Metronomics chemotherapy: time for computational decision support

Promotion of tumor angiogenesis and growth induced by low-dose antineoplastic agents via bone-marrow-derived cells in tumor tissues

Background

More research is needed to solidify the basis for reasonable metronomic chemotherapy regimens due to the inconsistent clinical outcomes from studies on metronomic chemotherapy with antineoplastic agents, along with signs of a nonlinear dose-response relationship at low doses. The present study therefore explored the dose-response relationships of representative antineoplastic agents in low dose ranges and their underlying mechanisms.

Methods

Cyclophosphamide (CPA) and 5-fluorouracil (5-Fu) were employed to observe the effects of the frequent administration of low-dose antineoplastic agents on tumor growth, tumor angiogenesis, and bone-marrow-derived cell (BMDC) mobilization in mouse models. The effects of antineoplastic agents on tumor and endothelial cell functions with or without BMDCs were analyzed in vitro.

Results

Tumor growth and metastasis were significantly promoted after the administration of CPA or 5-Fu at certain low dose ranges, and were accompanied by enhanced tumor angiogenesis and proangiogenic factor expression in tumor tissues, increased proangiogenic BMDC release in the circulating blood, and augmented proangiogenic BMDC retention in tumor tissues. Low concentrations of CPA or 5-Fu were found to significantly promote tumor cell migration and invasion, and enhance BMDC adhesion to endothelial cells in vitro.

Conclusion

These results suggest that there are risks in empirical metronomic chemotherapy using low-dose antineoplastic agents and the optimal dosage and administration schedule of antineoplastic agents need to be determined through further research.

Treatment of evolving cancers will require dynamic decision support

Cancer research has traditionally focused on developing new agents, but an underexplored question is that of the dose and frequency of existing drugs. Based on the modus operandi established in the early days of chemotherapies, most drugs are administered according to predetermined schedules that seek to deliver the maximum tolerated dose and are only adjusted for toxicity. However, we believe that the complex, evolving nature of cancer requires a more dynamic and personalized approach. Chronicling the milestones of the field, we show that the impact of schedule choice crucially depends on processes driving treatment response and failure. As such, cancer heterogeneity and evolution dictate that a one-size-fits-all solution is unlikely-instead, each patient should be mapped to the strategy that best matches their current disease characteristics and treatment objectives (i.e. their 'tumorscape'). To achieve this level of personalization, we need mathematical modeling. In this perspective, we propose a five-step 'Adaptive Dosing Adjusted for Personalized Tumorscapes (ADAPT)' paradigm to integrate data and understanding across scales and derive dynamic and personalized schedules. We conclude with promising examples of model-guided schedule personalization and a call to action to address key outstanding challenges surrounding data collection, model development, and integration.

Mathematical Modeling Support for Lung Cancer Therapy-A Short Review

The paper presents a review of models that can be used to describe dynamics of lung cancer growth and its response to treatment at both cell population and intracellular processes levels. To address the latter, models of signaling pathways associated with cellular responses to treatment are overviewed. First, treatment options for lung cancer are discussed, and main signaling pathways and regulatory networks are briefly reviewed. Then, approaches used to model specific therapies are discussed. Following that, models of intracellular processes that are crucial in responses to therapies are presented. The paper is concluded with a discussion of the applicability of the presented approaches in the context of lung cancer.

Metronomic Chemotherapy: Anti-Tumor Pathways and Combination with Immune Checkpoint Inhibitors

Increasing evidence pinpoints metronomic chemotherapy, a frequent and low dose drug administration with no prolonged drug-free intervals, as a potential tool to fight certain types of cancers. The primary identified targets of metronomic chemotherapy were the tumor endothelial cells involved in angiogenesis. After this, metronomic chemotherapy has been shown to efficiently target the heterogeneous population of tumor cells and, more importantly, elicit the innate and adaptive immune system reverting the "cold" to "hot" tumor immunologic phenotype. Although metronomic chemotherapy is primarily used in the context of a palliative setting, with the development of new immunotherapeutic drugs, a synergistic therapeutic role of the combined metronomic chemotherapy and immune checkpoint inhibitors has emerged at both the preclinical and clinical levels. However, some aspects, such as the dose and the most effective scheduling, still remain unknown and need further investigation. Here, we summarize what is currently known of the underlying anti-tumor effects of the metronomic chemotherapy, the importance of the optimal therapeutic dose and time-exposure, and the potential therapeutic effect of the combined administration of metronomic chemotherapy with checkpoint inhibitors in preclinical and clinical settings.

Revisiting metronomic vinorelbine with mathematical modelling: a Phase I trial in lung cancer

BACKGROUND

A phase Ia/Ib trial of metronomic oral vinorelbine (MOV) driven by a mathematical model was performed in heavily pretreated metastatic Non-Small Cell Lung Cancer or Pleural Mesothelioma patients. Disease Control Rate, progression free survival, toxicity and PK/PD were the main endpoints.

METHODS

Best MOV scheduling was selected using a simplified phenomenological, semi-mechanistic model with a total weekly dose of 150-mg vinorelbine. Computation of individual PK parameters was performed using population approach.

RESULTS

The mathematical model proposed the following metronomic schedule for a 150-mg weekly dose of vinorelbine: 60 mg D1, 30 mg D2, 60 mg D4. A total of 37 heavily pre-treated patients (30 evaluable) were enrolled. Grade III/IV neutropenia was observed in 30% patients. Median PFS was 11 weeks. Disease Control Rate was 73% (i.e.; 13% partial response and 60% stable disease). A large variability in drug exposure (AUC_0-24 h: 53%) and PK parameters (Cl: 83%) were observed among patients. Simulated trough levels after D2 and D4 showed similarly 56-73% variability among patients. Drug exposure was not associated with efficacy, but neutropenia was more frequent in patients with AUC > 250 ng/ml.h. Tumor burden, performance status and neutrophils-to-lymphocyte ratio (NLR) were associated with PFS, suggesting that MOV would be indicated in selected patients. We built a composite score to predict efficacy, mixing baseline tumor size and NLR showing 84% selectivity and 75% specificity.

CONCLUSIONS

MOV was characterized by important variability in drug exposure among patients. However, and despite being all heavily pre-treated, 73% of disease control rate and 11 weeks PFS were achieved with manageable toxicities. PK/PD relationships yielded conflicting results depending on the initial tumor burden and BSA, suggesting that patients should be carefully selected prior to be scheduled for metronomic regimen. Possible role NLR could play as a predictive marker suggests immunomodulating features with MOV.

A systematic review of modeling and simulation approaches in designing targeted treatment technologies for Leukemia Cancer in low and middle income countries

Virtual experimentation is a widely used approach for predicting systems behaviour especially in situations where resources for physical experiments are very limited. For example, targeted treatment inside the human body is particularly challenging, and as such, modeling and simulation is utilised to aid planning before a specific treatment is administered. In such approaches, precise treatment, as it is the case in radiotherapy, is used to administer a maximum dose to the infected regions while minimizing the effect on normal tissue. Complicated cancers such as leukemia present even greater challenges due to their presentation in liquid form and not being localised in one area. As such, science has led to the development of targeted drug delivery, where the infected cells can be specifically targeted anywhere in the body. Despite the great prospects and advances of these modeling and simulation tools in the design and delivery of targeted drugs, their use by Low and Middle Income Countries (LMICs) researchers and clinicians is still very limited. This paper therefore reviews the modeling and simulation approaches for leukemia treatment using nanoparticles as an example for virtual experimentation. A systematic review from various databases was carried out for studies that involved cancer treatment approaches through modeling and simulation with emphasis to data collected from LMICs. Results indicated that whereas there is an increasing trend in the use of modeling and simulation approaches, their uptake in LMICs is still limited. According to the review data collected, there is a clear need to employ these tools as key approaches for the planning of targeted drug treatment approaches.

Minimal PK/PD model for simultaneous description of the maximal tolerated dose and metronomic treatment outcomes in mouse tumor models

PURPOSE

Metronomic chemotherapy (MC) is a promising approach where, in contrast to the conventional maximal tolerated dose (MTD) strategy, regular fractionated doses of the drug are used. This approach has proven its efficacy, although drug dosing and scheduling are often chosen empirically. Pharmacokinetic/pharmacodynamic (PK/PD) models provide a way to choose optimal protocols with computational methods. Existing models are usually too complicated and are valid for only a subset of drug schedules. To address this issue, we propose herein a simple model that can describe MC and MTD regimens simultaneously.

METHODS

The minimal model comprises tumor suppression due to antiangiogenic drug effect together with a cell-kill term, responsible for its cytotoxicity. The model was tested on data obtained on tumor-bearing mice treated with gemcitabine in ether MTD, MC, or combined (MTD + MC) regimens.

RESULTS

We conducted a number of tests in which data were divided in various ways into training and validation sets. The model successfully described different trends in the MTD and MC regimens. With parameters obtained by fitting the model to MTD data, the simulations correctly predicted trends in both the MC and combined therapy groups.

CONCLUSION

Our results demonstrate that the proposed model presents a minimal yet efficient tool for modeling outcomes in different treatment regimens in mice. We hope that this model has the potential for use in clinical practice in the development of patient-specific chemotherapy scheduling protocols based on observed treatment response.

An Overview of In Vitro, In Vivo, and Computational Techniques for Cancer-Associated Angiogenesis Studies

Angiogenesis is a crucial area in scientific research because it involves many important physiological and pathological processes. Indeed, angiogenesis is critical for normal physiological processes, including wound healing and embryonic development, as well as being a component of many disorders, such as rheumatoid arthritis, obesity, and diabetic retinopathies. Investigations of angiogenic mechanisms require assays that can activate the critical steps of angiogenesis as well as provide a tool for assessing the efficacy of therapeutic agents. Thus, angiogenesis assays are key tools for studying the mechanisms of angiogenesis and identifying the potential therapeutic strategies to modulate neovascularization. However, the regulation of angiogenesis is highly complex and not fully understood. Difficulties in assessing the regulators of angiogenic response have necessitated the development of an alternative approach. In this paper, we review the standard models for the study of tumor angiogenesis on the macroscopic scale that include in vitro, in vivo, and computational models. We also highlight the differences in several modeling approaches and describe key advances in understanding the computational models that contributed to the knowledge base of the field.

Metronomic oral vinorelbine in patients with advanced non-small cell lung cancer progressing after nivolumab immunotherapy: a retrospective analysis

Purpose:

The availability of immune checkpoint inhibitors has deeply changed the therapeutic scenario of patients with advanced non-small cell lung cancer (NSCLC). Up until now, chemotherapy still represents the first-line treatment for patients with advanced NSCLC not harbouring genetic mutations or lacking high expression of programmed death ligand even if the addition of immunotherapy to first-line chemotherapy has recently been shown to improve clinical outcome. We carried out a multi-institutional retrospective analysis on third-line chemotherapy with metronomic oral vinorelbine (VNR) in a series of patients with metastatic NSCLC pre-treated with first-line chemotherapy and second-line immunotherapy.

Patients and methods:

Thirty patients with metastatic NSCLC with progressive disease after first-line chemotherapy and subsequent immunotherapy were treated with metronomic oral VNR continuously at the fixed dose of 30 mg three times per week.

Results:

A partial response was achieved in 4 patients (13.3%), while 10 patients (33.3%) displayed disease stabilisation for an overall disease control rate of 46.7%. Median progression-free survival was 3.9 months (range 1–13 months) and median OS reached 8.1 months (range 4.0–24.0+ months) with a 12-month survival rate of 22%.

Conclusion:

Oral metronomic VNR appears to be active and safe in patients with metastatic NSCLC in progression after first-line chemotherapy and second-line immunotherapy. The results reported, although from a limited sample, may suggest its use for long-term stabilisation of the disease with good patient compliance.

Open-label Phase II trial to evaluate safety and efficacy of second-line metronomic oral vinorelbine-atezolizumab combination for stage-IV non-small-cell lung cancer - VinMetAtezo trial, (GFPC‡ 04-2017)

Metronomic chemotherapy is defined as frequent low-dose administration without prolonged drug-free breaks. Combining immune-checkpoint inhibitors and metronomic chemotherapy is a new approach to improve responses and delay onset of resistance to immune-checkpoint inhibitors. This multicenter, Phase II, open-label, single-arm study was designed to assess the safety and efficacy of metronomic oral vinorelbine in combination with immune-checkpoint inhibitors in advanced non-small-cell lung cancers progressing after first-line platinum-based chemotherapy. The recommended metronomic oral vinorelbine dose will be determined during a safety run-in period including 12 patients; the main study will include 59 additional patients. The primary outcome is progression-free survival at 4 months. Secondary outcomes are safety of the combination, median overall survival, objective response rate, disease-control rate at 4 months and quality of life (NCT03801304).

Metronomic therapy in pediatric oncology: A snapshot

Metronomic chemotherapy transitioned from the bench to bedside in the early 2000s and since then has carved a niche for itself in pediatric oncology. It has been used solely or in combination with other modalities such as radiotherapy, maximum tolerated dose chemotherapy, and targeted agents in adjuvant, palliative, as well as maintenance settings. No wonder, the resulting medical literature is extremely heterogeneous. In this review, the authors review and synthesize the published literature in pediatric metronomics giving a glimpse of its history, varied applications, and evolution of this genre of chemotherapy in pediatric cancers. Limitations, future prospects, and grey areas are also highlighted.

Metronomic Chemotherapy with Vinorelbine Produces Clinical Benefit and Low Toxicity in Frail Elderly Patients Affected by Advanced Non-Small Cell Lung Cancer

BACKGROUND

Lung cancer is the leading cause of death worldwide. The treatment choice for advanced stage of lung cancer may depend on histotype, performance status (PS), age, and comorbidities. In the present study, we focused on the effect of metronomic vinorelbine treatment in elderly patients with advanced unresectable non-small cell lung cancer (NSCLC).

METHODS

From January 2016 to December 2016, 44 patients affected by non-small cell lung cancer referred to our oncology day hospital were progressively analyzed. The patients were treated with oral vinorelbine 30 mg x 3/wk or 40 mg x 3/wk meaning one day on and one day off. The patients were older than 60, stage IIIB or IV, ECOG PS ≥ 1, and have at least one important comorbidity (renal, hepatic, or cardiovascular disease). The schedule was based on ECOG-PS and comorbidities. The primary endpoint was progression-free survival (PFS). PFS was used to compare patients based on different scheduled dosage (30 or 40 mg x3/weekly) and age (more or less than 75 years old) as exploratory analysis. We also evaluated as secondary endpoint toxicity according to Common Toxicity Criteria Version 2.0.

RESULTS

Vinorelbine showed a good safety profile at different doses taken orally and was effective in controlling cancer progression. The median overall survival (OS) was 12 months. The disease control rate (DCR) achieved 63%. The median PFS was 9 months. A significant difference in PFS was detected comparing patients aged below with those over 75, and the HR value was 0.72 (p<0.05). Not significant was the difference between groups with different schedules.

CONCLUSIONS

This study confirmed the safety profile of metronomic vinorelbine and its applicability for patients unfit for standard chemotherapies and adds the possibility of considering this type of schedule not only for very elderly patients.

Optimal dynamic regimens with artificial intelligence: The case of temozolomide

We determine an optimal protocol for temozolomide using population variability and dynamic optimization techniques inspired by artificial intelligence. We use a Pharmacokinetics/Pharmacodynamics (PK/PD) model based on Faivre and coauthors (Faivre, et al., 2013) for the pharmacokinetics of temozolomide, as well as the pharmacodynamics of its efficacy. For toxicity, which is measured by the nadir of the normalized absolute neutrophil count, we formalize the myelosuppression effect of temozolomide with the physiological model of Panetta and coauthors (Panetta, et al., 2003). We apply the model to a population with variability as given in Panetta and coauthors (Panetta, et al., 2003). Our optimization algorithm is a variant in the class of Monte-Carlo tree search algorithms. We do not impose periodicity constraint on our solution. We set the objective of tumor size minimization while not allowing more severe toxicity levels than the standard Maximum Tolerated Dose (MTD) regimen. The protocol we propose achieves higher efficacy in the sense that –compared to the usual MTD regimen– it divides the tumor size by approximately 7.66 after 336 days –the 95% confidence interval being [7.36–7.97]. The toxicity is similar to MTD. Overall, our protocol, obtained with a very flexible method, gives significant results for the present case of temozolomide and calls for further research mixing operational research or artificial intelligence and clinical research in oncology.

Modeling therapeutic response to radioiodine in metastatic thyroid cancer: a proof-of-concept study for individualized medicine

Purpose

Radioiodine therapy (RAI) has traditionally been used as treatment for metastatic thyroid cancer, based on its ability to concentrate iodine. Propositions to maximize tumor response with minimizing toxicity, must recognize the infinite possibilities of empirical tests. Therefore, an approach of this study was to build a mathematical model describing tumor growth with the kinetics of thyroglobulin (Tg) concentrations over time, following RAI for metastatic thyroid cancer.

Experimental Design

Data from 50 patients with metastatic papillary thyroid carcinoma treated within eight French institutions, followed over 3 years after initial RAI treatments, were included in the model. A semi-mechanistic mathematical model that describes the tumor growth under RAI treatment was designed.

Results

Our model was able to separate patients who responded to RAI from those who did not, concordant with the physicians' determination of therapeutic response. The estimated tumor doubling-time (Td was found to be the most informative parameter for the distinction between responders and non-responders. The model was also able to reclassify particular patients in early treatment stages.

Conclusions

The results of the model present classification criteria that could indicate whether patients will respond or not to RAI treatment, and provide the opportunity to perform personalized management plans.

Precision Medicine with Imprecise Therapy: Computational Modeling for Chemotherapy in Breast Cancer

Medical oncology is in need of a mathematical modeling toolkit that can leverage clinically-available measurements to optimize treatment selection and schedules for patients. Just as the therapeutic choice has been optimized to match tumor genetics, the delivery of those therapeutics should be optimized based on patient-specific pharmacokinetic/pharmacodynamic properties. Under the current approach to treatment response planning and assessment, there does not exist an efficient method to consolidate biomarker changes into a holistic understanding of treatment response. While the majority of research on chemotherapies focus on cellular and genetic mechanisms of resistance, there are numerous patient-specific and tumor-specific measures that contribute to treatment response. New approaches that consolidate multimodal information into actionable data are needed. Mathematical modeling offers a solution to this problem. In this perspective, we first focus on the particular case of breast cancer to highlight how mathematical models have shaped the current approaches to treatment. Then we compare chemotherapy to radiation therapy. Finally, we identify opportunities to improve chemotherapy treatments using the model of radiation therapy. We posit that mathematical models can improve the application of anticancer therapeutics in the era of precision medicine. By highlighting a number of historical examples of the contributions of mathematical models to cancer therapy, we hope that this contribution serves to engage investigators who may not have previously considered how mathematical modeling can provide real insights into breast cancer therapy.

Frequency-Domain Response Analysis for Quantitative Systems Pharmacology Models

Drug dosing regimen can significantly impact drug effect and, thus, the success of treatments. Nevertheless, trial and error is still the most commonly used method by conventional pharmacometric approaches to optimize dosing regimen. In this tutorial, we utilize four distinct classes of quantitative systems pharmacology models to introduce frequency-domain response analysis, a method widely used in electrical and control engineering that allows the analytical optimization of drug treatment regimen from the dynamics of the model.

Mathematical modeling for Phase I cancer trials: A study of metronomic vinorelbine for advanced non-small cell lung cancer (NSCLC) and mesothelioma patients

INTRODUCTION

Using mathematical modelling allows to select a treatment's regimen across infinite possibilities. Here, we report the phase I assessment of a new schedule for metronomic vinorelbine in treating refractory advanced NSCLC and mesothelioma patients.

RESULTS

Overall, 13 patients were screened and 12 were treated (50% male, median age: 68yrs), including 9 NSCLC patients. All patients received at least one week (3 doses) of treatment. At data cut-off, the median length of treatment was 6.5 weeks (1-32+). All the patients presented with at least one adverse event (AE) and six patients with a severe AE (SAE). One partial response and 5 stable diseases were observed. The median OS was 6.4 months (95% CI, 4.8 to 12 months). The median and mean vinorelbine's AUC were 122 ng/ml*h and 159 ng/ml*h, respectively, with the higher plasmatic vinorelbine exposure associated with the best ORR (difference of AUC comparison between responders and non-responders, p-value 0.017).

MATERIALS AND METHODS

The mathematical modelling determined the administration of vinorelbine, 60 mg on Day 1, 30 mg on Day 2 and 60 mg on Day 4 weekly until progression, as the best schedule. Advanced NSCLC or mesothelioma patients progressing after standard treatment were eligible for the trial. NCT02555007.

CONCLUSIONS

Responses with acceptable safety profile were observed in heavily pretreated NSCLC and mesothelioma patients using oral vinorelbine at this metronomic dosage based on a mathematic modeling. This study demonstrates the feasibility of this new type of approach, as mathematical modeling may help to rationally decide the better regimen to be clinically tested across infinite possibilities.

Mathematical optimisation of the cisplatin plus etoposide combination for managing extensive-stage small-cell lung cancer patients

Background:

Small-cell lung cancer (SCLC) represents one of the most aggressive forms of lung cancer. Despite the fair sensitivity of SCLC to chemotherapy and radiotherapy, the current standard treatment regimens have modest survival rates and are associated with potential life-threatening adverse events. Therefore, research into new optimised regimens that increase drug efficacy while respecting toxicity constraints is of primary importance.

Methods:

A PK/PD model for the combination of cisplatin and etoposide to treat extensive-stage SCLC patients was generated. The model takes into consideration both the efficacy of the drugs and their haematological toxicity. Using optimisation techniques, the model can be used to propose new regimens.

Results:

Three new regimens with varying timing for combining cisplatin and etoposide have been generated that respect haematological toxicity constraints and achieve better or similar tumour regression. The proposed regimens are: (1) Protocol OP1: etoposide 80 mg m⁻² over 1 h D1, followed by a long infusion 12 h later (over 3 days) of 160 mg m⁻² plus cisplatin 80 mg m⁻² over 1 h D1, D1–D1 21 days; (2) Protocol OP2: etoposide 80 mg m⁻² over 1 h D1, followed by a long infusion 12 h later (over 4 days) of 300 mg m⁻² plus cisplatin 100 mg m⁻² over 1 h D1, D1–D1 21 days; and (3) Protocol OP3: etoposide 40 mg m⁻² over 1 h, followed by a long infusion 6 h later (3 days) of 105 mg m⁻² plus cisplatin 50 mg m⁻² over 1 h, D1–D1 14 days.

Conclusions:

Mathematical modelling can help optimise the design of new cisplatin plus etoposide regimens for managing extensive-stage SCLC patients.

Pharmacometrics-based decision tools facilitate mHealth implementation

INTRODUCTION

The healthcare system is experiencing a paradigm shift in delivering its services, evolving from a reactive 'one size-fits-all' structure to a patient-centric model focusing on individualized medicine. This change is driven by scientific progress, including quantitative evaluation and optimization of treatment strategies through pharmacometric approaches, harnessing the power of the digital revolution. Areas covered: This review describes four main steps to apply pharmacometrics-based decision support tools, consisting of validated scientific components, available technical options, consideration of regulatory aspects, and achievement of efficient commercialization. Examples of pharmacometrics-based decision tools that support monitoring of patients and individualization of treatment strategies in neonates, children and adults are presented. Expert commentary: We envision that user-friendly decision support tools will facilitate implementation of mobile health approaches (mHealth) realizing benefits to paediatric and adult patients and their caregivers.

A phase Ia/Ib clinical trial of metronomic chemotherapy based on a mathematical model of oral vinorelbine in metastatic non-small cell lung cancer and malignant pleural mesothelioma: rationale and study protocol

Background

Metronomic oral vinorelbine is effective in metastatic NSCLC and malignant pleural mesothelioma, but all the studies published thus far were based upon a variety of empirical and possibly suboptimal schedules, with inconsistent results. Mathematical modelling showed by simulation that a new metronomic protocol could lead to a better safety and efficacy profile.

Design

This phase Ia/Ib trial was designed to confirm safety (phase Ia) and evaluate efficacy (phase Ib) of a new metronomic oral vinorelbine schedule. Patients with metastatic NSCLC or malignant pleural mesothelioma in whom standard treatments failed and who exhibited ECOG performance status 0–2 and adequate organ function will be eligible. Our mathematical PK-PD model suggested an alternative weekly D1, D2 and D4 schedule (named Vinorelbine Theoretical Protocol) with a respective dose of 60, 30 and 60 mg. Trial recruitment will be two-staged, as 12 patients are planned to participate in phase Ia to confirm safety and consolidate the calibration of the model parameters. Depending on the phase Ia results and after a favourable decision from a consultative committee, the extension phase (phase Ib) will be an efficacy study including 20 patients who will receive the Optimal Vinorelbine Theoretical Protocol. The primary endpoint is the tolerance (assessed by CTC v4.0) for the phase Ia and the objective response according to RECIST 1.1 for phase Ib.

An ancillary study on circulating angiogenesis biomarkers will be a subproject of the trial.

Discussion

This ongoing trial is the first to prospectively test a mathematically optimized schedule in metronomic chemotherapy. As such, this trial can be considered as a proof-of-concept study demonstrating the feasibility to run a computational-driven protocol to ensure an optimal efficacy/toxicity balance in patients with cancer.

Trial registration

EudraCT N°: 2015-000138-31

Metronomic oral vinorelbine in advanced breast cancer and non-small-cell lung cancer: current status and future development

Metronomic chemotherapy (mCT), a frequent administration of low-dose chemotherapy, allows prolonged treatment duration and minimizes the toxicity of standard-dose chemotherapy. mCT has multiple actions against cancer cells including inhibition of angiogenesis and modulation of the immune system. A number of studies lend support to the clinical efficacy of mCT in advanced breast cancer and non-small-cell lung cancer. However, further evidence is necessary to describe the optimal use of mCT and to identify suitable patients. Oral vinorelbine has emerged as a promising metronomic treatment in patients with metastatic breast cancer and non-small-cell lung cancer and is the only orally available microtubule-targeting agent. This paper reviews current evidence on metronomic oral vinorelbine, discusses its management and defines a suitable patient profile on the basis of a workshop of Italian experts.

Metronomic chemotherapy: an attractive alternative to maximum tolerated dose therapy that can activate anti-tumor immunity and minimize therapeutic resistance

The administration of chemotherapy at reduced doses given at regular, frequent time intervals, termed 'metronomic' chemotherapy, presents an alternative to standard maximal tolerated dose (MTD) chemotherapy. The primary target of metronomic chemotherapy was originally identified as endothelial cells supporting the tumor vasculature, and not the tumor cells themselves, consistent with the emerging concept of cancer as a systemic disease involving both tumor cells and their microenvironment. While anti-angiogenesis is an important mechanism of action of metronomic chemotherapy, other mechanisms, including activation of anti-tumor immunity and a decrease in acquired therapeutic resistance, have also been identified. Here we present evidence supporting a mechanistic explanation for the improved activity of cancer chemotherapy when administered on a metronomic, rather than an MTD schedule and discuss the implications of these findings for further translation into the clinic.