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Demonstrating substantial EQUIVALENCE of a new cigarette to the existing portfoli Federico Karagulian

Equivalence Cigarette

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Page 1: Equivalence Cigarette

Demonstrating substantial EQUIVALENCEof a new cigarette to the existing portfolio

Federico Karagulian

Page 2: Equivalence Cigarette

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

Page 3: Equivalence Cigarette

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

Page 4: Equivalence Cigarette

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

Page 5: Equivalence Cigarette

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?

Page 6: Equivalence Cigarette

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

Page 7: Equivalence Cigarette

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

Page 8: Equivalence Cigarette

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

Page 9: Equivalence Cigarette

* 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

Page 10: Equivalence Cigarette

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

Page 11: Equivalence Cigarette

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

Page 12: Equivalence Cigarette

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

Page 13: Equivalence Cigarette

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

Page 14: Equivalence Cigarette

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

Page 15: Equivalence Cigarette

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

Page 16: Equivalence Cigarette

Overall EFFICIENCY for new cigarettes

feedback loop:take action on fundamental components

Discovery Validation EFFICIENCY(toxicological info)

totalefficiency

22 EE IE

Page 17: Equivalence Cigarette

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