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Sense and Reproducibility: the problem of translating academic discovery to drug discovery

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

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Sense and Reproducibility: the problem of translating academic discovery to drug discovery

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  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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