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Sense and Reproducibility: the problem of translating academic discovery to drug discovery Panelists Ira Mellman (chair): VP of Research Oncology, Genentech;

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Presentation on theme: "Sense and Reproducibility: the problem of translating academic discovery to drug discovery Panelists Ira Mellman (chair): VP of Research Oncology, Genentech;"— Presentation transcript:

1 Sense and Reproducibility: the problem of translating academic discovery to drug discovery Panelists Ira Mellman (chair): VP of Research Oncology, Genentech; Prof of Biochemistry & Biophysics UCSF; former JCB Editor in Chief C. Glenn Begley: former VP of Global Oncology, Amgen Elizabeth Iorns: CEO, Science Exchange (Reproducibility Initiative)

2 The problem: biotech/pharma scientists have found it difficult to reproduce published work from academic groups Prinz et al (2011) Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discovery 10:712 [Bayer] Begley & Ellis (2012) Drug development: raise standards for preclinical cancer research. Nature 483:531 [Amgen]

3 Why was this discovered? Industry and academia have different near-term goals: Publication of interesting work that drives a field forward vs Verification of published observations to justify long- term, expensive drug discovery efforts

4 Questions to be addressed by the panel: What is the nature of the reproducibility problem? Poor scientific/analytic quality? Poor quality of the validation effort? Generalizability vs bad science? How widespread is it? Why has it occurred? Problems are complex and difficult to reproduce? Corners are cut in the rush to publish? Inaccurate data representation or analysis? What can we do about it? Nothing? Motivate higher standards? Vigilantism? Institutionalized data verification (Elizabeth Iorns) Journals set higher standards for editing/data display?

5 The JCB experience: Since 2002, figures for all accepted manuscripts screened for inappropriate image manipulation (micrographs, gels) 10% of papers found to contain one or more examples 10% of these (1% overall) rejected after determination that manipulation fraudulently altered a key conclusion Frequencies have not changed in 10 years Issues: Desire to make data look optimal? Digital manipulation is easy to do? Cultural acceptance of digital manipulation

6 Sense and Reproducibility: the problem of translating academic discovery to drug discovery Panelists Ira Mellman (chair): VP of Research Oncology, Genentech; Prof of Biochemistry & Biophysics UCSF; former JCB Editor in Chief C. Glenn Begley: former VP of Global Oncology, Amgen Elizabeth Iorns: CEO, Science Exchange (Reproducibility Initiative)

7 Discussion questions: Is the reproducibility issue a new problem? Why is so much work apparently not reproducible? What should we do about it as a community? Will initiatives like Science Exchange have an impact? How can we guard against spurious claims? What is the role of journals and reviewers? What steps can we as individual scientists take to maximize the chances that our work can be reproduced?


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