In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability

PLoS Comput Biol. 2018 Oct 8;14(10):e1006460. doi: 10.1371/journal.pcbi.1006460. eCollection 2018 Oct.

Abstract

The delivery of blood-borne therapeutic agents to solid tumours depends on a broad range of biophysical factors. We present a novel multiscale, multiphysics, in-silico modelling framework that encompasses dynamic tumour growth, angiogenesis and drug delivery, and use this model to simulate the intravenous delivery of cytotoxic drugs. The model accounts for chemo-, hapto- and mechanotactic vessel sprouting, extracellular matrix remodelling, mechano-sensitive vascular remodelling and collapse, intra- and extravascular drug transport, and tumour regression as an effect of a cytotoxic cancer drug. The modelling framework is flexible, allowing the drug properties to be specified, which provides realistic predictions of in-vivo vascular development and structure at different tumour stages. The model also enables the effects of neoadjuvant vascular normalisation to be implicitly tested by decreasing vessel wall pore size. We use the model to test the interplay between time of treatment, drug affinity rate and the size of the vessels' endothelium pores on the delivery and subsequent tumour regression and vessel remodelling. Model predictions confirm that small-molecule drug delivery is dominated by diffusive transport and further predict that the time of treatment is important for low affinity but not high affinity cytotoxic drugs, the size of the vessel wall pores plays an important role in the effect of low affinity but not high affinity drugs, that high affinity cytotoxic drugs remodel the tumour vasculature providing a large window for the normalisation of the vascular architecture, and that the combination of large pores and high affinity enhances cytotoxic drug delivery efficiency. These results have implications for treatment planning and methods to enhance drug delivery, and highlight the importance of in-silico modelling in investigating the optimisation of cancer therapy on a personalised setting.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents* / metabolism
  • Antineoplastic Agents* / pharmacokinetics
  • Antineoplastic Agents* / pharmacology
  • Capillary Permeability / drug effects*
  • Computational Biology
  • Computer Simulation*
  • Drug Delivery Systems
  • Endothelium, Vascular* / drug effects
  • Endothelium, Vascular* / metabolism
  • Humans
  • Models, Biological*
  • Neoplasms* / drug therapy
  • Neoplasms* / metabolism
  • Neovascularization, Pathologic / drug therapy
  • Neovascularization, Pathologic / metabolism

Substances

  • Antineoplastic Agents

Grants and funding

VV has been partially supported by an FP7-PEOPLE project (Project ID: 627025; URL: https://cordis.europa.eu/project/rcn/188072_en.html), and TS has been supported by an FP7-IDEAS-ERC project (Project ID: 336839; URL: https://cordis.europa.eu/project/rcn/109567_en.html). This work was partly supported by H2020-WIDESPREAD-04-2017-Teaming Phase 1, Grant Agreement 763781, Integrated Precision Medicine Technologies. However, the funders had no role in the study design, data collection and analysis, the decision to publish, or the preparation of the manuscript. PAW has received no specific funding for this work.