Abstract
In silico cancer models have demonstrated great potential as a tool to improve drug design, optimise the delivery of drugs to target sites in the host tissue and, hence, improve therapeutic efficacy and patient outcome. However, there are significant barriers to the successful translation of in silico technology from bench to bedside. More precisely, the specification of unknown model parameters, the necessity for models to adequately reflect in vivo conditions, and the limited amount of pertinent validation data to evaluate models' accuracy and assess their reliability, pose major obstacles in the path towards their clinical translation. This review aims to capture the state-of-the-art in in silico cancer modelling of vascularised solid tumour growth, and identify the important advances and barriers to success of these models in clinical oncology. Particular emphasis has been put on continuum-based models of cancer since they - amongst the class of mechanistic spatio-temporal modelling approaches - are well-established in simulating transport phenomena and the biomechanics of tissues, and have demonstrated potential for clinical translation. Three important avenues in in silico modelling are considered in this contribution: first, since systemic therapy is a major cancer treatment approach, we start with an overview of the tumour perfusion and angiogenesis in silico models. Next, we present the state-of-the-art in silico work encompassing the delivery of chemotherapeutic agents to cancer nanomedicines through the bloodstream, and then review continuum-based modelling approaches that demonstrate great promise for successful clinical translation. We conclude with a discussion of what we view to be the key challenges and opportunities for in silico modelling in personalised and precision medicine.
Highlights
Cancer is regarded a complex and heterogeneous disease [1] that encompasses a large family of pathologies that involve abnormal cell growth and death, establishment of new blood vessels, and the potential to invade or spread to other parts of the body
The angiogenesis model was comprised of a Fick-like diffusion equation governing vessel cell density as a function of chemo- and haptotaxis coupled with partial differential equations for the drug and fibronectin concentrations, and drug transport through the network was described by a Poiseuille constitutive model
Despite the remarkable progress been made in in silico modelling in cancer, several important questions remain in understanding the transport of systemic drugs and nanomedicines, tumour perfusion, the treatment dynamics and cancer resistance, how to optimally combine specific chemotherapies with targeted therapies and radiation therapy
Summary
Cancer is regarded a complex and heterogeneous disease [1] that encompasses a large family of pathologies that involve abnormal cell growth and death, establishment of new blood vessels, and the potential to invade or spread to other parts of the body. With the emergence of precision and personalised medicine, cancer researchers have driven the development of new methods for systems analysis of the disease and its treatment.1 In this regard, reductionist in vitro and in vivo experimental models have been widely used to investigate the tumour–host microenvironment (THM) heterogeneity along with the factors that influence the effectiveness of chemotherapeutic agents and radiotherapy (e.g. that includes the size, charge and solubility drugs, the dosing level and schedule, the pharmacokinetics of drug residence in the circulation, the pharmacodynamics of cell killing in response to drug exposure) [5, 3, 6]. We conclude with the main obstacles and challenges in in silico cancer modelling (Section 5) along with the opportunities for its future use as a non-invasive personalised clinical tool
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