Chemical analysis in the regulation of tobacco products
Chris Wright PhD, Derek Mariner PhD, Mark Williams MBA & Chris Proctor PhD
British American Tobacco Group Research & Development, Southampton UK
68th Tobacco Science Research Conference, Charlottesville VA, 28 Sept – 1 Oct 2014
1 Overview
1. Tobacco product regulation 2. Regional requirements and substances of interest 3. Tobacco product emissions 4. Regional trends for selected HPHCs in smoke 5. Evaluating method performance 6. Ruggedness and how to achieve it 7. Demonstrating continuing improvement 8. Opportunities for shared learning
2 Abbreviated list of HPHCs in Cigarette Smoke Acetaldehyde Acrolein Acrylonitrile 4-Aminobiphenyl 2-Aminonaphthalene Ammonia Benzene Benzo[a]pyrene 1,3-Butadiene Carbon monoxide Crotonaldehyde Formaldehyde Isoprene Nicotine NNK NNN Toluene
Abbreviated list of HPHCs in Smokeless Tobacco
Acetaldehyde Arsenic Benzo[a]pyrene Cadmium Crotonaldehyde Formaldehyde Nicotine NNK NNN 2. Classes of constituents – FDA TPSAC April 2012
Trace metals Alkenes / Aromatic amines Aromatics Arsenic cyanoalkanes 4-Aminobiphenyl Benzene Carbonyls Beryllium 1,3-Butadiene 1-Aminonaphthalene Ethylbenzene Acetaldehyde Cadmium Isoprene 2-Aminonaphthalene Toluene Acetone Chromium Hydrogen cyanide o-Anisidine Caffeic acid Acrolein Cobalt Nitromethane 2,6-Dimethylaniline Catechol Crotonaldehyde Formaldehyde Lead Others o-Toluidine o-, m-, p-cresol Mercury Phenol Methyl ethyl ketone Aflatoxin B1 Nickel Propionaldehyde Coumarin Polonium-210 Nitrobenzene Selenium 2-Nitropropane Heterocycles Uranium-235 Carbon monoxide Quinoline Uranium-238 Chlorinated dioxins / Styrene furans Polycyclic Aromatics Alkaloids Heterocyclic aromatic amines α Benz[a]anthracene Anabasine A- -C (2-Amino-9H-pyrido[2,3-b]indole) Benz[j]aceanthrylene Nicotine Glu-P-1 (2-Amino-6-methyldipyrido[1,2- Benzo[b]fluoranthene Nornicotine a:3',2'-d]imidazole) Benzo[k]fluoranthene Glu-P-2 (2-Aminodipyrido[1,2-a:3',2'- Benzo[b]furan Low MW d]imidazole) CA Benzo[a]pyrene volatiles IQ (2-Amino-3-methylimidazo[4,5- Benzo[c]phenanthrene Acetamide N-nitrosamines f]quinoline) Chrysene Acrylamide 4-(Methylnitrosamino)-1-(3-pyridyl)-1- MeA-α-C (2-Amino-3-methyl)-9H- Cyclopenta[c,d]pyrene Acrylonitrile butanone pyrido[2,3-b]indole) Dibenz[a,h]anthracene Ammonia N-Nitrosodiethanolamine (NDELA) PhIP (2-Amino-1-methyl-6- Dibenzo[a,e]pyrene Ethyl carbamate N-Nitrosodiethylamine phenylimidazo[4,5-b]pyridine) Dibenzo[a,h]pyrene (urethane) N-Nitrosodimethylamine (NDMA) Trp-P-1 (3-Amino-1,4-dimethyl-5H- Dibenzo[a,i]pyrene Ethylene oxide N-Nitrosomethylethylamine pyrido[4,3-b]indole) Dibenzo[a,l]pyrene Furan N-Nitrosomorpholine (NMOR) Trp-P-2 (1-Methyl-3-amino-5H- Indeno[1,2,3-cd]pyrene Hydrazine N-Nitrosonornicotine (NNN) pyrido[4,3-b]indole ) 5-Methylchrysene Propylene oxide N-Nitrosopiperidine (NPIP) Naphthalene Vinyl acetate N-Nitrosopyrrolidine (NPYR) Vinyl chloride N-Nitrososarcosine (NSAR) 3. Constituents of emissions from novel tobacco products
Substances associated with alternative nicotine / tobacco product emissions
3R4F MS smoke (whole)
Disposable E-cigarette aerosol
Heated Tobacco aerosol Single puff from each product analysed using thermal desorption, capillary gas chromatography, TOF MS 5 3. Emissions from Electronic Cigarettes
Electronic cigarette aerosols contain very low levels of most HPHCs
Substances other than HPHCs may be present in e-cigarette aerosol, depending upon the e-liquid and device. But are they present at levels significant to health?
1,3-Dioxan-5-ol cis-Aconitic anhydride Maleic anhydride 1-Cyanovinyl acetate Citraconic anhydride Malic acid 4-Methylbenzophenone Citric acid Menthane (p-menthane) Abieta-8,11,13-trien-18 -oic acid Decanedioic acid, bis (2-ethylhexyl) ester Menthol (dehydroabietic acid) Ethanol Menthone Acetaldehyde Ethyl acetate Methyl 2-benzoylbenzoate Acetic acid Formaldehyde Methyl Acetate Acetic anhydride Glycerol Methylglyoxal Acrolein Glycidol Methyl Vinyl Ketone β-nicotyrine Glyoxal Nicotine Benzene Hexadecanoic acid Octadecanoic acid (stearic acid) Benzo[a]pyrene (palmitic acid) Phenol Bisphenol A Isoprene Propanoic acid Butyraldehyde Itaconic anhydride Toluene
Red = HPHC reported in e-cigarette aerosol 6 3. 3R4F smoke vs E-cigarette aerosol
HCI, comparison of selected constituents, scaled by consumption (14 cigarettes vs 300 puffs)
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7 3. Emissions from tobacco heating products
Heated tobacco emissions are different to cigarette smoke
Tobacco heating product emissions contain lower levels of HPHCs than cigarette smoke. They also contain other substances (as does cigarette smoke).
1,3-Butadiene Butyraldehyde Nitric Oxide 1-aminonaphthalene Carbon monoxide NNK 2-Aminonaphthalene Catechol NNN 3-Aminobiphenyl Crotonaldehyde o-Cresol 4-Aminobiphenyl Formaldehyde m+p-Cresol Acetaldehyde Hydrogen Cyanide Phenol Acetone Hydroquinone Propionaldehyde Acrolein Isoprene Pyridine Acrylonitrile Methyl ethyl ketone Quinoline Ammonia NAB Resorcinol Benzene NAT Styrene Benzo[a]pyrene Nicotine Toluene
Red = detected in heated tobacco aerosol Grey = awaiting data 8 3. 3R4F smoke vs heated tobacco aerosol vs E-cigarette vapour
HCI comparison of selected constituents per cig / consumable / 10 puffs
400.0
350.0
300.0
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200.0 3R4F 150.0 HnB E-Cig 100.0
50.0
0.0
9 4. Regional trends in selected smoke constituents
How similar are distributions in different regions?
Product testing results can be presented and interpreted in different ways. Data must be fit for intended use, and this is influenced by analytical sensitivity, accuracy and precision, especially if data are provided by multiple laboratories
The following slides present ‘snapshot data’ for BaP, NNN and 1,3-Butadiene in mainstream smoke from commercial products in different regional markets
Do different regions have similar ranges of concentration? Would common ‘global’ methods be applicable?
10 4. N-nitrosonornicotine in mainstream smoke, HCI
600 Market A 600 Market B 500 500
400 400
300 300 NNN(ng/cig) 200 NNN(ng/cig) 200
100 100
0 0 Product Index Product Index 600 Market C 600 Market D 500 500
400 400
300 300
NNN(ng/cig) 200 NNN(ng/cig) 200
100 100
0 0 Product Index Product Index Graphs show: Mean Min Max, of replicate measurements by product and median Data provided by Alison Eldridge, BAT Group Research & Development. 11 4. 1,3-Butadiene in mainstream smoke, HCI
160 Market A 160 Market B 140 140
120 120
100 100
80 80
60 60 1,3-Butadiene (µg/cig) 1,3-Butadiene (µg/cig) 40 40
20 20 Product Index Product Index
160 Market C 160 Market D 140 140
120 120
100 100
80 80
60 60 1,3-Butadiene (µg/cig) 1,3-Butadiene (µg/cig) 40 40
20 20 Product Index Product Index Graphs show: Mean Min Max, of replicate measurements by product and median Data provided by Alison Eldridge, BAT Group Research & Development. 12 4. Benzo[a]pyrene in mainstream smoke, HCI
50 50 Market A Market B 40 40
30 30
20 20 B[a]P (ng/cig) B[a]P (ng/cig)
10 10
0 0 Product Index Product Index
50 50 Market C Market D 40 40
30 30
20 20 B[a]P (ng/cig) B[a]P (ng/cig)
10 10
0 0 Product Index Product Index Graphs show: Mean Min Max, of replicate measurements by product and median Data provided by Alison Eldridge, BAT Group Research & Development. 13 4. Method stability 1,3-Butadiene
Laboratory Control Cigarette, 3R4F
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140
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60 1,3-Butadiene (µg/cig) 1,3-Butadiene
40
20 AUG10 SEP10 OCT10 NOV10 DEC10 JAN11 FEB11 MAR11 APR11 MAY11 Month
14 4. Method stability Benzo[a]pyrene
Laboratory Control Cigarette, 3R4F
50
40
30
20 B[a]P (ng/cig)B[a]P
10
0 AUG10 SEP10 OCT10 NOV10 DEC10 JAN11 FEB11 MAR11 APR11 MAY11 Month
15 5. Evaluating method performance
Specifying method performance requirements
Market Toxicant Units N Mean StdDev Min P25 Median P75 Max
A 1,3-Butadiene µg/cig 925 106.9 14.2 63.3 97.4 107.3 116.4 147.3
A B[a]P ng/cig 925 18.0 4.6 8.2 14.8 17.7 20.7 43.2
A NNN ng/cig 925 68.0 56.8 0.0 31.2 51.2 79.4 376.5
B 1,3-Butadiene µg/cig 695 70.8 16.2 31.4 60.3 68.1 79.3 126.3
B B[a]P ng/cig 700 18.6 4.9 7.1 15.2 18.1 21.3 42.2
B NNN ng/cig 700 139.1 52.4 31.0 104.0 135.5 163.0 423.0
C 1,3-Butadiene µg/cig 840 97.1 15.9 50.0 88.4 99.1 108.0 140.9
C B[a]P ng/cig 840 20.2 5.4 10.4 16.2 19.4 23.7 38.5
C NNN ng/cig 840 142.5 69.5 12.6 101.5 132.8 173.0 477.7
D 1,3-Butadiene µg/cig 700 98.8 20.5 51.8 83.1 101.3 112.9 156.5
D B[a]P ng/cig 700 13.1 3.9 5.1 10.4 12.7 15.3 30.3
D NNN ng/cig 700 150.4 78.1 33.2 102.9 133.4 174.4 515.2
16 5. Method performance requirement – 1,3-butadiene
160 Market B
140
120
100
80 75 th percentile
1,3-Butadiene (µg/cig) Market B median 60
40
Product Index 20 To exclude with 95% confidence all products above the 75 th percentile would require a method reproducibility SD (sR) ≤ 3.99µg/cig
Method reproducibility limit = (79.3 – 68.1) µg/cig; [1.96 √2.sR] = 11.2µg/cig; sR = 3.99µg/cig; 17 5. Performance of current methods CORESTA Recommended Method No 70 Determination of selected volatile organic compounds in mainstream cigarette smoke by GC-MS, July 2014
For a 10mg delivery product under HCI conditions, sR = 10.78µg/cig
Method reproducibility does not support the desired level of discrimination.
Mean = 73.77µg/cig; R = 30.27µg/cig; sR = 10.78µg/cig 5. Method performance requirement – NNN
600 Market D
500
400
300 NNN(ng/cig)
200 75 th percentile Market D median 100
0 Product Index
To exclude with 95% confidence all products above the 75 th percentile would require sR ≤ 14.60ng/cig.
R = 41ng/cig; [1.96 √2sR] = 41ng/cig; sR = 14.60ng/cig 19 5. Performance of current methods
CORESTA Recommended Method No 75 Determination of tobacco-specific nitrosamines in mainstream cigarette smoke by LC-MS/MS, July 2014
sR = 12.7ng/cig : Reproducibility supports the desired level of discrimination.
If a decision is based upon a ratio (e.g. analyte/nicotine), the reproducibility of measurement of nicotine must also be considered. Sample 2 Mean = 87.5ng/cig; R = 35.9ng/cig; sR = 12.7ng/cig 6. Rugged test methods
What makes a method able to tolerate minor changes without impacting performance?
Measurement by ratio – use a suitable internal standard (IS) If low signal/noise, increase the selectivity of measurement - improve chromatographic separation; - use a more selective detection technique ( e.g. MS, MS/MS) - remove matrix artefacts (cleanup). For mass selective detection, use stable isotope dilution. Consider the number of unique ions required to assure adequate confidence in chemical identity Apply system suitability criteria for selectivity and signal/noise Consider technical guidance and data acceptance criteria applied to similar methods in other regulated industries
21 7. Demonstrating continuing improvement
Interlaboratory studies can meet different needs Method performance studies, such as those conducted by CORESTA, enumerate the precision of measurement. In the absence of Certified Reference Materials, it is difficult to assess accuracy of measurement
Proficiency studies conducted in accordance with ISO/IEC 17043 and ISO 13528 evaluate the performance of participating laboratories against pre- established criteria by means of interlaboratory comparison. These include quantitative schemes for the measurement of constituents in test items. 22 7. Proficiency studies Can facilitate improved agreement of results For example, by applying a target standard deviation based on fitness for purpose and by collating information on methods to share best practice.
2007-2008 Annual Asia Collaborative Study on ISO Tar & Nicotine
23 7. Predicting achievable performance
The Horwitz function
Target Reproducibility [ RSD R ] can be calculated from the Horwitz function. The Horwitz function is based upon observations (drawn from thousands of collaborative studies) of the relationship between analyte concentration and reproducibility.
-0.1505 PRSD R (%) = 2 C
HorRat = RSD R/PRSD R
Reproduced from AMC technical Brief 17, Royal Society of Chemistry 2004. 24 8. Opportunities for shared learning
Best technical practice, internal and external quality assurance
Proficiency studies - represent full range of product variation in the population to be tested; - apply standards consistent with best practice ( e.g. target SD); - address substances of technical priority ( e.g. of regulatory interest); - collate information on methods used ( e.g. preparation, instrumental technique); - operate regular cycles or rounds and provide accessible reports; - generate commercial quality control samples; - provide material to be used for learning, e.g. in technical workshops
Reference Materials - require the use of definitive analytical methods to derive reference values - homogeneity, long-term stability, continuous availability - can generate certified values for additional constituents over time - may be solutions ( e.g. smoke condensate) as well as tobacco products
25 Thank you for your attention
Questions?
www.bat-science.com 4. Mainstream Cigarette Smoke Constituents
4 regional markets were sampled and representative products tested • Market A – Mixed Blend, low incidence of charcoal in filter, Sampled Q1 2012 • Market B – Mixed Blend, High incidence of charcoal in filter, Sampled Q4 2012 • Market C – Predominantly FCV, Sampled Q1 2013 • Market D – Predominantly US-Blended, Sampled Q4 2013, largest market
Thanks to my colleague Alison Eldridge of BAT Group Research & Development. The data and a more complete discussion of their implications will be published during 2014 and beyond.
27 4. Summary Statistics (4 markets combined) Statistics for all replicates. Products tested under HCI conditions
Market Toxicant Units N Mean StdDev Min P25 Median P75 Max
A 1,3-Butadiene µg/cig 925 106.9 14.2 63.3 97.4 107.3 116.4 147.3
A B[a]P ng/cig 925 18.0 4.6 8.2 14.8 17.7 20.7 43.2
A NNN ng/cig 925 68.0 56.8 0.0 31.2 51.2 79.4 376.5
B 1,3-Butadiene µg/cig 695 70.8 16.2 31.4 60.3 68.1 79.3 126.3
B B[a]P ng/cig 700 18.6 4.9 7.1 15.2 18.1 21.3 42.2
B NNN ng/cig 700 139.1 52.4 31.0 104.0 135.5 163.0 423.0
C 1,3-Butadiene µg/cig 840 97.1 15.9 50.0 88.4 99.1 108.0 140.9
C B[a]P ng/cig 840 20.2 5.4 10.4 16.2 19.4 23.7 38.5
C NNN ng/cig 840 142.5 69.5 12.6 101.5 132.8 173.0 477.7
D 1,3-Butadiene µg/cig 700 98.8 20.5 51.8 83.1 101.3 112.9 156.5
D B[a]P ng/cig 700 13.1 3.9 5.1 10.4 12.7 15.3 30.3
D NNN ng/cig 700 150.4 78.1 33.2 102.9 133.4 174.4 515.2 Total number of Products tested = 3165, replicates of 5
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