Abstract

The US FDA defines modified risk tobacco products (MRTPs) as products that aim to reduce harm or the risk of tobacco-related disease associated with commercially marketed tobacco products. Establishing a product’s potential as an MRTP requires scientific substantiation including toxicity studies and measures of disease risk relative to those of cigarette smoking. Best practices encourage verification of the data from such studies through sharing and open standards. Building on the experience gained from the OpenTox project, a proof-of-concept database and website (INTERVALS) has been developed to share results from both in vivo inhalation studies and in vitro studies conducted by Philip Morris International R&D to assess candidate MRTPs. As datasets are often generated by diverse methods and standards, they need to be traceable, curated, and the methods used well described so that knowledge can be gained using data science principles and tools. The data-management framework described here accounts for the latest standards of data sharing and research reproducibility. Curated data and methods descriptions have been prepared in ISA-Tab format and stored in a database accessible via a search portal on the INTERVALS website. The portal allows users to browse the data by study or mechanism (e.g., inflammation, oxidative stress) and obtain information relevant to study design, methods, and the most important results. Given the successful development of the initial infrastructure, the goal is to grow this initiative and establish a public repository for 21st-century preclinical systems toxicology MRTP assessment data and results that supports open data principles.

Highlights

  • IntroductionHarm reduction and modified risk tobacco products (MRTPs) Smoking is addictive and causes a number of serious diseases, including cardiovascular disease (heart disease), lung cancer, and chronic obstructive pulmonary disease (emphysema, chronic bronchitis)[1]

  • Harm reduction and modified risk tobacco products (MRTPs) Smoking is addictive and causes a number of serious diseases, including cardiovascular disease, lung cancer, and chronic obstructive pulmonary disease[1]

  • We focus on the data science practices developed to support verification of conclusions derived from systems toxicology studies, illustrated by a case study example

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Summary

Introduction

Harm reduction and modified risk tobacco products (MRTPs) Smoking is addictive and causes a number of serious diseases, including cardiovascular disease (heart disease), lung cancer, and chronic obstructive pulmonary disease (emphysema, chronic bronchitis)[1]. In addition to initiatives encouraging prevention and cessation of smoking, harm reduction for smokers may be achieved through the development of novel tobacco products that have the potential to reduce the risk of harm compared to continued cigarette smoking. The U.S Family Smoking Prevention and Tobacco Control Act defines a modified risk tobacco product (MRTP) as any that is ‘sold or distributed to reduce the harm or risk of tobacco-related disease associated with commercially marketed tobacco products’[2]. Building quality into study planning, using methods that have been validated, executed by trained personnel in adequate facilities, and with proper data management and processing practices are the essential components of such a system and are a first step in ensuring data quality, reproducibility and reliability

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