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Demonstrating substantial EQUIVALENCEof a new cigarette to the existing portfolio
Federico Karagulian
Proposing the INTER-COMPARISON equivalence method (comparative analysis)
portfolio new cigarettes
Equivalence to cigarettes already marked Compliance with legislative requirements for new tobacco products
(USA, EU, Canada, etc.)
smoke chemistry studiesin vitro studies
toxicological studiesbiological studies
R. Dempsey et al..Regulatory Toxicology and Pharmacology 61 (2011) 119–128
componentschemicals
emissionseffects
PORTFOLIO VARIABLES and COMPONENTS
portfolio variables (Pj) with components (pji)and uncertainties (vji)
pj1 pj2 pj3 pj4 pjnpj5 ... ... ... ...Pj =
Portfolio products
vj1 vj2 vj3 vj4 vjnvj5 ... ... ... ...± Vj =
Uncertainty:- standard deviation of the variable- analytical uncertainty of the components
new variables (Yj) with new components (yji)and uncertainty (uji)
yj1 yj2 yj3 yj4 yjnyj5 ... ... ... ...Yj =
Y1 = y11 + y12 + ...................+ y1n
Y2 = y21 + y22 + ...................+ y2n
Different cigarettes with the same variables (Yj) must be compared with the portfolio variable (Pj)
New cigarette
uj1 uj2 uj3 uj4 ujnuj5 ... ... ... ...Uj =
NEW CIGARETTE VARIABLES and COMPONENTS
Example for smoke chemistry studies
Smoke = organic(a) + CO +...+ tar + nicotine + particle(a) +...+ gas(a)+...metals+..
P1 = p11 + p12 + p13 + ...................+ p1n
Example: VARIABLE smoke (P1), present in all portfolio products, with common chemical COMPONENTS (p1i)
How these COMPONENTS change in new cigarettes?How to evaluate this change?
toxicological impact?
correlation is made at components level (yji , pji )
Correlation
Portfolio variables (Pj)
New variables (Yj)
0.6
0.0
1.0
0.6
0.0
1.0
NOT OK OK
The criterion of R2 = 0.6 is used to establish if a variable is comparable to all the othervariables in the same portfolio category
INTER-COMPARISON methodology I: Pearson correlation (R2), p<0.0X
portfolio components
New
var
iab
les
com
pon
ents
R2 = 0.85
R2
max
Orthogonal regressionStatistical significance p<0.01
Weighted difference
Portfolio variables (Pj) and uncertainties (vji)
New variables (Yj)and uncertainties (uji)
INTER-COMPARISON methodology II: Weighted difference
n
1i2ji
2ji
jijiPY
vu
py1/nWD
jj
2.0
0.0
4.0
0.0 OK NOT OK
3.0
2.0
4.0
3.0
1.0 1.0
weighted comparison
Acceptability: from 0 to1
WD
uncertainties of the components are considered in comparative analysis more robust assessment compared to Pearson correlation
INTER-COMPARISON methodology III: Z-score method for new cigarettes’ perfomance
Defining the standard deviation for proficiency assessment p as criterion to evaluate new cigarettes’ performance (ISO 13528)(p = 50%,25%...)
new cigarettes are considered coherent and satisfactory if:
“OK”2z
3z2
new cigarettes are considered questionable if:
“Warning”
new cigarettes are unsatisfactory if:
3z “Action”
p
jj
σ
PYz
z-score
reference
* s1.5d
dyy *jji
dyy *jji
dyy *jij,
dyy *jij,
ij,ij, yy
if
if
otherwise
ji*i yMEDy
*jji
*j yy MED1.483s
n
1jj
*j yn1yR
Z-score method: new cigarettes’ perfomances
Define a new assigned reference value (R) among new variables (Yj) and portfolio variables (Pj)
R is generated by robust analysis iterative algorithm:
(Analytical Methods Committee 1989a, 1989)
jji Yp
time
Targeting a new cigarette
keep the natural tobacco taste
and flavorreduced burning zone
new ingredients(toxicological relevance)
reduced emissions
New
cig
aret
te
How targeting
these objectives??
Same smoking pleasureReduced risk for health
Road map for product innovation
Typical cigarette combustion(ingredients and emissions)
Cigarette + Air Smoke
aCO2 + bH2O + cN2 + dO2
Combustion in ideal conditions
Combustion in real conditions
e(CO) + f(organics) + h(ash) + i(inorganic gases) + j(tar) + k…
t6
EMISSIONS
INGREDIENTS
cigarette lifetime
t5t4t2t1Toxicological relationship
Toxicological relationship
EFFICIENCY of INGREDIENTS and EMISSIONS for targeting INNOVATIVE cigarettes
COMPONENTS EFFICIENCY (ingredients and emissions)
componentsi
cigarette lifetime (ti)
tobacco efficiency
aerosols efficiency
..... .....
efficiency
tobacco y11 / t1 y12 / t1 ...... y1i / ti
aerosols y21 / t2 y22 / t2 ...... ...
additives y31 / t3 y32 / t3 ...... ...
tar y41 / t4 y42 / t4 ...... ...
CO y51 / t5 y52 / t5 ...... ...
..... yj1 / tj yj2 / tj ...... yji / tj
=
How targeting INGREDIENT EFFICIENCY (IE) andEMISSION EFFICIENCY (EE) in order to reduce TOXICITY?
Efficiency
Targeting EFFICIENCY factors with Positive Matrix Factorization (PMF)
Minimization of residuals for
targeting IE and EE
lifetime IE EE
t1 g11 g12
t2 g21 g22
t3 g31 g32
... ... ...
profiles IE EE
tar f11 f12
aerosols f21 f22
CO f31 f32
nicotine f41 f42
tobacco f51 f52
additives f61 f61
... ... ...
ji
2
1kjkkiiji εgf/ty
lifetime componentsi efficiency
t1 y13 / t1
t2 y23 / t2
t3 y33 / t3
... ...
2n
1j
m
1i ji
ji
ff u
εminQ min
(Jiaying Wu et al. JEM, 2012)
source(experimental
input data)
receptor(data analysis)
factors
target ingredientsand emissions for
orienting efficiency toward desidered
outputs
Pulling components to simulate best EFFICIENCY factor with reduced TOXICITY
target oriented data
target oriented data
2EE
2EEEE
auxEE iii
/s)f(aQ
2IE
2IEEE
auxIE iii
/s)f(aQ
profile
profile
ing
red
ien
t ef
fici
ency
(IE
)
emission efficiency (EE)
ing
red
ien
t ef
fici
ency
(IE
)
emission efficiency (EE)
Constraining factors for targeting single components
IE + EE
EE
IE
With Positive Matrix Factorization is possible to “pull” Factors towards a desidered target
no pulling with pulling
mixed solutions separeted solutions
Overall EFFICIENCY for new cigarettes
feedback loop:take action on fundamental components
Discovery Validation EFFICIENCY(toxicological info)
totalefficiency
22 EE IE
Inter-comparison (comparative analysis) has been proposed as method to prove substantial equivalence with portfolio product
Positive Matrix Factorization can be used as statistical method for targeting EFFICIENCY in new cigarettes for toxicological studies
Conclusions