Literature DB >> 26555236

Personalised and Precision Medicine in Cancer Clinical Trials: Panacea for Progress or Pandora's Box?

Mark Lawler1, Richard Sullivan.   

Abstract

Cancer clinical trials have been one of the key foundations for significant advances in oncology. However, there is a clear recognition within the academic, care delivery and pharmaceutical/biotech communities that our current model of clinical trial discovery and development is no longer fit for purpose. Delivering transformative cancer care should increasingly be our mantra, rather than maintaining the status quo of, at best, the often miniscule incremental benefits that are observed with many current clinical trials. As we enter the era of precision medicine for personalised cancer care (precision and personalised medicine), it is important that we capture and utilise our greater understanding of the biology of disease to drive innovative approaches in clinical trial design and implementation that can lead to a step change in cancer care delivery. A number of advances have been practice changing (e.g. imatinib mesylate in chronic myeloid leukaemia, Herceptin in erb-B2-positive breast cancer), and increasingly we are seeing the promise of a number of newer approaches, particularly in diseases like lung cancer and melanoma. Targeting immune checkpoints has recently yielded some highly promising results. New algorithms that maximise the effectiveness of clinical trials, through for example a multi-stage, multi-arm type design are increasingly gaining traction. However, our enthusiasm for the undoubted advances that have been achieved are being tempered by a realisation that these new approaches may have significant cost implications. This article will address these competing issues, mainly from a European perspective, highlight the problems and challenges to healthcare systems and suggest potential solutions that will ensure that the cost/value rubicon is addressed in a way that allows stakeholders to work together to deliver optimal cost-effective cancer care, the benefits of which can be transferred directly to our patients.
© 2015 S. Karger AG, Basel.

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Mesh:

Year:  2015        PMID: 26555236     DOI: 10.1159/000441555

Source DB:  PubMed          Journal:  Public Health Genomics        ISSN: 1662-4246            Impact factor:   2.000


  4 in total

1.  The Cancer Epidemiology Descriptive Cohort Database: A Tool to Support Population-Based Interdisciplinary Research.

Authors:  Amy E Kennedy; Muin J Khoury; John P A Ioannidis; Michelle Brotzman; Amy Miller; Crystal Lane; Gabriel Y Lai; Scott D Rogers; Chinonye Harvey; Joanne W Elena; Daniela Seminara
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-07-20       Impact factor: 4.254

Review 2.  Tau-based therapies in neurodegeneration: opportunities and challenges.

Authors:  Chuanzhou Li; Jürgen Götz
Journal:  Nat Rev Drug Discov       Date:  2017-10-06       Impact factor: 84.694

Review 3.  Mathematical and Computational Modeling in Complex Biological Systems.

Authors:  Zhiwei Ji; Ke Yan; Wenyang Li; Haigen Hu; Xiaoliang Zhu
Journal:  Biomed Res Int       Date:  2017-03-13       Impact factor: 3.411

4.  On the road to personalised and precision geomedicine: medical geology and a renewed call for interdisciplinarity.

Authors:  Maged N Kamel Boulos; Jennifer Le Blond
Journal:  Int J Health Geogr       Date:  2016-01-28       Impact factor: 3.918

  4 in total

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