Quality by design parameters with design

1. Quality by design in pharmaceutical Development
Dr. Swati Gokul Talele
Sandip Institute of Pharmaceutical Sciences, Nashik

2. Introduction:
Quality by design terminology coined by Quality pioneer Dr.
Joseph M.Juran (1985).
He believed that Quality can not be tested in products but
rather has to be built in product.
The concept of QBD was mention in ICH Q8 guidelines.
Woodcock second Scientist emphasis
 High-quality drug product as a product free of
contamination.
 Reliably delivering the therapeutic benefit promised in the
label to the consumer.

3. Definition of QBD
• Pharmaceutical QbD is a systematic approach
to development that begins
with predefined objectives and
emphasizes product and process understanding
and control based on sound science
and quality risk management

4. WHY QBD ?
Higher level of assurance of product quality for patient but
by great efforts and cost
Lack of modernasation of pharmaceutical manufacturing as
compared to other industry
Inability for scale up technology.
• Lack of predictability or understanding about manufacturing
failure.
Global fragmentation

5. Advantages of QBD
Industrial Benefits
• Better understanding of the process.
• Less batch failure.
• More efficient and effective control of change.
• Return on investment / cost savings.

6. Additional paybacks
To enhance root cause analysis and
Reduction of post-approval submissions.
 More efficient technology transfer to
manufacturing.
 Risk-based approach and identification.
Innovative process validation approaches.

7. QbD
Applications
Clinical Trials
Drug
Substance
Development
Formulation
Development
Bioequivalence
Studies
Pharmaceutical
Development
Analytical
Development

8. Quality by testing (QbT) Quality by design(QbD)
Setting right
Specifications
Scientific Understanding
Flexible Process
Robustress Of Methodology With
Enough Space For Acceptable
Variatoion
Knowledge Rich
Submission
Rigid Process
Repeated Reproducibility
With Zero Space For
Variations
Data Intensive
Submission

10. • The US Food and Drug Administration (FDA) encourages
Risk-based approaches and the implementation of QbD
principles in drug product development, manufacturing, and
regulation.
FDA’s emphasis on QbD began with the recognition that
increased testing does not necessarily improve product
quality.
Quality must be built into the product.

11. ICH Q8 through Q12
 ICH Q8(R2)- ‘Pharmaceutical Development’
ICH Q9- ‘Quality Risk Management’
ICH Q10- ‘Pharmaceutical Quality System’
ICH Q11- ‘Development and Manufacturing of Drug Substances’
(Chemical Entities and Biotechnological/Biological Entities)
ICH Q12- Concept paper- Guideline on Technical and Regulatory
Considerations for Pharmaceutical Product Lifecycle Management
and its Annexes

12. Developing Process Understanding

13. Development of Model Y =f(x)Enables Prediction of Future Process

14. Building
Blocks of QbD

15. Critical Process Parameter (CPP)
QBD Terminology
Critical Materials Attributes(CMA)
Introduction to Quality by Design(QbD)
Design Space(DS)
Control Strategy(CS)
Lifecycle
Quality target product profile (QTPP)
Critical Quality Attributes( CQA)

16. Define the quality
target product (QTPP)
as it relates to quality,
safety and efficacy,
considering for
example the route of
administration,
dosage form
bioavailability,
strength and stability.
Identification of
suitable approach to
drug formulation and
manufacturing
process.
Identification of
critical quality
attributes (CQA) of
raw material, drug
substance or product
and find out an impact
on product quality
and the then can be
controlled.
Steps involved
in QbD process
applied to
pharmaceutical
product
development
STEP 1 STEP 2 STEP 3

17. Identification of
critical process
parameter.
Risk assessment and
experimental
approaches utilize to
determine
relationship between
raw material CQA and
CPP to drug product
CQA.
Optimization of
formulation and
manufacturing
process. Insuch a way
to meet QTPP (step 1).
Establishment of
design space and
control strategy.
STEP 4 STEP 5 STEP 6 STEP 7

18. LEVAMLODIPINE BESILATE ORODISPERSIBLE TABLET(10 mg) APPLYING
QUALITY BY DESIGN(QbD) CONCEPT
18
• Active Pharmaceutical Ingredient.
Levamlodipine
besilate
• Multifunctional ExcipientGalen IQTM721
• Solubilizer and SuperdisintegrantKOLLIDON® CL
• Lubricant.Magnesium Stearate

19. QUALITY TARGET PROFILE FOR Drug Product
Sr. No Quality Attributes Target
1 Dosage form Tablet
2 Dose Design Orodispersible Tablet
3 Route of Administration Oral
4 Dose Strength 10 mg
5 Physical attribute
Tablet conforming to
description shape & size
6 Assay 98.0-102.0%
7 Content Uniformity As per I.P. standards
8 Hardness 50-60 N
9 Disintegration Time Not more than 120 seconds8/3/2020

20. Risk Ranking
Level Action to be Taken
High Risk
Risk is unacceptable .Further investigation
is needed to reduce the risk.
Medium Risk
Risk is acceptable. No further investigation
is needed.
Low Risk
Broadly acceptable risk. No further
investigation is needed.
208/3/2020

21. Critical Quality Attributes (CQA) of
Drug Product Levamlodipine besilate
orodispersible tablet
Quality
Attribute
Target Is this CQA? Justification
1)Appearance
Colour and shape
acceptable to the
patient. No visual
tablet defects
observed
Yes
Colour, shape and appearance are not
directly linked to safety and efficacy.
Therefore, they are not critical. But
appearance can affect patient
acceptability. The target is set to
ensure patient acceptability.
2) Odour No unpleasant odour No In general, a noticeable odour is not
directly linked to safety and efficacy, but
odour can affect patient acceptability. In
this product drug & excipient do not
have objectionable odour. No organic
solvents will be used in the drug
product manufacturing process.
3) Taste No Bitter Taste Yes
Levamlodipine besilate has Slightly
Bitter taste, hence in order to improve
patient acceptability, it’s taste should
me masked
218/3/2020

22. Critical Quality Attributes (CQA) of
Drug Product
Quality Attribute Target Is this CQA? Justification
4) Size
As per standards
No
For patient compliance the target tablet
dimensions are set as per standard size.
5) Assay 98-102.0% Yes
Assay variability will affect safety and
efficacy. Process variables may affect the
assay of the drug product. Thus, assay will
be evaluated throughout product and
process development
6) Water Content Not more than
0.8%
Yes
Levamlodipine besilate is sensitive to
moisture, the presence of water affects the
degradation and hence it is potential
CQA.
7) Content Uniformity Meets I.P .
Standards
Yes
Variability in content uniformity will affect
safety and efficacy. Both formulation and
process variables impact content
uniformity, so this CQA will be evaluated
throughout product and process
development
228/3/2020

23. Critical Quality Attributes (CQA) of Drug
Product
Quality Attribute Target Is this CQA? Justification
8) Hardness 50-60 N Yes Hardness is potential CQA for
Orodispersible tablets.
9) Friability NMT 0.6% No
A target of NMT 0.6% w/w of mean
weight loss assures a low impact on
patient safety and efficacy and
minimizes customer complaints
10)Disintegration
Time
NMT 120 sec Yes
As disintegration time is major
parameter for Orodispersible tablets
hence, CQA will be investigated
throughout formulation and process
development.
11) Dissolution
NLT 70% at 45 min
in 0.1M HCl using
USP apparatus 2
Yes
Failure to meet the dissolution
specification can impact bioavailability.
Both formulation and process variables
affect the dissolution profile. This CQA
will be investigated throughout
formulation and process development
238/3/2020

24. Critical Quality Attributes of Drug
Drug Product
CQAs
A.P.I. Attributes
Hygroscopicity Solubility Moisture Flow Properties Bulk Density
Appearance Low Low Low Low Low
Assay High Low High Medium Low
Hardness Medium Low High Low Medium
Friability Low Low Low
Low Low
Content
Uniformity
Low Low Low High Medium
Disintegration Low Medium Medium Low Low
Dissolution Low High Medium Low Low 248/3/2020

25. Critical Quality Attributes of Excipients
Drug Product CQAs Excipients Attributes
Galen IQTM721 Kollidon ®CL Magnesium Stearate
Appearance Low Low Low
Assay Low Low Low
Hardness Medium Low Low
Friability Low Low Low
Content Uniformity Medium Low Low
Disintegration Low High High
Dissolution Low High High
258/3/2020

26. Risk Assessment to Identify the Process
Variables Potentially Impacting Product
Quality
Drug Product CQAs
Variables and Unit Operations
Formulation
Composition
Blending Compression
Appearance Low Low Low
Identity Low Low Low
Assay Low Low Low
Impurities Low Low Low
Hardness Low Low High
Content Uniformity Low Low Low
Disintegration High Low High
Dissolution High Low High
268/3/2020

27. Factorial Design
• X n = Number of experiments
Where
• n = Experimental variables
• X= Levels

28. • There are two main types of response surface designs: Central
Composite designs. Central Composite designs can fit a full quadratic
model. ...
• Box-Behnken designs usually have fewer design points than central
composite designs, thus, they are less expensive to run with the same
number of factors.
Design Of Experiments
(DOE)
Taguthi
(DOE)
Factorial
(DOE)
RSM
Based DOE
Latin
square DOE

29. Design of Experiment: 1
Drug: LEVAMLODIPINE BESILATE
Excipients: Galen IQTM721, Kollidon® CL, Magnesium Stearate
 Experimental Design: 33 Box-Behnken Design
 Number of trials: 15 Experiments (3-center points)
29
Level of variables Concentration of Factors for 1 Tablet
Concentration
of
Galen IQTM721
(mg)
Concentration of
KOLLIDON ® CL
(mg)
Concentration of
Magnesium
Stearate (mg)
Low Level (-1) 74.5 1 0.5
Medium Level 84.5 3 0.8
High Level (+1) 94.5 5 1.1

30. Design of Experiment: 2
Formulation
Code as per
Standard order
Weight of
Levamlodipine
Besilate(mg)
Factor 1:
GalenTM
IQ721(mg)
Factor 2:
Kollidon®
CL(mg)
Factor 3:
Magnesium
Stearate(mg)
Total Tablet
Weight(mg)
1 10 74.5 1 0.8 86.3
2 10 94.5 1 0.8 106.3
3 10 74.5 5 0.8 90.9
4 10 94.5 5 0.8 110.3
5 10 74.5 3 0.5 88
6 10 95.5 3 0.5 108
7 10 74.5 3 1.1 88.6
8 10 94.5 3 1.1 108.6
9 10 84.5 1 0.5 96
10 10 84.5 5 0.5 100
11 10 84.5 1 1.1 96.6
12 10 84.5 5 1.1 100.6
13 10 84.5 3 0.8 98.3
14 10 84.5 3 0.8 98.3
15 10 84.5 3 0.8 98.3
308/3/2020

31. 31
Levamlodipine besilate ODT Evaluation
Results
Formulation
No.
Hardness
(N)
Thickness
(mm)
Weight
Variation
(mg)
WettingTime
(sec)
Disintegratio
n Time
(sec)
% Cumulative
Drug Release
1 45±2.5 2.07±0.20 86.3±0.75 66±0.5 87 89.34
2 45±2.5 2.55±0.20 106.3±0.75 62±0.5 85 91.38
3 45±2.5 2.16±0.20 90.3±0.75 48±0.5 61 96.42
4 45±2.5 2.64±0.20 110.3±0.75 57±0.5 63 97.86
5 45±2.5 2.11±0.20 88±0.75 54±0.5 64 94.26
6 45±2.5 2.59±0.20 108±0.75 57±0.5 66 96.29
7 45±2.5 2.12±0.20 88.6±0.75 55±0.5 78 93.05
8 45±2.5 2.60±0.20 108.6±0.75 59±0.5 82 93.97
9 45±2.5 2.30±0.20 96±0.75 62±0.5 90 91.68
10 45±2.5 2.40±0.20 100±0.75 35±0.5 54 99.99
11 45±2.5 2.31±0.20 96.6±0.75 65±0.5 96 88.17
12 45±2.5 2.41±0.20 100.6±0.75 58±0.5 67 95.50
13 45±2.5 2.35±0.20 98.3±0.75 56±0.5 68 97.16
14 45±2.5 2.35±0.20 98.3±0.75 56±0.5 69 97.16
15 45±2.5 2.35±0.20 98.3±0.75 56±0.5 67 97.16
8/3/2020

32. Results of ANOVA for Response surface Quadratic
Model for Disintegration Time
Source
Sum of
Squares
df
Mean
Square
F
Value
p-value
Prob> F
Model 2053.98 9 230.65 19.76 0.0022 Significant
A-Galen IQ721 4.50 1 4.50 0.39 0.5599
B-Kollidon CL 1596.13 1 1596.13 138.19 < 0.0001
C-Magnesium Stearate 300.12 1 300.12 25.98 0.0038
AB 4.00 1 4.00 0.35 0.5818
AC 1.00 1 1.000 0.087 0.7804
BC 12.25 1 12.25 1.06 0.3503
A2 2.83 1 2.83 0.24 0.6418
B2 96.98 1 96.98 8.40 0.0339
C2 48.52 1 48.52 4.20 0.0957
Residual 57.75 5 11.55
Lack of Fit 55.75 3 18.58
Pure Error 2.00 2 1.00
Cor Total 2115.60 14
328/3/2020

33. Results of ANOVA for Response surface Quadratic
Model for % Cumulative Drug Release
Source
Sum of
Squares
Sum of
Squares
df
Mean
Square
F
Value
p-value
Prob> F
Model 154.06 9 17.12 27.85 57.59 0.0009 Significant
A-Galen IQ721 5.17 1 5.17 8.41
1.88
0.0338
B-Kollidon CL 106.58 1 106.58 173.38
462.01
< 0.0001
C-Magnesium Stearate 16.62 1 16.62 27.03
10.32
0.0035
AB 0.090 1 0.090 0.15
7.522E-004
0.7177
AC 0.31 1 0.31 0.50 0.27 0.5106
BC 0.24 1 0.24 0.39 0.97 0.5594
A2 7.51 1 7.51 12.22 32.00 0.0174
B2 14.53 1 14.53 23.64 5.50 0.0046
C2 6.64 1 6.64 10.81 10.50 0.0218
Residual 3.07 5 0.61
Lack of Fit 3.07 3 1.02
Pure Error 0.000 2 0.000
Cor Total 157.13 14
8/3/2020

34. Other Parameters
• Coulter plot
• 3D response Plot
• Desirability plot
• Model Validation

35. THANK YOU