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sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in science

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Stephanie Boue, Manager Scientific Transparency & Verification, Philip Morris International

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sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in science

  1. 1. www.sbvimprover.com sbv IMPROVER: an industry initiative to harness the power of the crowd in science Dr Stéphanie Boué, Manager Scientific Transparency & Verification, Philip Morris International R&D Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchatel, Switzerland (Part of Philip Morris International group of companies) CSW – March 2018
  2. 2. 2 © 2018 sbv IMPROVER • Intro - Crowdsourcing in science • Why did Philip Morris International build a program leveraging crowdsourcing? • Example applications of sbv IMPROVER • How do we make it work?
  3. 3. 3 © 2018 sbv IMPROVER • Intro - Crowdsourcing in science • Why did Philip Morris International build a program leveraging crowdsourcing? • Example applications of sbv IMPROVER • How do we make it work?
  4. 4. 4 © 2018 sbv IMPROVER A brief history of crowdsourcing in science • Critical Assessment of protein Structure Prediction (CASP) is a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994. It provides an independent assessment of the state of the art in protein structure modeling to the research community and software users • Critical Assessment of Massive Data Analysis (CAMDA) - founded to provide a forum to critically assess different techniques used in microarray data mining. • Critical Assessment of Information Extraction systems in Biology (BioCreAtIvE) • MicroArray Quality Control (MAQC) • Dialogue for Reverse Engineering Assessments and Methods (DREAM) • sbv IMPROVER …
  5. 5. 5 © 2018 sbv IMPROVER Crowdsourcing biomedical research J. Saez-Rodriguez, J. C. Costello, S. H. Friend, M. R. Kellen, L. Mangravite, P. Meyer, T. Norman, G. Stolovitzky, Crowdsourcing biomedical research: leveraging communities as innovation engines. Nature reviews. Genetics 17, 470-486 (2016)
  6. 6. 6 © 2018 sbv IMPROVER Why do we need crowdsourcing in science? Develop a robust methodology that verifies systems biology-based approaches Explosion of dataGenomic Literature Molecular Profiles Structures We are experiencing a data deluge… The self-assessment trap: can we all be better than average?  Researchers wishing to publish their methods are usually required to compare their methods against others  Authors’ method tends to be the best in an unreasonable majority of cases  Selective reporting of performance: inadvertent or disingenuous  Choice of only one, best metric Mol Syst Biol. 2011 Oct 11;7:537. doi: 10.1038/msb.2011.70.
  7. 7. 7 © 2018 sbv IMPROVER Benefits of crowdsourcing in science – for the organizers and participants Be part of a pioneering community, working together to improve how scientific research is verified Drive innovation in science with crowdsourced solutions Complement peer review Peer recognition and self-esteem Access network of experts Contribute and work towards consensus in the scientific community Monetary incentives Co-author publications
  8. 8. 8 © 2018 sbv IMPROVER • Intro - Crowdsourcing in science • Why did Philip Morris International build a program leveraging crowdsourcing? • Example applications of sbv IMPROVER • How do we make it work?
  9. 9. 9 © 2018 sbv IMPROVER PMI R&D Smoking is one of the causes of serious diseases such as cardiovascular diseases, lung cancer and chronic obstructive pulmonary disease. Philip Morris International is therefore developing novel products that may have the potential to reduce smoking-related disease risk compared to smoking cigarettes. Scientific determination of the reduced risk potential of these products includes comparison of the biological impact with that of a reference cigarette (3R4F) on a mechanism-by-mechanism basis. We want to share this data and encourage other stakeholders in inhalation toxicology to also share their data on the same platform.
  10. 10. 10 © 2018 sbv IMPROVER Scientific assessment strategy & Systems toxicology Program: Systems Toxicology Demonstrate and quantify the Risk Reduction Potential of RRPs* in vitro and in vivo. Develop methods for the quantitative mechanism-based comparison of the biological impact of RRPs aerosol as compared to cigarette smoke. Further grow our mechanistic understanding of cigarette-smoke induced diseases. Independently verify our findings using community-based approaches. * Reduced-Risk Products ("RRPs") is the term we use to refer to products that present, are likely to present, or have the potential to present less risk of harm to smokers who switch to these products versus continued smoking. We have a range of RRPs in various stages of development, scientific assessment and commercialization. Because our RRPs do not burn tobacco, they produce far lower quantities of harmful and potentially harmful compounds than found in cigarette smoke.
  11. 11. 11 © 2018 sbv IMPROVER Hoeng J et al. A network-based approach to quantifying the impact of biologically active substances. Drug Discovery Today, 2012, 17:413-418 (PMID: 22155224) Multi-Omics Data Systems Response Profile Inflammation (IPN) Cell Proliferation (CPR) Cell Stress (CST) Cell Fate (CFA) Tissue repair and angiogenesis (TRA) Biological Network models Network Perturbation Amplitudes Exposure Sham 3R4F pRRP Test items Test system Biological impact factor (BIF) ∑ 1 per condition vs. control comparing conditions 1 per condition vs. control Systems toxicology assessment: Use disease mechanism understanding for product assessment
  12. 12. 12 © 2018 sbv IMPROVER sbv IMPROVER • sbv IMPROVER stands for Systems Biology Verification combined with Industrial Methodology for Process Verification in Research. • This approach aims to provide a measure of quality control of industrial research and development by verifying the methods used. • The sbv IMPROVER project is a collaborative effort led and funded by PMI Research and Development.
  13. 13. 13 © 2018 sbv IMPROVER • Intro - Crowdsourcing in science • Why did Philip Morris International build a program leveraging crowdsourcing? • Example applications of sbv IMPROVER • How do we make it work?
  14. 14. 14 © 2018 sbv IMPROVER Network verification challenge (2014-2015) Past sbv IMPROVER Challenges Diagnostic signature challenge (2012): Aimed to verify computational approaches that classify clinical samples based on transcriptomics data in 4 disease areas Species translation challenge (2013): Identify a function which maps measurements derived from systematic perturbations in one species to another Understand the system boundaries of the translatability concept Quantify the translatability between species
  15. 15. 15 © 2018 sbv IMPROVER From: Crowdsourcing and curation: perspectives from biology and natural language processing Database (Oxford). 2016;2016. doi:10.1093/database/baw115 New networks, including xenobiotic metabolism response in liver, will be proposed for a new network verification challenge in the next months. Participate at: bionet.sbvimprover.com Leveraging biological knowledge from scientists for network models refinement
  16. 16. 16 © 2018 sbv IMPROVER • Verify and enhance existing biological network models that will then be released to the community for use in research applications such as drug discovery, personalized medicine, and toxicological assessment. • Rapid and simple to get started and participation can last as long as you wish. • Collaborate: have fun competing and collaborating with others. • Learn the Biological Expression Language, and use BELIEF, a curation tool to create BEL statements from text extracted from scientific publications. • Challenge your peers and see in real time how you rank in the leaderboard. • Select the compounds to be tested and fine tune the design of the study to be conducted by InSphero with 3D InSight™ Liver Microtissues*. • Win a travel grant of up to USD 2,000*. • Earn a gift card of 150 USD when reaching 3000 points in the leaderboard*. *(see Challenge rules on bionet.sbvimprover.com) Collaborate. Contribute. Compete. Who can participate? Any biologists interested in network modelling. Questions? sbvimprover.RD@pmi.com Network Verification Challenge 3 – Verify and enhance liver xenobiotic metabolism network models
  17. 17. 17 © 2018 sbv IMPROVER • Identify state-of-the-art computational microbiome analysis pipeline(s) that can be used as off-the-shelf solutions for scientists to best recover the composition and relative abundance of bacterial communities present in a sample. • Requires from a few days to a few weeks develop method. • Contribute and help the scientific community to benchmark computational methods objectively and establish standards and best practices in computational metagenomics data analysis. • Win a travel grant of up to USD 2,000*. • Contribute to writing peer-reviewed scientific article(s) describing the outcome of the challenge. *(see Challenge rules on www.sbvimprover.com) Who can participate? Any computational biologist or data scientist with an interest in sequencing data analysis in general, or in microbiomics. Questions? sbvimprover.RD@pmi.com Microbiomics computational challenge
  18. 18. 18 © 2018 sbv IMPROVER sbv Symposia Boston, 2012 Montreux, 2014 Athens, 2013 Barcelona, 2015 Orlando, 2016 Singapore, 2016 Tel Aviv, 2017
  19. 19. 19 © 2018 sbv IMPROVER • Intro - Crowdsourcing in science • Why did Philip Morris International build a program leveraging crowdsourcing? • Example applications of sbv IMPROVER • How do we make it work?
  20. 20. 20 © 2018 sbv IMPROVER A specific target audience Data Source: World Development Indicators (data.worldbank.org) Percentage of R&D Scientists in the Population Sweden Non-scientists R&D scientists Our target population is really small, and even more so given scientists are already very busy with their own projects -> Communication strategy and choice of incentives are key
  21. 21. 21 © 2018 sbv IMPROVER sbv IMPROVER: a Brand and a Community Engagement with potential participants during scientific conferences: • Oral presentations • Poster presentations • Booth Posters, flyers and giveaways Ambassadors & lectures Webinars PR, email campaigns, eTOC and web banners Social media campaigns
  22. 22. 22 © 2018 sbv IMPROVER sbv IMPROVER website
  23. 23. 23 © 2018 sbv IMPROVER sbv IMPROVER – Media engagement LinkedIn Twitter Facebook
  24. 24. 24 © 2018 sbv IMPROVER Participation map (challenges 1-4)
  25. 25. 25 © 2018 sbv IMPROVER Publications resulting from the sbv IMPROVER project • Ansari, S. et al. On crowd-verification of biological networks. Bioinformatics and biology insights 7 (2013). • Belcastro, V. et al. The sbv IMPROVER Systems Toxicology computational challenge: Identification of human and species-independent blood response markers as predictors of smoking exposure and cessation status. Computational Toxicology, doi:https://doi.org/10.1016/j.comtox.2017.07.004 (2017). • Bilal, E. et al. A crowd-sourcing approach for the construction of species-specific cell signaling networks. Bioinformatics 31, 484-491, doi:10.1093/bioinformatics/btu659 (2015). • Binder, J. et al. in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 270-281. • Boue, S. et al. Enhancement of COPD biological networks using a web-based collaboration interface. F1000Research 4 (2015). • Hoeng, J., Peitsch, M. C., Meyer, P. & Jurisica, I. Where are we at regarding species translation? A review of the sbv IMPROVER challenge. Bioinformatics 31, 451-452, doi:10.1093/bioinformatics/btv065 (2015). • Meyer, P. et al. Verification of systems biology research in the age of collaborative competition. Nature biotechnology 29, 811-815, doi:10.1038/nbt.1968 (2011). • Meyer, P. et al. Industrial methodology for process verification in research (IMPROVER): toward systems biology verification. Bioinformatics 28, 1193-1201, doi:10.1093/bioinformatics/bts116 (2012). • Poussin, C. et al. Crowd-Sourced Verification of Computational Methods and Data in Systems Toxicology: A Case Study with a Heat-Not-Burn Candidate Modified Risk Tobacco Product. Chemical research in toxicology 30, 934-945, doi:10.1021/acs.chemrestox.6b00345 (2017). • Poussin, C. et al. The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cells. Scientific data 1, 140009, doi:10.1038/sdata.2014.9 (2014). • Rhrissorrakrai, K. et al. Understanding the limits of animal models as predictors of human biology: lessons learned from the sbv IMPROVER Species Translation Challenge. Bioinformatics 31, 471-483, doi:10.1093/bioinformatics/btu611 (2015). • sbv IMPROVER project team et al. On Crowd-verification of Biological Networks. Bioinformatics and biology insights 7, 307-325, doi:10.4137/BBI.S12932 (2013). • sbv IMPROVER project team et al. Reputation-based collaborative network biology. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 270-281 (2015). • sbv IMPROVER project team et al. Enhancement of COPD biological networks using a web-based collaboration interface. F1000Research 4, 32, doi:10.12688/f1000research.5984.2 (2015). • sbv IMPROVER project team et al. Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications. Gene regulation and systems biology 10, 51-66, doi:10.4137/GRSB.S39076 (2016). • Tarca, A. L. et al. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge. Bioinformatics 29, 2892-2899, doi:10.1093/bioinformatics/btt492 (2013).
  26. 26. 26 © 2018 sbv IMPROVER Management of crowd-based scientific challenges – Key ingredients Incentive Motivation Comm. & Marketing Platform (IT& IS) Crowd- sourcing System Biology Discovery & innovation ↓ emergent changes Scientific community to verify biological networks and methods Multidisciplinary approaches involving biology, high-performance computing, … Leaderboard & reputation Awards & travel bursaries Invitation to the congress Academic articles Ads Conferences Videos & webinars Publications Ambassadors Intuitive Interactive Social Events Scientific event Top speakers Networking opportunities
  27. 27. 27 © 2018 sbv IMPROVER The sbv IMPROVER project, the websites and the Symposia are part of a collaborative project designed to enable scientists to learn about and contribute to the development of a new crowd sourcing method for verification of scientific data and results. The project is led and funded by Philip Morris International. For more information on the focus of Philip Morris International’s research, please visit www.pmiscience.com. Thank you! Questions? Contact Us sbvimprover.RD@pmi.com>

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