Systems Biology Tools and Data for a Better Understanding of Mechanisms of Toxicity.

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Risk assessment in the context of 21st century toxicology relies on the elucidation and understanding of mechanisms of toxicity. While no single experiment allows deciphering toxic mechanisms at the interplay of complex pathways, network models built from the knowledge accumulated in the scientific literature enable a more comprehensive view of the changes to the system caused by toxic or pharmaceutical agents. Moreover well‐designed and rich data collection in the context of toxicology or pharmacology will further advance risk assessment. Bringing the scientific community together and harnessing the wisdom of crowds is the method used by sbv IMPROVER to verify methods and biological networks used in systems toxicology, pharmacology and diagnostic through a series of collaborative competition challenges. We will present past challenges and their outcome regarding methods to classify biological samples based on their transcriptomics profiles and to assess the translatability of key pathways between human and rat cell cultures. Moreover, we will show how we apply crowd‐sourcing methods to verify and fine tune network models of lung biology.Our goal at Philip Morris International R&D is to develop and assess potentially reduced risk alternatives to combustible cigarettes in order to reduce the harm caused by smoking, which is one of the leading causes of preventable diseases. The next sbv IMPROVER challenge will focus on evaluating large pre‐clinical Systems Toxicology datasets generated from experimental systems exposed to conventional cigarette smoke and the aerosol generated from a prototype noncombustible product's aerosol.