Organizational Initiatives Towards

Developing Greener Processes for

Generic Active Pharmaceutical

Ingredients

IGCW, DEC 4-5, 2015

Vilas H Dahanukar, Ph.D., FRSC

Chief Scientist Process R&D

G O O D H E A LT H CAN ’ T W A I T.

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• Background

• Introduction to Quality by Design and Six Sigma

• Work practices developed at DRL

• Case study highlighting example of greener

processes using QbD

PRESENTATION OUTLINE

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Average API Manufacturing

Cost Breakup

Excessive amount of product non-

conformances – market recalls,

quality compliance

Changing regulatory landscape

(GDUFA requirement, QbD, etc)

Longer product development cycle

time

Large inefficient batch equipment

with lower utilization

Capital and labor intensive

High inventories and excessive

warehouse space

Challenges Facing Generic Pharma

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Desired State

Pharm Develop

Q(8)

Quality Risk

Mgmt(Q9)

Quality Systems

Q(10)

ICH Q8, Q9, Q10: Foundation of Quality by Design (QbD

Current Regulatory Scenario

• Innovation & Continual Improvement

• Optimized Changed Management

• Flexible Regulatory Approach

Source: Moheb Nasir, 2006

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Quality by Design (QbD)

• Science and risk-based approach to development with principle-“Quality cannot be tested into products must be built in”.

• Critical Quality Attributes (CQA) and factors which affect Quality Target Profile (QTPP) must be well understood and controlled in Intermediates, Drug substance, Excipients and Drug product.

• Risk assessment should be used throughout development to guide and justify development decisions, along with control strategies to manage risks.

• Design space used to define the acceptable limits for operational parameters to assure the product quality.

• Applicable over entire product lifecycle.

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• Quality Target Product Profile (QTPP)

• Determine “potential” critical quality

attributes (CQAs)

• Link raw material attributes and

process parameters to CQAs and

perform risk assessment

• Develop a design space

• Design and implement a control

strategy

• Manage product lifecycle, including

continual improvementContinual Improvement

CQA’s

Risk Assessment

Design Space

Control Strategy

Product Profile

ICH Guideline Q11 on Dev & Mfg of API

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WHAT IS DOE?

• Designed set of experiments in which all relevant factors (variables that influence response) are varied simultaneously instead of traditional OVAT (one variable at a time)

• Analysis indicate which factors influence the outcome and identifies optimal conditions

• Systematic, organized approach to process optimization & designing robust processes

• Mathematical model of the design space

• Screening• Which factors are most influential ?

• What are their appropriate values/ranges ?

• Optimization• Extract information regarding how factors combine to influence response

• Identify optimized reaction conditions

• Automation/technology helps reduce the effort needed

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CONTROL STRATEGY

Nature of Control Extent of Control

Design Space: Multidimensional combination and

interaction of input variables (e.g., material attributes) and

process parameters that have been demonstrated to

provide assurance of quality (derived from DoE)

Design Control: Controls implemented to avoid/exclude

the potential failure scenario(s), viz., selecting the route,

including an unit operation, excluding temperature zone.

Process Control: Controlled through Edge of Failure

(EOF)/What-if studies, and suitable validatable sampling

plan and test procedure (controls on CMA and CPP, in-

process controls)

System Control: Evaluated through sampling protocol; eg.

in process sampling, GLP and GMP controls in plant

• PAR > NOR

• PAR = NOR

• PAR # NOR

• PAR < NOR

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• Data driven methodology of DMAIC (Define,

Measure, Analyze, Improve & Control) with end

customer/product requirements in forefront

• Systematic process improvement by reducing

variation and defects

• Can be applied for an existing process or used

to design a new process using DFSS

• Enhances customer satisfaction and reduce

cost

What is Six Sigma

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Tools & Approaches

Ref: http://www.pharmamirror.com/pharmaceutical-articles/six-sigma-in-pharmaceutical-manufacturing-industry/

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OVERVIEW OF WORK PRACTICES AT DRL

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Quality Philosophy at DRL

• Identify sources of variability and reduce

process variability.

• Be right the first time. Identify and eliminate

waste, and productivity.

• Understand the impact of raw material

attributes on the final product quality.

• Adjust and control the process based on

quality of the raw materials.

• Develop and implement a control strategy

at the shop floor level ensuring delivery of

the right product quality.

• Culture of reporting incidents and take it as

a tool for continual improvement.

Quality for Customer Delight: Linking the patient, product and process

PATIENT

PRODUCTPROCESS A T

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Six Sigma Training

• Developed program with “American Society

for Quality (ASQ)” to train Six Sigma Green

and Black belts

• Over last 18 months 17 black belts and 40

green belts were certified.

• Black Belt Key Responsibility Areas: Applying

six sigma concepts and tools in all stages of

product development, mentoring green belts,

publications & presentations

• Green Belt Key Responsibility Areas:

Identification and use of distinct Six Sigma

Tools in different stages of Product

Development, inclusion at least threee distinct

tools in Product Development Reports and

Regulatory Submissions.

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Generic API Development

•Literature & Patent survey

•Product Development Strategy

•Route identification (BI metrics & cost models)

•Raw Material identification & sourcing

•Feasibility

•Optimization (Solvent, Reagent Selection, DoE, Design space)

•Analytical method development (DoE)

•Validated Method dev

•Trial & validation

•Stability studies

•Polymorph

•Salt

Risk Assessment & control with documented data

done at each stage in API development cycle

Define Research Design Develop Implement

Product selectionForm

selectionProcess

DevelopmentTechnology

TransferValidation & DMF filing

•Scale up FMEA

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QbD Enabled Product Development

API

Product

Develop

ment

Next Project Route selection metrics QTPP OEL ( safety, impurity limits)

Solvent Selection ( Prior knowledge, Principal component analysis); Reagent Selection

Brainstorming prior to parameter selection ( FMEA, Pareto analysis)

Factors selection for DOE ( Mechanistic understanding, Cause & Effect analysis)

Screening & optimisation DOE ( Choice of design based on nature of reaction)

Calorimetric studies ( Safety & QA) Linking intermediate CQA , CMA with

product CQA ( Matrix diagrams) Impurity tracker ( Defining key, critical,

non-critical, GTA, cutt-off imp’s) PMI tracker

Scale dependent and independent parameters

Scale up FMEA Specifications ( NOR,

PAR, Process capability) Control Strategy

(Process, equipment, Inprocess)

Inprocess and Spec trend analysis

Scale dependency of critical parameters

Confirmation of design space on scale

Route selection &

Feasibility

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ROUTE SELECTION METRICS

No. Parameter Variable Criterion Points Route A Route B Route C

1Reaction Mass Intensity(total wt of reactionmaterials/wt of product)

Does any stages have RMIgreater than 5?

No/Yes 10/7 10 10 10

2Process Mass Intensity(mass of materialsin/mass of product)

Does any stage has PMIgreater than 20 ?

Yes/No 10/7 7 7 3

3 YieldAny stages have yield lessthan 80% ?

No/Yes 10/7 8 8 4

4 Starting Materials

Are all raw materialsreadily available andinexpensive (individualcontribution of less than20% to total RMC)??

Yes/No 10 /7 7 7 7

5Use of HazardousReagents

Any hazardous reagentsused?

No /Yes 10/7 10 10 10

6 Intermediates

Does route involvesintermediates with poorphysical and chemicalproperties?

Yes/No 10/7 8 8 8

Org. Process Res. Dev . 2012,16, 1697

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ROUTE SELECTION METRICS

No. Parameter Variable Criterion Points Route A Route B Route C

7 Use of Hazardous SolventsAny hazardous solventsused?

No/Yes 10/7 10 10 10

8Extreme reactiontemperature or pressures

What is the reactiontemperature or pressure

No extremes/>150°C / < -30 °COr pressure >5bar

10/7/7/7

10 10 10

9 Reaction timeWhat is the timerequired for reaction?

<12 h/>12h 10/7 7 7 7

10 SafetyHighly exothermicreaction or other safetyconsiderations?

No/Yes 10/7 7 7 7

11 Impurities

Does route produce anygenotoxic impurities orother impurities that arepotentially difficult toremove in API stage?

No/Yes 10/7 7 7 7

Total 91 91 83

Org. Process Res. Dev . 2012,16, 1697

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Automation Tools Useful in DoE

Work Station Application Remarks

Radley's 12 plus carousel parallel Synthesizer

Parallel screening of 12 reactions at constant temperature

Maximum capacity 10 mL.Useful for screening reaction parameters viz,choice of reagent, solvent concentration,mole ratio for homogeneous reactions.

Easy max Controlled heating, cooling ramp , addition rate , RPM and data recording

Essential for minimisation of experimental variability in DoE. Essential for standardisation of process prior to scale up

HELPB-4 parallel Synthesizer Controlled heating, cooling ramp , addition rate , RPM and data recording. Interchangeblevessel capacity ranging from 25 to 500 mL

Ability to screen wide range of parametersviz, heating/cooling ramp, mixing, controlledaddition rates etc. from 30 mL to 500 mLscale

ChemSpeed Parallel Synthesiser of 20reactions with controlledheating, cooling ramp RPM andexperimental data recording

Maximum capacity 100 mL.Useful for screening reaction parameters viz,choice of reagent, solvent concentration atvariable reaction temperature

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Equipment Details

MOC Type of Agitator (RPM)

Proposed capacity

SSR Anchor 3.0 KL

GLR Propeller 1.0 KL

Leaf/Candy

-- 50 L

SS-CF -- 48’’

ATD -- 48 Trays

Unit OperationCycle

time(Hr)

Reaction 9

Work up 4

Crystallization 6

Filtration 9

Drying 6

Total Cycle Time 34

Input Output

180 kgRCM1

58 kg RCM2

Process Detailing & Green Metrics

Green metrics

Process Mass Intensity (PMI)

10

No of Steps 132

Aqueous Waste 500 L

Organic Waste 300 L

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CASE STUDY: OPTIMIZATION OF CHEMICAL

REACTION USING DoE

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Optimization of Nucleophilic Aromatic

Substitution Reaction

• Prior art disclosed EtOH/Et3N/Under Pressure/1200C @ 75-80 %• Major challenges were: complete conversion (>2% KSM-1) &

formation of dimer (5-7%)• Higher conversion and lower amount of dimer impurity necessary

to facilitate purification• Needed simpler process with a straightforward work up

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Solvent & Base Screening

S.N Solvent Dielec

tric Const

Temp BaseKSM-1

( Chloro)Product (NPD-2)

Imp-1KSM-2

(Amine)Remarks

1 Toluene 2.38 100 DIPEA -- -- -- NA No progress

2 THF 7.58 60 DIPEA -- -- -- NA No progress

3 Ethylacetate 6.02 75 DIPEA -- -- -- NA No progress

4 Ethylacetate 6.02 75 DIPEA 26.7 35.3 14.7(6.8RT) 8.3 KI additive

5 Isopropyl acetate 7 80 TEA -- -- -- NA KI additive

6 MIBK 12.4 100 DIPEA 35 24 -- NA Reaction not completed

7 Isoamylalchohol 15.3 100 TEA -- -- -- NA No progress,

8 n-Butanol 17.5 100 TEA -- -- -- NA No progress

9 IPA 19.92 80 DIPEA 60.66 19 -- NA Reaction not completed

10 NMM 32.2 100 NMM ND 64.7 15.7(NMM) 0.35 NMM reacting with KSM-1

11NMP 32.2 100 DIPEA 15.8 61.12 3.34(14.35) NA

24h, Reaction not completed

12Acetonitrile 35.94 80 TEA 33.1 31.5 6.6(14.83) NA

24h, Reaction not completed

13DMA 37.78 100 DIPEA 24.2 43.56 8.11(24.1) NA

24h, Reaction not completed

14 DMF 36.71 100 DIPEA 0.47 23.18 56.21(24.00) NA Imp formation is more

15 DMSO 46.45 100 TEA 0.92 71 9.8 (23.22RT) 0.6 Reaction time 4-5 hrs

16 DMSO 46.45 100 TEA 1.03 82.70 1.7 (23.22RT) 0.6 Reaction time 4-5 hrs

17 Water 80.4 100 NaHCO3 0.04 97.13 1.14 ( Dimer) ND Reaction time 10 hrs

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Design of Experiment for NPD-2 Stage

Response

Target

Yield Maximize

Purity Maximize

Impurity Minimize

S.No Parameters Low High Remarks

1 KSM-2 mole ratio 1.0 1.2Theoretically 1.0 equivalent is required. 1.5 eq offered desired yield and purity

2 NaHCO3 mole ratio 4.0 8.0 Usage of < 4.0 eq of NaHCO3 offered low yield

3 Water Vol 3.0 7.0 Usage of < 3.0 volumes did not offered good stirriblity

Fixed Variables

4 Temperature 90 100 Higher temperature leads to dimer impurity formation

5 RPM No EffectNo Effect on RPM

Design Summary:

Runs :20

Design Type :RSM

Design Model :Linear

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Contour Plot: Factors Affecting Dimer Imp

• Dimer impurity formation is not affected by mole ratio of amine

(KSM-2) and water volumes ( Fig-1)

• Reduction of KSM-2 mole ratio to less than 1.15 eq resulted in

increase of dimer formation from 0.3 to 0.7 % (Fig-2)

Fig-1Fig-2

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Factors affecting NPD-2 Purity & Yield

• Amine mole ratio and water volume does not have significant

impact on NPD-2A purity at fixed mole ratio of NaHCO3

• Yield is directly proportional to mole ratio of amine (KSM-2)

Low

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• High conversion obtained with higher mole ratio of amine (KSM-2)

• Purity of 98.1- 98.5 % is feasible within the identified ranges of

water and mole ratio of amine.

Factors Affecting Yield & Purity

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Design Space Validation & GMP Batch Data

Design-Expert® SoftwareFactor Coding: ActualOverlay Plot

yieldTIC-2ATIC-2A(NPY)

Design Points

X1 = A: KSM-2X2 = B: NaHCO3

Actual FactorC: Water = 3.00

1.00 1.05 1.10 1.15 1.20

4.0

5.0

6.0

7.0

8.0Overlay Plot

A: KSM-2

B:

Na

HC

O3

yield: 89.000

TIC-2A(NPY): 0.500

S.

No

KSM-2

m/r

NaHCO3

m/r

H2O

VolumeYield Purity Dimer

1

1.2 5.0 3.0

Actual / observed 90.95 98.81 0.65

Predicted 89.33 98.44 0.36

2

1.1 7.0 3.0

Actual / observed 91.4 98.82 0.66

Predicted 89.9 98.40 0.45

3

1.1 6.0 3.0

Actual / observed 90.96 98.65 0.65

Predicted 90.04 98.37 0.44

Trend Data of Scale up batches under optimum conditions

B.No Solvent Base Temp (°C)

Time (h)

Input (Kg)

Output (Kg)

%yield Purity (%)

AOGH000031 Water NaHCO3 90-95 15 9.0 14.4 91.0 98.4

AOGH000034 Water NaHCO3 90-95 15 9.0 15.1 95.3 98.6

AOGH000040 Water NaHCO3 90-95 15 9.0 14.8 93.5 98.5

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SUMMARY

Advantages:

• Focused experimentation helps in enhancing R&D

productivity and development of robust product development

using science and risk based approach

• Enables to maximize process efficiency and minimize waste-

Greener Processes

• Facilitates Life Cycle Management and managing regulatory

changes

Challenges:

• Culture and mindset change (creativity/innovation vs.

systems/processes) needs to be managed

• Need investment and commitment from senior management

in implementation of QbD

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ACKNOWLEDGMENT

Dr. ERR Chandrashekar

Dr. Rakeshwar Bandicchor

Dr. Amit Biswas

Dr. Sudhir Nambiar

Srinivas Mazumdar

PVM Ravi Shankar

Integrated Product Development Organization (IPDO), Hyderabad