european journal of cancer 48, suppl. 5 (2012) S5–S12
available at www.sciencedirect.com
journal homepage: www.ejcancer.info
Sunday 8 July 2012 Sunday 8 July 2012
08:00−08:50
Educational Lectures
Sunday 8 July 2012
09:00−09:45
Meet the Expert
17 Sequencing
20 Meet the Editor − Inside Nature
No abstract received.
B. Marte1 . 1 Nature Publishing Group, London, United Kingdom
18 Drug Discovery and Development − a Changing Paradigm?
In this session, participants can find out more about scientific publishing. I will discuss how the peer-review process at Nature and other Nature journals works, who the editors are and how we decide which primary research papers are published in Nature. As the editor at Nature involved in handling submissions in the area of cancer, I will highlight our interest in all aspects of the field, including in translational cancer research.
1 1
J. Yingling . Eli Lilly & Co, Cancer Research, Indianapolis IN, USA In the face of mounting social, economic and industry pressure, pharmaceutical firms find themselves at a critical juncture in history, yet drug discovery and development paradigms continue to involve systematic approaches to preclinical and clinical experimentation. Significant advances in technology and computing power have converged to provide an unprecedented opportunity for knowledge creation from the myriad of data produced daily in laboratories around the world. I will review state-of-the-art drug discovery and development technologies and methodology spanning the full continuum from target selection to product launch. Topics to be covered include pre-clinical small molecule and mAb discovery, modern clinical trial designs involving biomarkers and importance of tailored therapeutics as a driver of innovation and pharmaceutical industry transformation. 19 How Do We Study Network Perturbations in Clinical Specimens? How do we Select “Drivers” of Malignancies? S. Friend1 . 1 Sage Bionetworks EU, Seattle WA, USA We need to develop an open innovation space where physicians, patients and scientists can together develop maps of cancer capable of driving better screening, diagnosis, treatment, and control of cancer. We will need to develop an infrastructure to manage this data and to provide an environment to build these maps of disease. This is not a problem that is solved by few but will involve large-scale involvement of the scientific and patient communities working together. Here are some of the issues to be discussed: • Accessible but minimally usable clinical/genomic data − little care to annotate and curate data for other’s use • Mathematical models of disease are not built to be reproduced or versioned by others • Data seen as supplemental materials after publications • Assumption that those funded to generate data somehow own the data they generate • Assumption that genetic alterations in human tumors can be owned • Transient nature of sites where data models and tools for others are maintained • Lack of standard forms for sharing data and future rights • Most patients are not actively participating in donating samples and their outcome data • Few cancer patients as activists demanding sharing data in the public forum • Most clinical/genomic data generated by industry from trials is not shared • Most academics feel they need to sequester data until their lab can complete publishing • Rewards are for first/last authors who want to protect their unique contribution till after full article is published.
21 Meet the ERC C. Heldin1 . 1 Uppsala University, Ludwig Institute for Cancer Research, Uppsala, Sweden The European Research Council (ERC) is a novel instrument for EU funding of excellent frontier research in Europe. The budget for ERC is 7.5 bnEUR for the period 2007–2013. ERC is led by a Scientific Council of 22 European scientists covering all scientific fields. The implementation and daily work of ERC is carried out at an Executive Agency in Brussels with more than 300 employees. ERC has adopted a bottom-up procedure, meaning that all scientists can apply irrespective of field of research. Excellence of the application and the qualifications of the Principal Investigator, as determined by peer-review by highly qualified panels, are the only criteria which determine who will be awarded grants. The grants are large and flexible. Over 90% of the budget of ERC goes to funding of specific projects run by individual scientists. Three streams have been developed, i.e. Starting Grants for young scientists 2−7 years after their PhD, Consolidators Grants for midterm scientists 7−12 years after their PhD, and Advanced Grants for experienced scientists. Thus, ERC covers the entire scientific career, from the establishment of the first independent research group to the productivity ends, without any predetermined retirement age. Recently, two novel, smaller funding streams have been adopted, i.e. the Proof-of-Concept call which can give a scientist who already has an ERC grant additional money to take a discovery further towards application, and the Synergy call, in which groups of 2−4 scientists of complementary skills can apply for money to solve a common research problem. It is anticipated that ERC will continue during the next framework program, Horizon 2020, with an increased budget. With its focus on excellence, ERC provides an opportunity to increase the quality and competitiveness of European science. 22 The Cancer Cell Line Encyclopedia − Using Preclinical Models to Predict Anticancer Drug Sensitivity J. Barretina1 , G. Caponigro1 , N. Stransky2 , K. Venkatesan1 , A.A. Margolin2 , S. Kim3 , C.J. Wilson1 , J. Lehar1 , G.V. Kryukov2 , L. Murray2 , M.P. Morrissey1 , W.R. Sellers1 , R. Schlegel1 , L.A. Garraway2,4 . 1 Novartis Institutes for Biomedical Research, Cambridge, Massachusetts 02139, USA, 2 The Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA, 3 Genomics Institute of the Novartis Research Foundation, San Diego, California 92121, USA, 4 Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts 02115, USA The systematic translation of cancer genomic data into knowledge of tumor biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic
0959-8049/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.