INTERNSHIP EXPERIENCE IN
ANALYZING STABILITY DATA
Speaker: Charlene Pu
ASA UP-STATConference - 4/6/2013
Source: FDA
http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/PostMarketActivities/LotReleases/ucm310644.htm
A/California (H1N1)
 A/Victoria (H3N2)
 B/Wisconsin

Potency
VACCINE SHELF LIFE
Potency of
vaccine degrade
over time
Registration
Limit
Time, months
FLUZONE POTENCY STABILITY PROJECT

Reduce Potency Variability of Fluzone Product

Partial Least Squares technique (PLS)



Take care of multicollinearity issue
Latent Factor (component)
-optimally chosen to obtain high R-square and low RMSE
Variation in the predicted variable + Variation in the
response variable
Tutorial Video– Using PLS in JMP
http://www.youtube.com/watch?v=TtSYTXk_0y4
Potency
DEGRADATION PLOT
Determine
concentration
here
To Predict
the Potency on
Expiry here
Formulation
Target
Registration
Limit
Expiry
Manufacturing
Time Point
Time, months
Potency Stability Data
Lot 1
Lot 2
Lot 3
Lot 4
Lot 5
Lot 6
Overall Slope
10%
Potency Change, %
0%
-10%
-20%
-30%
-40%
log Time, days  1
-50%
-60%
0
100
200
300
Time , days
400
500
600
REGRESSION THROUGH THE ORIGIN
y  1 x  
LOWER CONFIDENCE INTERVAL ON E(Y|X )
0
 
ˆ y| x  t / 2,df x0  se ˆ1
2
0
SAS CODES
proc glm data=asa_example;
model _CHANGE=TIME/NOINT;
run;
log days  1
Potency % Cˆ hange  12.0871 time
OVERALL SLOPE







Confidence Level: 95%
Registration Limit: 27 ug HA/mL
Manufacturing Time Point to Expiration Date: 365 days
Average Slope: -12.0871
Standard Error of Average Slope, se(slope): 0.5809
Mean Square Error of Regression Model: 73.1774
Degree of Freedom: 47
Formulation Target=
LRL /1   Slope  log days  1  t / 2,df
 
 
log days  12  seSlope   100% 




27 / 1   12.0871 log( 365  1)  t0.025, 47 log( 365  1) 2  0.5809 100%
27 / 1   33.5% 100%   40.6


Potency Stability Data
Lot 1
Lot 2
Lot 3
Lot 4
Lot 5
Lot 6
Overall Slope
Lot 3
10%
Potency Change, %
0%
-10%
-20%
-30%
-40%
-50%
-60%
0
100
200
300
Time , days
400
500
600
SAS CODES
SLOPE FOR WORST LOT
data ex; set asa_example;
l1=0; l2=0; l3=0; l4=0; l5=0; l6=0;
if lot='Lot 1' then l1=1;
if lot='Lot 2' then l2=1;
if lot='Lot 3' then l3=1;
if lot='Lot 4' then l4=1;
if lot='Lot 5' then l5=1;
if lot='Lot 6' then l6=1;
time1=Time*l1;
time2=Time*l2;
time3=Time*l3;
time4=Time*l4;
time5=Time*l5;
time6=Time*l6;
proc reg data=ex;
model _CHANGE = time1-time6 / noint;
run; quit;
SEPARATE SLOPE







Confidence Level: 95%
Registration Limit: 27 ug HA/mL
Manufacturing Time Point to Expiration Date: 365 days
Slope for the Worst Case: -15.8185
SE of Slope for the Worst Case: 1.0693
Mean Square Error of Regression Model: 41.8014
Degree of Freedom: 42
Formulation Target =
LRL /1   Slope  log days  1  t / 2,df
 
 
log days  12  seSlope   100% 




27 / 1   15.8185 log( 365  1)  t0.025, 42 log( 365  1) 2 1.0693 100%
27 / 1   45.2% 100%   49.2


CONCLUSION
The least squares regression analysis could be
employed to model potency decay.
 Partial Least Squares analysis could be
performed to quantify manufacturing factors that
affect the vaccine stability

CONTACT INFORMATION
Hsuen- Li (Charlene) Pu

Email: pucharlene1224@gmail.com

Phone: (917)847-2323

LinkedIn:
www.linkedin.com/pub/hsuen-li-charlenepu/42/760/aa7/
SAS CODES
SLOPE FOR WORST LOT
proc glm data=asa_example;
class LOT;
model _CHANGE=TIME TIME*LOT/noint solution;
run; quit;
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