Biomarker discovery for nicotine-containing product assessment can be facilitated by INTERVALS, a platform to share and analyze non-clinical and clinical data

      Boue, S.; Talikka, M.; Martin, F.; Poussin, C.; Ivanov, N. V.; Hoeng, J.; Peitsch, M. C.

      Conference date
      Feb 22, 2019
      Conference name
      Society for Research on Nicotine and Tobacco (SRNT) 2019

      The harm caused by smoking could be reduced by offering safer alternatives to cigarettes, such as e-cigarettes and heated tobacco products, to smokers who are not willing to quit. Extensive and rigorous scientific studies are conducted by industry and the global scientific community to assess the relative risk of so-called “modified risk tobacco products” compared with that of smoking cigarettes. As the scientific community is conducting such assessments in a variety of laboratory models as well as clinical studies, knowledge and large datasets on toxicity and disease mechanisms are becoming available. By fostering the consolidation of data and knowledge gained from studies assessing novel tobacco/nicotine delivery products on a community platform, new hypotheses may be generated, including the development of biomarkers of exposure or disease risk. Therefore, we have created and are developing INTERVALS (, an online platform supporting independent, third-party collaboration by proactively sharing detailed protocols, tools, and data from assessment studies. Data files are accompanied by the relevant information to foster reproducible research and encourage data re-analysis. Strengthened by community and peer-review features, INTERVALS enables the necessary dialogue between industry, independent reviewers, the public health community, and regulatory agencies that can validate the harm reduction potential of these products. Employing datasets from multiple in vivo and clinical studies, we have derived a whole blood gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. A crowdsourcing challenge, part of sbv IMPROVER, has allowed verification of the signature and classification of samples from smokers switching to a heat-not-burn product and those who continue to smoke. All datasets and a summary of the methods used to generate this signature are published on INTERVALS. In this presentation, we will summarize the gene signature, its crowdsourced verification, and the classification obtained as well as introduce the INTERVALS platform, a new vector of innovation.