INTERVALS is an online platform established by Philip Morris International R&D to serve data transparency and reproducibility in science.
INTERVALS aims to become a hub for the community interested in product assessment and basic research relevant to tobacco harm reduction and safety assessment of consumer products.
INTERVALS enables independent data re-analysis and collaboration by sharing protocols, tools, and data.
The last few decades have witnessed prominent voices articulate growing concerns on reproducibility in science. At the core of these concerns is the observation that subsequent attempts to replicate certain findings often lead to significantly different results. This problem—which appeared to increase in magnitude—was termed the replication crisis.
Among the culprits are the unprecedented rate at which scientific manuscripts are produced, the ever-growing size and interdisciplinary character of dataset acquisition, and the tremendous demand for computational power, often for a single experiment. All these factors have impinged on the reproducibility of scientific results and, at the same time, on the possibility to effectively peer-review manuscripts. Perhaps with even more dire consequences, the blueprint of this growing crisis also affects regulatory bodies, which need comprehensive and exhaustive access to all past and present research findings pertaining to the assessment of new products.
In an effort to address this problem, Philip Morris International R&D has created INTERVALS, a growing online platform open to scientists from both academia and industry, meant to enable third-party collaboration and data analysis. The website and the associated data warehouse are developed in collaboration with Emakina and Edelweiss Connect GmbH.
With a foundation built by using the latest standards in data sharing and reproducible research, the continuously updated INTERVALS is driven by the idea of proactive sharing of protocols, computational tools, and data from assessment studies. In a single place, it shares results, software, raw data files, and detailed information on the design and protocols used in studies. This facilitates the review process and allows, at the same time, for the reuse of data for generating and testing new hypotheses. We believe that all these traits enhance the transparency of the scientific process several fold and accelerate scientific research.
Initially, the platform was meant to present studies and share data from inhalation toxicology assessments. Owing to its continuous development, INTERVALS has evolved to include clinical study designs and results, various population studies, and even results from the fields of physics and chemistry. Although now enhanced, its core mission remains the same: to establish high standards for transparency and reproducibility by sharing data on scientific assessment of products.
In addition, the INTERVALS platform harbors basic research within the framework of systems biology—leading to a mechanistic understanding of diseases and pathways—as well as research on various aerosols and chemicals.
Taken together, these studies contribute significantly to the understanding of tobacco smoke-induced perturbations in human signaling pathways, detail the scientific assessment of new products, and represent an important step forward in addressing the reproducibility crisis in science by making data and software freely available.
The aforementioned mission of INTERVALS is in line with the vision of the 21st century toxicity testing established by The National Research Council following commission by the United States Environmental Protection Agency. This vision steers away from the sole use of traditional toxicity testing methods and calls for the study of adverse health effects sourced from induced perturbations in human signaling pathways by biologically active substances or their metabolites (Committee on Toxicity Testing and Assessment of Environmental Agents, 2007; Hartung, 2010; Krewski et al., 2010).
While INTERVALS was created as a platform for sharing (raw and processed) datasets and assessment results, the scientific community is invited to use the portal to share their own datasets and results and adhere to our vision of accelerated innovation through scientific transparency.
The portal allows users to browse the data by study, disease, pathway, endpoint, or product and obtain relevant information related to study design, methods, and, most importantly, results from preclinical as well as clinical studies.
INTERVALS VALUES ↑
The last two decades have seen an increase in scientific output and sharing of industry-sponsored and -conducted research, which is met with skepticism from the scientific community. Indeed, reports detailing concerns about data manipulation and misrepresentation have led to a decline in the credibility of industry-sponsored research. Engraved in public opinion, this lack of trust is damaging to innovation and makes the work of regulatory bodies even more difficult. In a now-landmark paper published in 2013, Bauchner and Fontanarosa presented a possible solution for restoring the credibility of the industry (Bauchner and Fontanarosa, 2013).
The INTERVALS platform has implemented the suggestions therein by:
- providing public access to data from industry-sponsored research
- enabling academic scientists to (re)analyze the data
- reporting the contributions and identities of all persons involved
Candidate and potential MRTPs are largely developed and, so far, assessed by tobacco companies. In order to establish the validity of the findings, the INTERVALS platform enables in-depth access to all scientific data and findings and acts as a study repository. Hence, the INTERVALS platform aims to complement the peer-review publication process by offering a comprehensive medium for sharing data, analyses, and software and to allow researchers to find all relevant information, detailed protocols, and, most importantly, interoperable data files to facilitate independent reanalysis of key findings, meta-analysis, and data reuse.
Starting in 2020, the publication of scientific content on INTERVALS will be overseen by an Editorial Board consisting of subject-matter experts and key opinion leaders. Aside from providing expertise and guidance to ensure that researchers are aware of INTERVALS, both in the sense of using the platform and contributing to it, the members of the Editorial Board will ensure that the submissions are appropriate, relevant, and of sufficient quality, in accordance with the COPE guidelines for Editors.
The current state of risk assessment employed for environmental toxicants and therapeutic drugs relies on correlative analyses performed within the framework of epidemiological studies that are run years or even decades after a product is released on the market or after a certain public policy is enacted. This state of affairs leads to irrecoverable delays, well past the point when a change in therapeutic regimen, lifestyle, or environmental exposure can prevent the onset of disease. In addition, post-hoc epidemiological studies do not aim to elucidate the mechanisms that link perturbations in molecular signaling to diseases.
One way to address these issues is to develop a computational approach capable of quantifying the risk posed by exposure to an active substance well in advance (Hoeng et al., 2012). To this end, the INTERVALS platform constitutes a gateway to a comprehensive data structure meant to provide a detailed picture of diseases, pathways, and interaction of active substances with tissues. It is intended to allow exploration of the Data Cube in relation to multiple biologically active substances that can constitute perturbations of biological networks, test systems, and samples.
TRANSPARENCY AND REPRODUCIBILITY IN SCIENCE ↑
The scientific process relies heavily on the peer-review mechanism, which plays a key role in controlling scientific quality, improving performance, and providing credibility. The lack of scientific transparency leads to a peer-review process that is less than ideal and often results in irreproducible science that might have an unpredictable impact on public health or socioeconomic or political factors. To choose just one example, a 2012 report has shown that the results of 47 of 53 published peer-reviewed cancer studies could not be reproduced (Begley and Ioannidis, 2015). Consequently, the last decade has seen increasing awareness and recognition of the weaknesses that have infiltrated the biomedical research peer-review system, and it has been widely acknowledged that this system, under its current implementation, has its limitations.
In terms of journals, the number of signatories of the Transparency and Openness Promotion (TOP) guidelines, as of March 2019, was close to 5000, with an average increase of approximately 120 journals every month over the last three years.
Several impactful studies have detailed the reasons behind the current crisis (Begley and Ioannidis, 2015; Couchman, 2014; Drubin, 2015; Frye et al., 2015; Iorns and Chong, 2014) and identified a spectrum of causes, including inappropriate study design, lack of reagent validation, inadequate documentation of methods and datasets, and insufficient sharing of data and methods – essential for detailed analysis and replication.
Consequently, the replication crisis calls for significant improvements to current practices (McNutt, 2014) that are ultimately meant to restore confidence and facilitate the peer-review process. This implies that the data must be readily available in a comprehensive format that allows the rapid testing of new hypotheses, meaningful meta-analysis, and the development of robust methods. The following points constitute an excellent starting point (Freedman et al., 2017):
- Introduction of blinded analyses to mitigate subconscious biases;
- Repetition of experiments whenever possible;
- Validation of reagents (including cell lines and antibodies);
- Careful determination of appropriate data analysis procedures and statistical tests;
- Sharing of all results, including negative and positive controls.
Beyond experiments and reporting, adequate disclosure of potential conflicts of interest (COI), and proper credit to the researchers involved are two of the critical components of scientific transparency. Although often met with skepticism, we believe that sponsored research must always be properly identified.
There is no shortage of publications suggesting that industry funding increases the likelihood of pro-industry conclusions (Babor and Miller, 2014; Pisinger et al., 2019), and the genre has certainly been of help in identifying many publication biases and cases of misconduct in both industry and non-industry funded research (Allison and Cope, 2010; Boutron et al., 2010; Cope and Allison, 2010; Golder and Loke, 2008). However numerous, these publications do not grant industry-wide generalizations. In 2011, a study found that, over the last few decades, only 3.8% of all misconduct cases that led to the retraction of medical and scientific publications were associated with support from industry (Woolley et al., 2011). In a perspective article, Barton and colleagues reported that they could not find any data showing that financial conflicts of interest lead to a drop in scientific quality (Barton et al., 2014). In fact, on average, industry-funded clinical trials have been found to be qualitatively superior in their reporting and adherence to regulations when compared with non-industry funded clinical trials run by academic institutions (Del Parigi, 2012).
It is noteworthy to point out that scientific transparency is never a concluded process, and there will always be adjustments and more things we can do in order to facilitate innovation and cooperation. We are only at the beginning of an era of big data, high-throughput experiments, and massive parallel calculations, and our scientific tools are in the process of being reshaped for this new reality. Initiatives like INTERVALS spearhead this transformation and encourage transparent sharing of data to allow easy review and understanding, which will facilitate the objective evaluation of the evidence (Carlo et al., 1992).
Harm reduction and modified risk tobacco products ↑
Smoking is addictive and causes a number of serious diseases, such as cardiovascular disease, lung cancer, and chronic obstructive pulmonary disease (COPD).
Despite existing strategies to reduce smoking-related harm (i.e., preventing initiation and promoting cessation of smoking), it is estimated that more than one billion people worldwide will continue to smoke in the foreseeable future (Eriksen et al., 2015).
More recently, Tobacco Harm Reduction has emerged as an additional approach to address the health risks of smoking (World Health Organization, 2015; Zeller et al., 2009).
Tobacco Harm Reduction was defined by the U.S. Institute of Medicine (IOM) as “decreasing total morbidity and mortality, without the complete elimination of tobacco and nicotine use.” The IOM referred to “potentially reduced-exposure products (PREPs) as having reductions in exposure to one or more tobacco toxicants” (Institute of Medicine, 2001).
Tobacco Harm Reduction is based on encouraging smokers to switch to less harmful products that emit significantly lower levels of toxicants while providing levels of nicotine comparable to cigarettes. The U.S. Family Smoking Prevention and Tobacco Control Act embraces the concept of Tobacco Harm Reduction and defines a modified risk tobacco product (MRTP) as any tobacco product that is sold or distributed for use to reduce harm or the risk of tobacco-related disease associated with commercially marketed tobacco products (Food and Drug Administration (FDA), 2009).
Candidate MRTPs include products such as e-cigarettes and heat-not-burn products as well as other smokeless tobacco products.
Effective Tobacco Harm Reduction requires that a significant number of smokers adopt available MRTPs, meaning that MRTPs must be designed to minimize product risk while maximizing product acceptance by smokers. Therefore, an effective MRTP must meet two conditions:
- it must significantly reduce the risk of disease compared with cigarettes;
- it must be acceptable to smokers and encourage them to switch while neither appealing to non-smokers nor being perceived as an alternative to quitting (Institute of Medicine, 2001).
To address a range of consumer needs and thereby ensure the broadest possible adoption of reduced-risk alternatives, the industry is developing a portfolio of products, including heated tobacco products (i.e., heat-not-burn products), e-vapor products (i.e., e-cigarettes), oral tobacco, and nicotine products.
Evaluating candidate and potential MRTPs for their potential to significantly reduce smoking-related disease and death requires a robust, science-based assessment framework (Kozlowski and Abrams, 2016; Morven Dialogues, 2015), implemented by companies in the industry (Murphy et al., 2017; Smith et al., 2016).
As a result, numerous studies conducted with various candidate and potential MRTPs have been published by the companies that develop them.
Recently, several independent reports and studies reviewing the available science on heated tobacco and e-vapor products have been published:
- The UK Royal College of Physicians concluded in 2016 that “ the hazard to health arising from long-term vapor inhalation from the e-cigarettes available today is unlikely to exceed 5% of the harm from smoking tobacco” (Royal College of Physicians, 2016).
- In 2017, the British Medical Association published a position paper on e-cigarettes (British Medical Association, 2017) stating, “There are clear potential benefits to their use in reducing the substantial harms associated with smoking, and a growing consensus that they are significantly less harmful than tobacco use.”
- A review by Public Health England (McNeill et al., 2018) mentioning more than 32,000 e-cigarette and nicotine-containing e-liquid products that had been notified per the European Union Tobacco Products Directive concluded that“Widespread misperceptions about the relative risks of nicotine and tobacco need to be addressed and corrected,” and that “Vaping poses only a small fraction of the risks of smoking and switching completely from smoking to vaping conveys substantial health benefits over continued smoking. Based on current knowledge, stating that vaping is at least 95% less harmful than smoking remains a good way to communicate the large difference in relative risk unambiguously so that more smokers are encouraged to make the switch from smoking to vaping. It should be noted that this does not mean e-cigarettes are safe.” The review also mentions that “More research on nicotine in comparison to tobacco cigarette smoking is needed” and that “There is a need for more research that is independent of commercial interests” for heated tobacco products.
- Similarly, a review entitled “Public health consequences of e-cigarettes” was published by the National Academies of Sciences, Engineering, and Medicine, a U.S.-based organization of leading researchers (National Academies of Sciences and Medicine, 2018). After analyzing the results of more than 800 peer-reviewed scientific studies, they concluded that “There is conclusive evidence that completely substituting e-cigarettes for combustible tobacco cigarettes reduces users’ exposure to numerous toxicants and carcinogens present in combustible tobacco cigarettes.” However, they also point out the lack of long-term data from repeated inhalation exposures.
In our view, while evidence regarding the harm reduction potential of candidate MRTPs has accumulated rapidly in the scientific literature, it is essential to share the scientific basis of product assessment and the available methods as well as the data and results of assessment studies to enable their independent review and analysis.
Toxicological assessment in the 21st century ↑
The quantitative assessment of the risk reduction potential of candidate and potential MRTPs involves (i) the use and/or development of state-of-the-art methods in regulatory and systems toxicology, (ii) a deep knowledge of the mechanisms that lead to smoking-related diseases, and (iii) expertise in the design and conduct of clinical studies aimed at substantiating reduced exposure and risk in adult smokers.
Toxicity testing is at a turning point now that long-range strategic planning is in progress to update and improve testing procedures for potential stressors. The U.S. Environmental Protection Agency (EPA) commissioned the U.S. National Research Council (NRC) to develop a vision for toxicity testing in the 21st century (Committee on Toxicity Testing and Assessment of Environmental Agents, 2007; Krewski et al., 2010; Thomas et al., 2013) to base the new toxicology primarily on Pathways of Toxicity (PoT) (Basketter et al., 2012). The report by the NRC envisions a shift away from traditional toxicity testing and toward a focused effort to explore and understand the signaling pathways perturbed by biologically active substances or their metabolites that have the potential to cause adverse health effects in humans.
This understanding should allow researchers to:
- Achieve testing of broad coverage of chemicals, mixtures, outcomes, and life stages.
- Significantly increase human relevance.
- Reduce the cost and time required to conduct chemical safety assessments.
- Reduce and potentially eliminate high-dose animal testing.
Systems toxicology (Sturla et al., 2014), or 21st century toxicology (Hartung, 2010), aims to create a detailed understanding of the mechanisms by which biological systems respond to toxicants so that this understanding can be leveraged to assess the potential risk associated with chemicals, drugs, and consumer products. For example, to determine whether a candidate MRTP has the potential to reduce disease risk, its biological impact is compared with that of a reference cigarette (e.g., 3R4F cigarette) on a mechanism-by-mechanism basis.
The identification of pathways of toxicity is imperative in order to understand the mode of action of a given stimulus and to group together different stimuli based on the toxicity pathways they perturb. The first component of the vision focuses on pathway identification , which is preferably derived from studies performed in human cells or cell lines using omics assays. The second component of the vision involves targeted testing of the identified pathways in whole animals and clinical samples to further explain toxicity pathway data. This two-component toxicity testing paradigm, combined with chemical characterization and dose-response extrapolation, delivers a much broader understanding of the potential toxicity associated with a biologically active substance. Systems biology plays an essential role in this paradigm, consolidating large amounts of information that can be probed to reveal key cellular pathways perturbed by various stimuli (Sturla et al., 2014). Of importance, moving to mechanism-based assessment comes with its own challenges and requires new ways to assess literature data (Health and Services, 2014; Smith et al., 2016).
Importantly, omics technologies used to characterize the effect of different exposures molecularly also allow detailed descriptions of what each individual is exposed to (i.e., the exposome). For example, the EXPOsOMICS consortium (Vineis et al., 2017) aims at characterizing the external and internal exposome in relation to air pollution and water contaminants (Turner et al., 2018). Methods developed in this field are relevant to Tobacco Harm Reduction science, and vice versa, so a conversation between the relevant stakeholders through community platforms, such as INTERVALS, is highly relevant.
Furthermore, 21st century toxicology has identified the promise of new technologies and the need for large-scale efforts. Aligned with the 3Rs strategy — which states that animal use in scientific research should be reduced, refined, and replaced — in vitro studies using relevant test systems and systems biology approaches offer new prospects in the field of human toxicology (Daneshian et al., 2011). It is important that synergies are established between different laboratories to ensure that the best possible methods are developed and validated for regulatory consideration.
Relevance of animal models for product assessment ↑
In drug development and toxicological risk assessment, compound testing usually starts with in vitro experiments and is followed by in vivo testing using rodents as a mammalian model. This practice assumes that animal models respond to active substances through similar mechanisms. Recent inconsistencies in translating findings from animal models to human clinical outcomes (Knight, 2011), as well as animal welfare concerns, have led to the development of increasingly more sophisticated in vitro systems mimicking even the most complex tissue structures (Iskandar et al., 2017; Zanetti et al., 2016).
In vitro models capture events efficiently at molecular, cellular, and, at best, tissue levels and can be used to study transport rates across epithelia, toxicity, and mechanism of action (Fernandes and Vanbever, 2009). However, the fourth level of biological organization, which includes the physiological functions of an organism, can so far only be mimicked in the whole animal (Barré-Sinoussi and Montagutelli, 2015; Choy et al., 2016).
In addition to physiology, the organ of a living animal has advantages over in vitro models, especially in a disease context. For example, no in vitro model can adequately mimic COPD, an important adverse outcome caused by cigarette smoking. The complex pathogenesis of COPD includes inflammatory cell infiltration, goblet cell hyperplasia, cilia dysfunction, squamous cell metaplasia, and emphysema of the lung (Adamson et al., 2011). While ciliary dysfunction, mediator release, and goblet cell hyperplasia can be achieved in an in vitro setting, the C57BL6 mouse model comes much closer to mimicking the structural tissue alterations characteristic of emphysema (Sasaki et al., 2015). The role of the immune system, inflammatory cell infiltration into the lung, and lung function as a whole can also be better addressed in an animal model (Fricker et al., 2014). The C57BL/6 model is also suitable for testing aerosols generated by e-vapor and heat-not-burn products (Ansari et al., 2016; Phillips et al., 2015).
Therefore, despite criticism, animal models continue to serve an important role in human disease research and toxicological assessment (Denayer et al., 2014; Simmons, 2008; Vandamme, 2014).
However, considering the genetic differences between species, it is crucial to gain a detailed understanding of the similarities and differences between the experimental test system and the human disease or mechanism(s) that it is intended to model.
Inter-species comparisons conducted solely at the molecular level are generally inadequate because not all genes/proteins are conserved between species (Lin et al., 2014). Cross-species analysis of co-regulated genes can detect evolutionary conservation and provide functional information beyond sequence alignment (Berg and Lässig, 2006; Djordjevic et al., 2016; Rhrissorrakrai et al., 2015).
Hence, the mechanism-level conservation between species becomes more important than gene-level conservations. Importantly, mechanism-level comparisons will enable the identification of so-called “translational biomarkers”, which are representative of the behavior of key mechanisms. Equally important, the identification of the dissimilarity in disease pathways between species can highlight the value and limitations of a given model (Miller et al., 2010). The co-expression analyses can be conducted using an in vitro setting to establish convergence and divergence in cellular processes that contribute to specific pathologies in humans and animal models (Mueller et al., 2017; Rhrissorrakrai et al., 2015). This way, the in vitro research serves as the “adapter” between rodents and humans.
- Adamson, J. et al. In vitro models of chronic obstructive pulmonary disease (COPD). Bronchitis (2011).
- Allison, D.B., Cope, M.B. Randomized Controlled Trials With Statistically Nonsignificant Results. JAMA 304 (9), 965–965 (2010).
- Ansari, S. et al. Comprehensive systems biology analysis of a 7-month cigarette smoke inhalation study in C57BL/6 mice. Sci Data 3, 150077 (2016).
- Babor, T.F., Miller, P.G. McCarthyism, conflict of interest and Addiction’s new transparency declaration procedures. Addiction 109 (3), 341–344 (2014).
- Barré-Sinoussi, F., Montagutelli, X. Animal models are essential to biological research: issues and perspectives. Future Sci. OA 1 (4) (2015).
- Barton, D. et al. After 20 years, industry critics bury skeptics, despite empirical vacuum. Int. J. Clin. Pract. 68 (6), 666–673 (2014).
- Basketter, D.A. et al. A roadmap for the development of alternative (non-animal) methods for systemic toxicity testing - t4 report*. ALTEX 29 (1), 3–91 (2012).
- Bauchner, H., Fontanarosa, P.B. Restoring confidence in the pharmaceutical industry. JAMA 309 (6), 607–9 (2013).
- Begley, C.G., Ioannidis, J.P. Reproducibility in science: improving the standard for basic and preclinical research. Circ Res 116 (1), 116–26 (2015).
- Berg, J., Lässig, M. Cross-species analysis of biological networks by Bayesian alignment. Proc. Natl. Acad. Sci. 103 (29), 10967–10972 (2006).
- Boue, S. et al. Supporting evidence-based analysis for modified risk tobacco products through a toxicology data-sharing infrastructure. F1000Res 6, 12 (2017).
- Boue, S. et al. Embracing Transparency Through Data Sharing. Int J Toxicol 1091581818803880 (2018).
- Boutron, I. et al. Reporting and Interpretation of Randomized Controlled Trials With Statistically Nonsignificant Results for Primary Outcomes. JAMA 303 (20), 2058–2064 (2010).
- British Medical Association. E-cigarettes: Balancing risks and opportunities. (2017).
- Carlo, G.L. et al. The interplay of science, values, and experiences among scientists asked to evaluate the hazards of dioxin, radon, and environmental tobacco smoke. Risk Anal 12 (1), 37–43 (1992).
- Choy, L. et al. Cardiac disease and arrhythmogenesis: mechanistic insights from mouse models. IJC Heart Vasc. 12, 1–10 (2016).
- Committee on Toxicity Testing and Assessment of Environmental Agents, N.R.C. Toxicity testing in the 21st century: A vision and a strategy. (2007).
- Cope, M.B., Allison, D.B. White hat bias: examples of its presence in obesity research and a call for renewed commitment to faithfulness in research reporting. Int. J. Obes. 34 (1), 84–88 (2010).
- Couchman, J.R. Peer review and reproducibility. Crisis or time for course correction?. J Histochem Cytochem 62 (1), 9–10 (2014).
- Daneshian, M. et al. A framework program for the teaching of alternative methods (replacement, reduction, refinement) to animal experimentation. ALTEX 28 (4), 341–52 (2011).
- Del Parigi, A. Industry funded clinical trials: bias and quality. Curr Med Res Opin 28 (1), 23–5 (2012).
- Denayer, T. et al. Animal models in translational medicine: Validation and prediction. New Horiz. Transl. Med. 2 (1), 5–11 (2014).
- Djordjevic, D. et al. XGSA: A statistical method for cross-species gene set analysis. Bioinformatics 32 (17), i620–i628 (2016).
- Drubin, D.G. Great science inspires us to tackle the issue of data reproducibility. Mol Biol Cell 26 (21), 3679–80 (2015).
- Eriksen, M. et al. The Tobacco Atlas 5th Edition (http://www.tobaccoatlas.org/). Am. Cancer Soc. (2015).
- Fernandes, C.A., Vanbever, R. Preclinical models for pulmonary drug delivery. Expert Opin. Drug Deliv. 6 (11), 1231–1245 (2009).
- Food and Drug Administration (FDA). Family Smoking Prevention And Tobacco Control Act. Public Law 111-31 Section 911(b)(1), 21 U.S.C 387 k (2009).
- Freedman, L.P. et al. Reproducibility2020: Progress and priorities. F1000Res 6, 604 (2017).
- Fricker, M. et al. Animal models of chronic obstructive pulmonary disease. Expert Opin. Drug Discov. 9 (6), 629–645 (2014).
- Frye, S.V. et al. Tackling reproducibility in academic preclinical drug discovery. Nat Rev Drug Discov 14 (11), 733–4 (2015).
- Golder, S., Loke, Y.K. Is there evidence for biased reporting of published adverse effects data in pharmaceutical industry-funded studies?. Br. J. Clin. Pharmacol. 66 (6), 767–773 (2008).
- Hartung, T. Lessons learned from alternative methods and their validation for a new toxicology in the 21st century. J Toxicol Env. Health B Crit Rev 13 (2–4), 277–90 (2010).
- Health, U.D. of, Services, H. The health consequences of smoking—50 years of progress: a report of the Surgeon General. Atlanta GA US Dep. Health Hum. Serv. Cent. Dis. Control Prev. Natl. Cent. Chronic Dis. Prev. Health Promot. Off. Smok. Health 17 (2014).
- Hoeng, J. et al. A network-based approach to quantifying the impact of biologically active substances. Drug Discov Today 17 (9–10), 413–8 (2012).
- Institute of Medicine. Clearing the smoke: assessing the science base for tobacco harm reduction. (2001).
- Iorns, E., Chong, C. New forms of checks and balances are needed to improve research integrity. F1000Res 3, 119 (2014).
- Iskandar, A. et al. Systems toxicology meta-analysis of in vitro assessment studies: biological impact of a candidate modified-risk tobacco product aerosol compared with cigarette smoke on human organotypic cultures of the aerodigestive tract. Toxicol Res 6, 631–653 (2017).
- Knight, D. Weighing the Costs and Benefits of Animal Experiments. ALTEX Proceedings of WC8 (2011).
- Kozlowski, L.T., Abrams, D.B. Obsolete tobacco control themes can be hazardous to public health: the need for updating views on absolute product risks and harm reduction. BMC Public Health 16, 432 (2016).
- Krewski, D. et al. Toxicity testing in the 21st century: a vision and a strategy. J. Toxicol. Environ. Health Part B 13 (2–4), 51–138 (2010).
- Lin, S. et al. Comparison of the transcriptional landscapes between human and mouse tissues. Proc. Natl. Acad. Sci. 111 (48), 17224–17229 (2014).
- McNeill, A. et al. Evidence review of e-cigarettes and heated tobacco products 2018. Rep. Comm. Public Health Engl. Lond. Public Health Engl. 6 (2018).
- McNutt, M. Journals unite for reproducibility. Science 346 (6210), 679 (2014).
- Miller, J.A. et al. Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways. Proc. Natl. Acad. Sci. 107 (28), 12698–12703 (2010).
- Morven Dialogues. Core Principles Concerning the Implementation of Effective and Workable Tobacco, Nicotine, and Alternative Products Policies for Reducing Disease and Death from Tobacco Use. (2015).
- Mueller, A.J. et al. Cross-species gene modules emerge from a systems biology approach to osteoarthritis. NPJ Syst. Biol. Appl. 3 (1), 13 (2017).
- Murphy, J. et al. Assessing modified risk tobacco and nicotine products: Description of the scientific framework and assessment of a closed modular electronic cigarette. Regul. Toxicol. Pharmacol. RTP 90, 342–357 (2017).
- National Academies of Sciences, E., Medicine. Public health consequences of e-cigarettes. (2018).
- Phillips, B. et al. A 7-month cigarette smoke inhalation study in C57BL/6 mice demonstrates reduced lung inflammation and emphysema following smoking cessation or aerosol exposure from a prototypic modified risk tobacco product. Food Chem Toxicol 80, 328–45 (2015).
- Pisinger, C. et al. A conflict of interest is strongly associated with tobacco industry-favourable results, indicating no harm of e-cigarettes. Prev. Med. 119, 124–131 (2019).
- 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 (4), 471–83 (2015).
- Royal College of Physicians. Nicotine without smoke—tobacco harm reduction. (2016).
- Sasaki, M. et al. Evaluation of cigarette smoke-induced emphysema in mice using quantitative micro-computed tomography. Am. J. Physiol.-Lung Cell. Mol. Physiol. 308 (10), L1039–L1045 (2015).
- Simmons, D. The use of animal models in studying genetic disease: transgenesis and induced mutation. Nat. Educ. 1 (1), 70 (2008).
- Smith, M.R. et al. Evaluation of the Tobacco Heating System 2.2. Part 1: Description of the system and the scientific assessment program. Regul. Toxicol. Pharmacol. RTP 81 Suppl 2, S17–S26 (2016).
- Sturla, S.J. et al. Systems toxicology: from basic research to risk assessment. Chem. Res. Toxicol. 27 (3), 314–329 (2014).
- Thomas, R.S. et al. Incorporating new technologies into toxicity testing and risk assessment: moving from 21st century vision to a data-driven framework. Toxicol Sci 136 (1), 4–18 (2013).
- Turner, M.C. et al. EXPOsOMICS: final policy workshop and stakeholder consultation. BMC Public Health 18 (1), 260 (2018).
- Vandamme, T.F. Use of rodents as models of human diseases. J. Pharm. Bioallied Sci. 6 (1), 2 (2014).
- Vineis, P. et al. The exposome in practice: Design of the EXPOsOMICS project. Int J Hyg Env. Health 220 (2 Pt A), 142–151 (2017).
- Woolley, K.L. et al. Lack of involvement of medical writers and the pharmaceutical industry in publications retracted for misconduct: a systematic, controlled, retrospective study. Curr. Med. Res. Opin. 27 (6), 1175–1182 (2011).
- World Health Organization. WHO study group on tobacco product regulation: report on the scientific basis of tobacco product regulation: fifth report of a WHO study group. (2015).
- Zanetti, F. et al. Systems toxicology assessment of the biological impact of a candidate modified risk tobacco product on human organotypic oral epithelial cultures. Chem. Res. Toxicol. 29 (8), 1252–1269 (2016).
- Zeller, M. et al. The Strategic Dialogue on Tobacco Harm Reduction: a vision and blueprint for action in the US. Tob Control 18 (4), 324–32 (2009).