Utility of biomarkers of potential harm for the assessment of novel tobacco and nicotine products.

Biomarkers of potential harm are measurable events in the body, which either are a part of, or a surrogate measure for, the extent of underlying disease development.  In the absence of long term epidemiological data, biomarkers offer a pragmatic alternative to estimate the harm reduction potential of novel tobacco and nicotine products.  Although a large number of biomarkers exist, their practical utility in the regulatory context needs to be carefully considered. The aim of the workshop was to open the discussion among medical experts, public health organisations and other stakeholders on how best to identify suitable biomarkers and implement their use.

“Being invited to contribute to this workshop as an expert scientist is testament to the strength of our scientific programme and our team of biomarker scientists,” says Dr Chris Proctor, BAT’s Chief Scientific Officer. “Having a seat at the table helps shape the near future where regulators will be asked to determine whether next-generation products are  reduced-risk products.”

To help discern the relationship between tobacco smoke-induced early biological responses and a disease outcome, a better understanding of the cause/effect relationship in the underlying biology is needed.

To this end, BAT proposes an integrated Adverse Outcome Pathway (AOP) approach, which incorporates pre-clinical, clinical and population data to assess the risk-reduction potential of novel products at the molecular, cellular, individual and population level. Both in vitro endpoints and clinical biomarkers are embedded within this framework to describe the impact of tobacco smoke exposure from early effects to known disease-related changes.  Novel products may then be compared using the same endpoints/biomarkers.

Using a variety of in vitro tests, we recently found that exposure to aerosols from BAT’s Vype ePen (an e-cigarette) resulted in large reductions in adverse responses in both toxicological tests (mutagenic, cytotoxic and genotoxic) and a variety of assays that mimic disease-relevant key events, when compared with tobacco smoke exposure1. Similarly, transcriptomic and gene-enrichment analyses have shown that repeated short-term exposure to conventional cigarette smoke results in gene expression changes that are associated with cellular stress, inflammation and tissue remodelling.  In contrast, Vype ePen aerosols did not induce these changes, and were comparable to untreated controls2. Additionally, by comparing the metabolome, lipidome and proteome of smokers and non-smokers, we have identified a number of targets which significantly differ between the two groups, and hence these could serve as candidate biomarkers of potential harm3, 4.

AOPs could lay the foundations for a bridging approach, according to Proctor. This would involve building a complete data set on the first generation of novel product type to confirm any risk-reduction potential and then identifying a reduced number of key studies that would be performed on similar products. This could potentially minimise the need for costly clinical studies and exhaustive biological testing, given that the underlying biology is well understood in an approved AOP.  This will enable the development of efficient, intelligent testing strategies, and reduce the burden on regulators.

Dr Proctor's presentation at the FDA Workshop can be viewed here .

1. Lowe et al. The assessment of a range of next generation tobacco and nicotine products using pre-clinical in vitro tools .  SRNT 2016, POS5-117
2. Banerjee et al. Differential Gene Expression Using RNA-seq Profiling in a Reconstituted Airway Epithelium, Mucilair™, Exposed to Conventional or Electronic Cigarettes Aerosols . SOT 2016, Abstract 3037, P179
3. Kaluarachchi et al. A Multiplatform Metabolic Phenotyping Approach Integrated with Pathway Mapping to Identify Biochemical Differences Between Healthy Smokers and Non-smokers. SOT 2016, Abstract 1107 – P136,
4. Garcia-Perez et al. Bioanalysis 2014, 6: 2733-2749

NOTES TO EDITORS

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