Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • News & Views
  • Published:

COMPUTATIONAL ONCOLOGY

Predicting a tumour’s drug uptake

Nature Biomedical Engineering volume 2, pages 717–718 (2018)Cite this article

Subjects

Computational modelling, informed by data from 3D volumetric imaging of transparent and intact whole-tumour samples, predicts blood flow and the spatial distribution of drug uptake in tumours.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: A pipeline for predicting drug uptake by tumour tissue.

References

  1. Barbolosi, D. et al. Nat. Rev. Clin. Oncol. 13, 242–254 (2016).

    Article  Google Scholar 

  2. McKenna, M. et al. Transl. Oncol. 11, 732–742 (2018).

    Article  Google Scholar 

  3. Richardson, D. S. & Lichtman, J. W. Cell 162, 246–257 (2015).

    Article  CAS  Google Scholar 

  4. Sharpe, J. et al. Science 296, 541–555 (2002).

    Article  CAS  Google Scholar 

  5. Tomer, R. et al. Meth. Mol. Biol. 931, 123–137 (2013).

    Article  CAS  Google Scholar 

  6. Tanaka, N. et al. Nat. Biomed. Eng. 1, 796–806 (2017).

    Article  Google Scholar 

  7. Glaser, A. K. et al. Nat. Biomed. Eng. 1, 0084 (2017).

    Article  Google Scholar 

  8. Marusyk, A. et al. Nat. Rev. Cancer 12, 323–334 (2012).

    Article  CAS  Google Scholar 

  9. d’Esposito, A. et al. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-018-0306-y (2018).

  10. Jain, R. K. et al. Annu. Rev. Biomed. Eng. 16, 321–346 (2014).

    Article  CAS  Google Scholar 

  11. Tanaka, N. et al. Br. J. Cancer 118, 995–999 (2018).

    Article  CAS  Google Scholar 

  12. Fernandez, M. I. et al. Eur. Urol. 53, 571–580 (2008).

    Article  Google Scholar 

  13. DiMasi, J. A. et al. Clin. Pharmacol. Ther. 87, 272–277 (2010).

    Article  CAS  Google Scholar 

  14. Uhlén, P. & Tanaka, N. Trends Cancer 4, 337–341 (2018).

    Article  Google Scholar 

  15. Kiessling, F. et al. Nat. Med. 10, 1133–1138 (2004).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden

    Lauri Louhivuori, Shigeaki Kanatani & Per Uhlén

Authors
  1. Lauri Louhivuori
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shigeaki Kanatani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Per Uhlén
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Per Uhlén.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Louhivuori, L., Kanatani, S. & Uhlén, P. Predicting a tumour’s drug uptake. Nat Biomed Eng 2, 717–718 (2018). https://doi.org/10.1038/s41551-018-0311-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41551-018-0311-1

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer