mg/m(2) IV D1, 8; and bortezomib 0.6 mg/m2 IV D1, 4, 8, 11 [DOSAGE ERROR CORRECTED] of a 21-day cycle. In silico modeling suggests the regimen induces cell population shifts from G2/M and S phases to G1 phase and the quiescent G0 phase. Eighteen percent of subjects (11/62) achieved partial response (n = 2, serous ovarian and papillary thyroid) or stable disease for > 6 months (n = 9).

CONCLUSION

Combining drugs with inhibitory activity of G1 phase, S phase, and G2/M phase is safe and warrants further evaluation.

Schedule-Dependent Antiangiogenic and Cytotoxic Effects of Chemotherapy on Vascular Endothelial and Retinoblastoma Cells

Current treatment of retinoblastoma involves using the maximum dose of chemotherapy that induces tumor control and is tolerated by patients. The impact of dose and schedule on the cytotoxicity of chemotherapy has not been studied. Our aim was to gain insight into the cytotoxic and antiangiogenic effect of the treatment scheme of chemotherapy used in retinoblastoma by means of different in vitro models and to evaluate potential effects on multi-drug resistance proteins. Two commercial and two patient-derived retinoblastoma cell types and two human vascular endothelial cell types were exposed to increasing concentrations of melphalan or topotecan in a conventional (single exposure) or metronomic (7-day continuous exposure) treatment scheme. The concentration of chemotherapy causing a 50% decrease in cell proliferation (IC50) was determined by MTT and induction of apoptosis was evaluated by flow cytometry. Expression of ABCB1, ABCG2 and ABCC1 after conventional or metronomic treatments was assessed by RT-qPCR. We also evaluated the in vivo response to conventional (0.6 mg/kg once a week for 2 weeks) and metronomic (5 days a week for 2 weeks) topotecan in a retinoblastoma xenograft model. Melphalan and topotecan were cytotoxic to both retinoblastoma and endothelial cells after conventional and metronomic treatments. A significant decrease in the IC50 (median, 13-fold; range: 3–23) was observed following metronomic chemotherapy treatment in retinoblastoma and endothelial cell types compared to conventional treatment (p<0.05). Metronomic topotecan or melphalan significantly inhibited in vitro tube formation in HUVEC and EPC compared to vehicle-treated cells (p<0.05). Both treatment schemes induced apoptosis and/or necrosis in all cell models. No significant difference was observed in the expression of ABCB1, ABCC1 or ABCG2 when comparing cells treated with melphalan or topotecan between treatment schedules at the IC50 or with control cells (p>0.05). In mice, continuous topotecan lead to significantly lower tumor volumes compared to conventional treatment after 14 days of treatment (p<0.05). Continuous exposure to melphalan or topotecan increased the chemosensitivity of retinoblastoma and endothelial cells to both chemotherapy agents with lower IC50 values compared to short-term treatment. These findings were validated in an in vivo model. None of the dosing modalities induced multidrug resistance mechanisms while apoptosis was the mechanism of cell death after both treatment schedules. Metronomic chemotherapy may be a valid option for retinoblastoma treatment allowing reductions of the daily dose.

Nifurtimox reduces N-Myc expression and aerobic glycolysis in neuroblastoma

Neuroblastoma is one of the most common solid tumors in childhood and usually accompanied with poor prognosis and rapid tumor progression when diagnosed with amplification of the proto-oncogene N-Myc. The amplification of N-Myc has major influence on the maintenance of aerobic glycolysis, also known as the Warburg effect. This specific switch in the conversion of pyruvate to lactate instead of the conversion of pyruvate to acetyl-coenzyme A even in the presence of oxygen has important benefits for the tumor, e.g. increased production of enzymes and enzyme substrates that are involved in tumor progression, angiogenesis and inhibition of apoptosis. The antiprotozoal drug nifurtimox, which is generally used for the treatment of infections with the parasitic protozoan Trypanosoma cruzi, has been reported to have cytotoxic properties in the therapy of neuroblastoma. However, its action of mechanism has not been described in detail yet. The presented in vitro study on the neuroblastoma cell lines LA-N-1, IMR-32, LS and SK-N-SH shows an increased production of oxidative stress, a reduced lactate dehydrogenase enzyme activity and reduced lactate production after nifurtimox treatment. Furthermore, nifurtimox leads to reduced mRNA and protein levels of the proto-oncogene protein N-Myc. Thus, the current work gives new insights into the effect of nifurtimox on tumor metabolism revealing a shifted glucose metabolism from production of lactate to oxidative phosphorylation and a reduced expression of the major molecular prognostic factor in neuroblastoma N-Myc, presenting nifurtimox as a possible adjuvant therapeutic agent against (high risk) neuroblastoma.

Semimechanistic cell-cycle type-based pharmacokinetic/pharmacodynamic model of chemotherapy-induced neutropenic effects of diflomotecan under different dosing schedules

The current work integrates cell-cycle dynamics occurring in the bone marrow compartment as a key element in the structure of a semimechanistic pharmacokinetic/pharmacodynamic model for neutropenic effects, aiming to describe, with the same set of system- and drug-related parameters, longitudinal data of neutropenia gathered after the administration of the anticancer drug diflomotecan (9,10-difluoro-homocamptothecin) under different dosing schedules to patients (n = 111) with advanced solid tumors. To achieve such an objective, the general framework of the neutropenia models was expanded, including one additional physiologic process resembling cell cycle dynamics. The main assumptions of the proposed model are as follows: within the stem cell compartment, proliferative and quiescent cells coexist, and only cells in the proliferative condition are sensitive to drug effects and capable of following the maturation chain. Cell cycle dynamics were characterized by two new parameters, FProl (the fraction of proliferative [Prol] cells that enters into the maturation chain) and kcycle (first-order rate constant governing cell cycle dynamics within the stem cell compartment). Both model parameters were identifiable as indicated by the results from a bootstrap analysis, and their estimates were supported by date from the literature. The estimates of FProl and kcycle were 0.58 and 1.94 day(-1), respectively. The new model could properly describe the neutropenic effects of diflomotecan after very different dosing scenarios, and can be used to explore the potential impact of dosing schedule dependencies on neutropenia prediction.

Data-driven modeling of pharmacological systems using endpoint information fusion

This study investigated the feasibility of deriving data-driven model of a class of pharmacological systems using the information fusion of endpoint responses. For a class of pharmacological systems subsuming conventional steady-state dose-response models, compartmental pharmacokinetic-pharmacodynamic models and indirect response models, a relation between multiple endpoint responses was formalized and analyzed to elucidate if this class of systems is identifiable, i.e., if the data-driven model of this class of systems can be derived from the endpoint responses alone. It was shown that this class of systems is fully identifiable in case all the responses involve effect compartments. However, it was also observed that persistently exciting dose profiles may be required in accurately deriving reliable data-driven model with low variance. The findings from the identifiability analysis were demonstrated using benchmark pharmacological system examples.

A mechanistic tumor penetration model to guide antibody drug conjugate design

Antibody drug conjugates (ADCs) represent novel anti-cancer modalities engineered to specifically target and kill tumor cells expressing corresponding antigens. Due to their large size and their complex kinetics, these therapeutic agents often face heterogeneous distributions in tumors, leading to large untargeted regions that escape therapy. We present a modeling framework which includes the systemic distribution, vascular permeability, interstitial transport, as well as binding and payload release kinetics of ADC-therapeutic agents in mouse xenografts. We focused, in particular, on receptor dynamics such as endocytic trafficking mechanisms within cancer cells, to simulate their impact on tumor mass shrinkage upon ADC administration. Our model identified undesirable tumor properties that can impair ADC tissue homogeneity, further compromising ADC success, and explored ADC design optimization scenarios to counteract upon such unfavorable intrinsic tumor tissue attributes. We further demonstrated the profound impact of cytotoxic payload release mechanisms and the role of bystander killing effects on tumor shrinkage. This model platform affords a customizable simulation environment which can aid with experimental data interpretation and the design of ADC therapeutic treatments.

Metronomics chemotherapy: time for computational decision support

Over the last decade, metronomic chemotherapy has been increasingly considered as an attractive strategy for treating cancer in a variety of settings. Beside pharmaco-economic considerations making metronomics a unique opportunity in low- or middle-income countries, revisiting dosing schedules using continuous low doses of cytotoxics should theoretically permit to reduce the incidence of treatment-related toxicities, while offering unexpected novel mechanisms of actions such as antiangiogenic or immuno-stimulating properties. Consequently, a number of clinical trials sought to evaluate to what extent switching to metronomic schedules could actually impact indeed on the efficacy/toxicity balance of a variety of anticancer drugs in both adults and pediatric oncology. Vinorelbine is a vinca-alcaloïd that remains the backbone of several regimens to treat patients with metastatic breast cancer or non-small cell lung cancer. Additionally, vinorelbine is widely used to treat a variety of solid tumors in children such as rhabdomyosarcomas and acute leukemia. The recent approval of an oral formulation of vinorelbine has open the way to developing alternative metronomic schedules with this drug. Consequently, a number of clinical trials investigating on metronomic vinorelbine have been performed over the last few years, with seemingly inconsistent results to date. Of note, all the studies published thus far were based upon empirical determination of the metronomic schedule, both in terms of doses, drug-free intervals and repartition of the administrations throughout time. Because the very concept of «low, repeated doses with little or no drug-free interval» covers numerous possible combinations, determining the optimal protocol using traditional under-powered empirical design looks like an unreachable goal. In this context, mathematical modeling offers invaluable in silico tools to help determining the optimal metronomic schedule among a variety of possibilities. This review covers the latest clinical trials investigating on metronomic vinorelbine and proposes alternative strategies for developing computational decision support to make metronomics a scientific-grounded strategy, rather than an empirical practice at the bedside. In particular, mathematical simulations using an original pharmacokinetics/pharmacodynamics constraint models provide clues for exploring new paths in the way metronomic vinorelbine could be scheduled in patients with lung cancer.

Metronomics: towards personalized chemotherapy?

Since its inception in 2000, metronomic chemotherapy has undergone major advances as an antiangiogenic therapy. The discovery of the pro-immune properties of chemotherapy and its direct effects on cancer cells has established the intrinsic multitargeted nature of this therapeutic approach. The past 10 years have seen a marked rise in clinical trials of metronomic chemotherapy, and it is increasingly combined in the clinic with conventional treatments, such as maximum-tolerated dose chemotherapy and radiotherapy, as well as with novel therapeutic strategies, such as drug repositioning, targeted agents and immunotherapy. We review the latest advances in understanding the complex mechanisms of action of metronomic chemotherapy, and the recently identified factors associated with disease resistance. We comprehensively discuss the latest clinical data obtained from studies performed in both adult and paediatric populations, and highlight ongoing clinical trials. In this Review, we foresee the future developments of metronomic chemotherapy and specifically its potential role in the era of personalized medicine.

Optimizing drug development of anti-cancer drugs in children using modelling and simulation

Modelling and simulation (M&S)-based approaches have been proposed to support paediatric drug development in order to design and analyze clinical studies efficiently. Development of anti-cancer drugs in the paediatric population is particularly challenging due to ethical and practical constraints. We aimed to review the application of M&S in the development of anti-cancer drugs in the paediatric population, and to identify where M&S-based approaches could provide additional support in paediatric drug development of anti-cancer drugs. A structured literature search on PubMed was performed. The majority of identified M&S-based studies aimed to use population PK modelling approaches to identify determinants of inter-individual variability, in order to optimize dosing regimens and to develop therapeutic drug monitoring strategies. Prospective applications of M&S approaches for PK-bridging studies have scarcely been reported for paediatric oncology. Based on recent developments of M&S in drug development there are several opportunities where M&S could support more informative bridging between children and adults, and increase efficiency of the design and analysis of paediatric clinical trials, which should ultimately lead to further optimization of drug treatment strategies in this population.

Formalizing an integrative, multidisciplinary cancer therapy discovery workflow

Although many clinicians and researchers work to understand cancer, there has been limited success to effectively combine forces and collaborate over time, distance, data, and budget constraints. Here we present a workflow template for multidisciplinary cancer therapy that was developed during the 2nd Annual Workshop on Cancer Systems Biology sponsored by Tufts University, Boston, Massachusetts, in July 2012. The template was applied to the development of a metronomic therapy backbone for neuroblastoma. Three primary groups were identified: clinicians, biologists, and quantitative scientists (mathematicians, computer scientists, and engineers). The workflow described their integrative interactions; parallel or sequential processes; data sources and computational tools at different stages as well as the iterative nature of therapeutic development from clinical observations to in vitro, in vivo, and clinical trials. We found that theoreticians in dialog with experimentalists could develop calibrated and parameterized predictive models that inform and formalize sets of testable hypotheses, thus speeding up discovery and validation while reducing laboratory resources and costs. The developed template outlines an interdisciplinary collaboration workflow designed to systematically investigate the mechanistic underpinnings of a new therapy and validate that therapy to advance development and clinical acceptance.

Pilot study assessing a seven-day continuous intrathecal topotecan infusion for recurrent or progressive leptomeningeal metastatic cancer

Objective

To determine the feasibility and toxicity profile of topotecan administered as a seven-day continuous intrathecal infusion for patients with leptomeningeal metastasis secondary to recurrent or progressive central nervous system cancer.

Study design

Two patients with central nervous system leptomeningeal metastasis were treated with a seven-day continuous infusion of topotecan (0.2 mg/day) administered via continuous intrathecal/intraventricular infusion at a rate of 0.6 mL/h, totaling 1.4 mg/course. CSF and plasma concentrations of topotecan closed lactone (the active metabolite) were quantified at various points during topotecan infusion. Patients were monitored for neurologic and systemic toxicities according to NCI common toxicity criteria.

Results

Both patients tolerated the seven-day continuous topotecan without any significant adverse events. One patient received a second course 21 days after treatment initiation. CSF concentration of topotecan closed lactone ranged from 3.73 to 312 ng/mL (median = 131 ng/mL) and plasma topotecan closed lactone ranged from 0.44 to 1.78 ng/mL (median = 0.92 ng/mL). The median CSF topotecan concentration was greater than the median serum topotecan concentration by a 44-fold magnitude when samples were obtained at the same time point. None of the patients experienced any grade 3 or higher hematological toxicities or signs of arachnoiditis.

Conclusion

A seven-day continuous intrathecal infusion of topotecan is well tolerated and has the potential of maximizing central nervous system drug exposure.

Application of hematological toxicity modeling in clinical development of abexinostat (S-78454, PCI-24781), a new histone deacetylase inhibitor

PURPOSE

A population pharmacokinetic/pharmacodynamic (PK/PD) model was developed to describe the thrombocytopenia (dose-limiting toxicity) of abexinostat, a new histone deacetylase inhibitor. An optimal administration schedule of the drug was determined using a simulation-based approach.

METHODS

Early PK and PK/PD data were analysed using a sequential population modeling approach (NONMEM 7), allowing for the description of a PK profile and platelet-count decrease after abexinostat administration with various administration schedules. Simulations of platelet count with several administration schedules over 3-week treatment cycles (ASC) and over a day (ASD) were computed to define the optimal schedule that limits the depth of thrombocytopenia.

RESULTS

An intermediate PK/PD model accurately described the data. The administration of abexinostat during the first 4 days of each week in a 3-week cycle resulted in fewer adverse events (with no influence of ASD on platelet count profiles), and corresponded to the optimal treatment schedule. This administration schedule was clinically evaluated in a phase I clinical trial and allowed for the definition of a new maximum tolerated dose (MTD), leading to a nearly 30% higher dose-intensity than that of another previously tested schedule. Lastly, a final model was built using all of the available data.

CONCLUSIONS

The final model, characterizing the dose-effect and the dose-toxicity relationships, provides a useful modeling tool for clinical drug development.

Comparison of three a-priori models in the prediction of serum lithium concentration

Context:

Mathematical models are valuable for optimizing drug dose and dosing regimens.

Aims:

To compare the precision and bias of three a-priori methods in the prediction of serum level of lithium in patients with bipolar disorder, and to determine their sensitivity and specificity in detecting serum lithium levels outside the therapeutic range.

Settings and Design:

Hospital-based, retrospective study.

Materials and Methods:

In a retrospective study of 31 in-patients, the serum level of lithium was calculated using three different a-priori methods. Mean Prediction Error was used as a measure of bias while Mean Absolute Error and Root Mean Squared Error were used as a measure of precision. The sensitivity and specificity of the methods was calculated.

Results:

All three models underestimated serum lithium level. Precision was best with the model described by Pepin et al., while bias of prediction was the least with the method of Abou Auda et al. The formula by Pepin et al. was able to predict serum lithium level with a mean error of 36.57%. The sensitivity and specificity of the models in identifying serum lithium levels outside the therapeutic range was 80% and 76.19% for Pepin et al., 90% and 74.19% for Zetin et al., and 90% and 66.67% for Abou-Auda et al., respectively.

Conclusion:

The study demonstrates the difference in precision and bias of three a-priori methods, with no one method being superior to the other in the prediction of serum concentration.

A phase I/II study of CY and topotecan in patients with high-risk malignancies undergoing autologous hematopoietic cell transplantation: the St Jude long-term follow-up

Fifty-eight consecutive children with high-risk malignancies were treated with CY, and targeted topotecan followed by autologous hematopoietic cell transplantation (AHCT) in a phase I/II Institutional Review Board-approved study. Twelve participants enrolled in phase I; 5 received dose level 1 of topotecan 3 mg/m(2) per day, with subsequent doses targeted to total systemic exposure of 100±20 ng h/mL and CY 750 mg/m(2) per day. Seven participants received dose level 2. CY dose escalation to 1 g/m(2) per day was considered excessively toxic; one died from irreversible veno-occlusive disease and two experienced reversible hepatotoxicity. These adverse events halted further dose escalation. A total of 46 participants were enrolled in phase II; results are on the 51 participants who received therapy at dose level 1, the maximum tolerated dose. Diagnoses included neuroblastoma (26), sarcoma (9), lymphoma (8), brain tumors (5), Wilms (2) and retinoblastoma (1). Twenty participants (39.3%) were in CR1 at enrollment; median age was 5.1 years. Most common non-hematological grade III-IV toxicity was gastrointestinal (n=37). Neutrophil and platelet engraftment occurred at a median of 15 and 24 days, respectively. Twenty-six (51%) participants remain alive at a median of 6.4 years after AHCT. CY 3.75 g/m(2), and targeted topotecan followed by AHCT are feasible and produce acceptable toxicity in children with high-risk malignancies.

Phase I Study of Topotecan, Ifosfamide, and Etoposide (TIME) with autologous stem cell transplant in refractory cancer: pharmacokinetic and pharmacodynamic correlates

PURPOSE

To determine the maximum tolerated dose (MTD) of topotecan in combination with ifosfamide, mesna, and etoposide (TIME), followed by autologous hematopoietic cell transplant (HCT), in patients with chemotherapy-refractory malignancies.

EXPERIMENTAL DESIGN

Patients were treated with (in mg/m(2)/d) ifosfamide 3,333, mesna 3,333, and topotecan 3.3 to 28.3 during days -8 through -6 and etoposide 500 (days -5 through -3) followed by HCT on day 0. Once MTD was defined, we expanded this dosing cohort to include patients with high-risk lymphoma due to activity seen during dose escalation. Topotecan pharmacokinetic analyses were carried out, and topoisomerase I levels and activity were measured.

RESULTS

The topotecan MTD in this regimen was 64 mg/m(2) (21.3 mg/m(2)/d). Mucositis was dose limiting and correlated with topotecan dose level and area under the curve (AUC). Dose level was also correlated with length of hospitalization, number of days of parenteral nutrition, and neutrophil and platelet engraftment. Topotecan AUC was significantly correlated with time to platelet recovery. The baseline peripheral blood mononuclear cell topoisomerase I level was found to be a significant positive predictor for overall and progression-free survival. Topotecan AUC was positively correlated with dose level, with a trend toward decreasing clearance with increasing dose.

CONCLUSION

Topotecan can be a useful drug in the high-dose setting given its activity in some malignancies when given in standard dose. Pharmacokinetic monitoring may be a valuable tool for optimizing the use of topotecan and to avoid toxicity seen with high-systemic exposures. Baseline topoisomerase I levels may have an important role in predicting topotecan efficacy.

Pilot induction regimen incorporating pharmacokinetically guided topotecan for treatment of newly diagnosed high-risk neuroblastoma: a Children's Oncology Group study

PURPOSE

To assess the feasibility of adding dose-intensive topotecan and cyclophosphamide to induction therapy for newly diagnosed high-risk neuroblastoma (HRNB).

PATIENTS AND METHODS

Enrolled patients received two cycles of topotecan (approximately 1.2 mg/m(2)/d) and cyclophosphamide (400 mg/m(2)/d) for 5 days followed by four cycles of multiagent chemotherapy (Memorial Sloan-Kettering Cancer Center [MSKCC] regimen). Pharmacokinetically guided topotecan dosing (target systemic exposure with area under the curve of 50 to 70 ng/mL/hr) was performed. Peripheral-blood stem cell (PBSC) harvest and surgical resection of residual primary tumor occurred after cycles 2 and 5, respectively. Patients achieving at least a partial response received myeloablative chemotherapy with PBSC rescue and radiation to the presurgical primary tumor volume. Oral 13-cis-retinoic acid maintenance therapy was administered twice daily for 14 days in six 28-day cycles.

RESULTS

Thirty-one patients were enrolled onto the study. No deaths related to toxicity or dose-limiting toxicities occurred during induction. Mucositis rarely occurred after topotecan cycles (9.7%) in contrast to 30% after MSKCC cycles. Thirty patients underwent PBSC collection with median 31.1 × 10(6) CD34+ cells/kg (range, 1.8 to 541.8 × 10(6) CD34+ cells/kg), all negative for tumor contamination by immunocytochemical analysis. Targeted topotecan systemic exposure was achieved in 26 (84%) of 31 patients. At the end of induction, 26 patients (84%) had tumor response and one patient had progressive disease. In the overall cohort, 3-year event-free and overall survival were 37.8% ± 9.4% and 57.1% ± 9.4%, respectively.

CONCLUSION

This pilot induction regimen was well tolerated with expected and reversible toxicities. These data support investigation of efficacy in a phase III clinical trial for newly diagnosed HRNB.

An integrated disease/pharmacokinetic/pharmacodynamic model suggests improved interleukin-21 regimens validated prospectively for mouse solid cancers

Interleukin (IL)-21 is an attractive antitumor agent with potent immunomodulatory functions. Yet thus far, the cytokine has yielded only partial responses in solid cancer patients, and conditions for beneficial IL-21 immunotherapy remain elusive. The current work aims to identify clinically-relevant IL-21 regimens with enhanced efficacy, based on mathematical modeling of long-term antitumor responses. For this purpose, pharmacokinetic (PK) and pharmacodynamic (PD) data were acquired from a preclinical study applying systemic IL-21 therapy in murine solid cancers. We developed an integrated disease/PK/PD model for the IL-21 anticancer response, and calibrated it using selected “training” data. The accuracy of the model was verified retrospectively under diverse IL-21 treatment settings, by comparing its predictions to independent “validation” data in melanoma and renal cell carcinoma-challenged mice (R²>0.90). Simulations of the verified model surfaced important therapeutic insights: (1) Fractionating the standard daily regimen (50 µg/dose) into a twice daily schedule (25 µg/dose) is advantageous, yielding a significantly lower tumor mass (45% decrease); (2) A low-dose (12 µg/day) regimen exerts a response similar to that obtained under the 50 µg/day treatment, suggestive of an equally efficacious dose with potentially reduced toxicity. Subsequent experiments in melanoma-bearing mice corroborated both of these predictions with high precision (R²>0.89), thus validating the model also prospectively in vivo. Thus, the confirmed PK/PD model rationalizes IL-21 therapy, and pinpoints improved clinically-feasible treatment schedules. Our analysis demonstrates the value of employing mathematical modeling and in silico-guided design of solid tumor immunotherapy in the clinic.

Among the many potential drugs explored within the scope of cancer immunotherapy are selected cytokines which possess promising immune-boosting properties. Yet, the natural involvement of these proteins in multiple, often contradicting biological processes can complicate their use in the clinic. The cytokine interleukin (IL)-21 is no exception: while its strength as an anticancer agent has been established in several animal studies, response rates in melanoma and renal cell carcinoma patients remain low. To help guide the design of effective IL-21 therapy, we have developed a mathematical model that bridges between the complex biology of IL-21 and its optimal clinical use. Our model integrates data from preclinical studies under diverse IL-21 treatment settings, and was validated by extensive experiments in tumor-bearing mice. Model simulations predicted that beneficial, clinically practical IL-21 therapy should be composed of low-dose schedules, and/or schedules in which several partial doses are administered rather than a single complete dose. These findings were subsequently confirmed in mice with melanoma. Thus, future testing of these strategies in solid cancer patients can be a promising starting point for improving IL-21 therapy. Our model can thus provide a computational platform for rationalizing IL-21 regimens and streamlining its clinical development.

Short topotecan-based induction regimen in newly diagnosed high-risk neuroblastoma

PURPOSE

Topotecan is an active drug in relapsed neuroblastoma. We investigated the efficacy and toxicity of a topotecan-based induction regimen in newly diagnosed neuroblastoma.

METHODS

Patients older than 1 year with either metastatic or localised stage 2-3 MYCN-amplified neuroblastoma received 2 courses of high-dose topotecan (HD-TPT) 6mg/m(2) and high-dose cyclophosphamide (HD-CPM) 140 mg/kg, followed by 2 courses of ifosfamide, carboplatin and etoposide (ICE) every 28 days. After surgery on primary tumour, a fifth course with vincristine, doxorubicin and CPM was given, followed by high-dose chemotherapy with stem cell support. Response was assessed in accordance with the International Neuroblastoma Response Criteria.

RESULTS

Of 35 consecutive patients, 33 had metastatic disease. The median length of induction phase was 133 days (range 91-207) and time to high-dose chemotherapy was 208 days (range 156-285). The median tumour volume reduction was 55% after two HD-TPT/HD-CPM courses and 80% after four courses. Radical surgery was performed in 16/27 patients after chemotherapy. After the fifth course, 29/34 patients (85%) had achieved a partial remission (12) or a CR/very good partial remission (17). CR of metastases was achieved in 13/32 (41%) and bone marrow was in complete remission in 16/24 patients (67%). Grade 4 neutropenia and/or thrombocytopenia occurred in 100% of HD-TPT/HD-CPM and in 95% of ICE courses, while non-haematological toxicities were manageable.

CONCLUSIONS

These data indicate that our induction regimen is feasible and well tolerated. A major response rate of 85% with 41% complete metastatic response confirms this regimen as effective induction in high-risk neuroblastoma.

Systems biology and modeling in neuroblastoma: practicalities and perspectives

Neuroblastoma (NB) is a common pediatric malignancy characterized by clinical and biological heterogeneity. A host of prognostic markers are available, contributing to accurate risk stratification and appropriate treatment allocation. Unfortunately, outcome is still poor for many patients, indicating the need for a new approach with enhanced utilization of the available biological data. Systems biology is a holistic approach in which all components of a biological system carry equal importance. Systems biology uses mathematical modeling and simulation to investigate dynamic interactions between system components, as a means of explaining overall system behavior. Systems biology can benefit the biomedical sciences by providing a more complete understanding of human disease, enhancing the development of targeted therapeutics. Systems biology is largely contiguous with current approaches in NB, which already employ an integrative and pseudo-holistic approach to disease management. Systems modeling of NB offers an optimal method for continuing progression in this field, and conferring additional benefit to current risk stratification and management. Likewise, NB provides an opportunity for systems biology to prove its utility in the context of human disease, since the biology of NB is comprehensively characterized and, therefore, suited to modeling. The purpose of this review is to outline the benefits, challenges and fundamental workings of systems modeling in human disease, using a specific example of bottom-up modeling in NB. The intention is to demonstrate practical requirements to begin bridging the gap between biological research and applied mathematical approaches for the mutual gain of both fields, and with additional benefits for clinical management.

A semi-physiological-based pharmacokinetic/pharmacodynamic model to describe the effects of topotecan on b-lymphocyte lineage cells

PURPOSE

To develop a semi-physiological-based model describing simultaneously the time course of immature and mature B-lymphocytes after topotecan (TPT) administration to tumor-bearing rats.

METHODS

Twenty-four tumor-bearing BDIX male rats received a single 6 mg/kg intra-peritoneal dose of TPT or saline. Mature and immature B-cell levels were measured every two days during three weeks and showed a very different temporal pattern. Both B-cell populations declined rapidly, reaching the nadir at 3-4 days after TPT administration; however, mature cells returned to baseline at day 8, while immature B-cells stayed at nadir until day 9 instead. Data were modeled using the population approach with NONMEM VI.

RESULTS

The model developed maintains the proliferation, maturation and degradation elements of previous published models for myelosuppresion. In order to describe the rapid recovery of mature cells, it includes a peripheral compartment providing a constant supply of mature cells to the bloodstream.

CONCLUSIONS

The major contribution of the model is its new structure and the dynamical consequences, demonstrating an independent behavior between mature and immature B-cells during recovery. The final model could represent a good basis for the optimization of cytotoxic drugs oriented to attain a maximum antitumor efficacy while minimizing hematological toxicity.

Chemotherapy of vascularised tumours: role of vessel density and the effect of vascular "pruning"

In this work we propose to model chemotherapy taking into account the mutual interaction between tumour growth and the development of tumour vasculature. By adopting a simple model for this interaction, and assuming that the efficacy of a drug can be modulated by the vessel density, we study the constant continuous therapy, the periodic bolus-based therapy, and combined therapy in which a chemotherapic drug is associated with an anti-angiogenic agent. The model allows to represent the vessel-disrupting activity of some standard chemotherapic drugs, and shows, in the case of constant continuous drug administration, the possibility of multiple stable equilibria. The multistability suggests an explanation for some sudden losses of control observed during therapy, and for the beneficial effect of vascular "pruning" exerted by anti-angiogenic agents in combined therapy. Moreover, in case of periodic therapies in which the drug amount administered per unit time is constant ("metronomic" delivery), the model predicts a response, as a function of the bolus frequency, significantly influenced by the extent of the anti-angiogenic activity of the chemotherapic drug and by the dependence of the drug efficacy on the vessel density.

Mathematical modeling as a tool for planning anticancer therapy

We review a large volume of literature concerning mathematical models of cancer therapy, oriented towards optimization of treatment protocols. The review, although partly idiosyncratic, covers such major areas of therapy optimization as phase-specific chemotherapy, antiangiogenic therapy and therapy under drug resistance. We start from early cell cycle progression models, very simple but admitting explicit mathematical solutions, based on methods of control theory. We continue with more complex models involving evolution of drug resistance and pharmacokinetic and pharmacodynamic effects. Then, we consider two more recent areas: angiogenesis of tumors and molecular signaling within and among cells. We discuss biological background and mathematical techniques of this field, which has a large although only partly realized potential for contributing to cancer treatment.

Semi-mechanistic model for neutropenia after high dose of chemotherapy in breast cancer patients

PURPOSE

To describe the absolute neutrophil counts (ANC) profile in breast cancer patients receiving high-dose of chemotherapy and peripheral blood stem-cells (PBSC) transplantation.

METHODS

Data from 41 subjects receiving cyclophosphamide, thiotepa and carboplatin were used to develop the ANC model consisting of a drug-sensitive progenitor cell compartment, linked to the peripheral blood compartment, through three transition compartments. PBSC were incorporated into the first transit compartment following a zero-order process, k(in), and the rebound effect was explained by a feedback mechanism. A 'kinetics of drug action' model was used to quantify the HDC effect on the progenitor cells according to a linear function, with a slope (alpha).

RESULTS

The typical of the ANC at baseline (Circ(0)), mean transit time (MTT), feedback parameter (gamma), k(in) and alpha were estimated to be 5,610 x 10(6)/L, 3.25 days, 0.145, 0.954 cell/kg/day and 2.50 h/U, respectively. rHuG-CSF shortens the MTT by 92% and increases the mitotic activity by 120%. Bootstrap analysis, visual predictive check and numerical predictive checks evidenced accurate prediction of the ANC nadir, time to ANC nadir and time to grade 4 neutropenia recovery.

CONCLUSION

The time course of neutropenia following high-dose of chemotherapy and PBSC transplantation was accurately predicted. Higher amount of CD34+ cells in the PBSC transplantation and earlier administration rHuG-CSF were associated with faster haematological recovery.

Cell killing and resistance in pre-operative breast cancer chemotherapy

Background

Despite the recent development of technologies giving detailed images of tumours in vivo, direct or indirect ways to measure how many cells are actually killed by a treatment or are resistant to it are still beyond our reach.

Methods

We designed a simple model of tumour progression during treatment, based on descriptions of the key phenomena of proliferation, quiescence, cell killing and resistance, and giving as output the macroscopically measurable tumour volume and growth fraction. The model was applied to a database of the time course of volumes of breast cancer in patients undergoing pre-operative chemotherapy, for which the initial estimate of proliferating cells by the measure of the percentage of Ki67-positive cells was available.

Results

The analysis recognises different patterns of response to treatment. In one subgroup of patients the fitting implied drug resistance. In another subgroup there was a shift to higher sensitivity during the therapy. In the subgroup of patients where killing of cycling cells had the highest score, the drugs showed variable efficacy against quiescent cells.

Conclusion

The approach was feasible, providing items of information not otherwise available. Additional data, particularly sequential Ki67 measures, could be added to the system, potentially reducing uncertainty in estimates of parameter values.