Introduction to Process Analytical Technology -...
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Introduction to Process Analytical Technology
PAT
PhPh. D. Line Lundsberg. D. Line Lundsberg--NielsenNielsenLundsberg ConsultingLundsberg ConsultingIndustriFarmaceutForeningen, 2. marts, 2006IndustriFarmaceutForeningen, 2. marts, 2006
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PAT – Process Understanding
The goal is to understand our processes enabling us fast to develop and produce smart and cost effectively high quality products
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Who is strongly involved in PAT, 2006
• Sanofi Aventis (first approval)
• ~10 other approvals (not public – OTC, generic, API, biotech, DP)
• Pfizer (4 b $ savings – PAT a part of the tools)
• GSK (to save inventory 2b$)
• Abbott (Controlling the Porto Rico plants by PAT from US – saved 3 digit million $/year – save inventory 1b$/year)
• AstraZeneca (Plackstadt)
• AstraZeneca (Sødertäljecontrolled 70% by PAT)
• Ge Healthcare• Merck • Wyeth• BMS
• Lilly• Lundbeck• Baxter• Amgen• Novo Nordisk• Watson Pharmaceuticals• Xcellercx• Scherring-Plough• Johnson&Johnson• Amteck• Novartis• Sandoz• Genentech• Biogen• FDA, ICH, ISPE, ASTM,
aaps,…..
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Outline
• Why PAT?• What is PAT?• Examples of applying PAT
tools
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Why PAT
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“The pharmaceutical industry has a little secret: Even as it invents futuristic new drugs, its manufacturing techniques lag far behind those of potato-chip and laundry-soap makers”
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Doug Dean, FDA Science Board, Nov 16, 2001
Current Paradigm:
• Utilisation levels - 15% or less
• Scrap and rework - plan for 5-10%
• Time to effectiveness - takes years
• Hesitant to Innovate– Incentive?
• Manufacturing Costs: $90 Billion
Why PAT?
Ray Scherzer, FDA Science Board, Apr 2, 2002
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Product focus – the traditional development concept
• Compliance – meet specifications – documentations• 3 validation batches• Trial and error• Limited sampling and analysis• Ignore variations, testing to required specifications• No changes, changes are negative• No link between input and output quality• Budgeted scraps, rework, OOS, investigations
Input Production Output
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Pharmas compared to other industries
65
90
95
99
99,999
Yields (%)
25-35
20-25
4-8
4-8
1-3
Cost of Quality (% of COGS)
>99%Car, & electronics
1-4%
2-20%
20-50%
>90%
Mass Productivity (Kg Product/ Kg total ex water)
Pharma-ceuticals
Fine Chemicals
Bulk chemicals
Oil refining
Industry
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Cost of manufacturing
25%
12%
30%
12%
5%16%Net Income
TaxOther Expenses
SGA
R&D
COGS
Components of Pharmaceutical Industry Costs
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What is PAT
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PAT- Process Analytical Technology
A Framework for Innovative Pharmaceutical Development,
Manufacturing, and Quality Assurance
FDA PAT Guide
PAT is a framework – not a set of requirements
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Change Focus
Move from product focus to process focus
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What is PAT, by definition
• A system for:– designing, analyzing, and controlling
manufacturing– timely measurements (i.e., during processing)– critical quality and performance attributes – raw and in-process materials– processes
• “Analytical” includes:– integrated chemical, physical, microbio-
logical, mathematical, and risk analysis
• Focus of PAT is Understanding and Controlling the manufacturing Process
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Designing
Based on– Target product profile– Raw materials and intermediates and their
variability– Systematic compilation of Process
Knowledge (literature, existing, other processes and new)
– Identification of critical quality attributes CQA
– Identification of critical process parameters CPP
– Understanding the process
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Analysing
• Analysis of (relevant and appropriate, not necessary on-line, but results has to be used for justification within the production process)
– Raw Materials– Process data– In-process analysis– Critical Control Points
• Prediction of– Process and product quality
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Controlling
• Control strategies• Monitoring critical quality attributes and
process parameters• Process signatures• Feed-back control• Feed-forward control• Process performance
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The PAT Framework will enable
• Focusing on Process Understanding• Creating an environment that facilitates
rationale science, risk, and business decisions
• Providing a flexible and less burdensome regulatory approach for well understood processes
• Only controlling critical quality and process parameters
• Managing the variability in manufacturing processes
Input Production Output
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A Process is understood when
• All critical sources of variability are identified and explained
• Variability is managed by the process
• Product quality attributes can be accurately and reliable predicted
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PAT production framework
On-line control of critical parameters
Feed back Process control
loop
Raw materialsProduct
Adjustment
Production processes
Monitoring of critical parameters
Adjustment
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Result of the “new” way of thinking
• A focus on process understanding will reduce/remove validation burden
• No process validation - each batch process is a validation
• If anything goes wrong, we know what it is• Room for natural variation (e.g. raw material)• Reduction in OOS and failure investigations• Quality of end product can be predicted• Expected regulatory relief• Cost reduction!!!
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Note!
• Transfer of laboratory methods to on-, in-, or at-line methods may not necessarily be PAT
• A “PAT” technology used in the lab may not necessarily be PAT
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PAT is multi functional
• Chemists• Pharmacist• Process Engineers• Quality expert• Analytical chemist• Chemometician (statistician)• Regulatory• Development• Manufacturing
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PAT Tools
• Integrated Systems Approach • Risk Based Approach• Systematic approach• Related tools – LEAN, Six Sigma• Multivariate tools for design, data acquisition
and analysis• Process analyzers• Process control tools• Continuous improvement and
knowledge management tools• Real Time Release
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Obstacles in implementing PAT
• Understanding ”Process Understanding”• Holistic approach• Not only a R&D, production or support issue• Organisational challenges: Has to involve
– R&D– QA– RA – Productions– Engineering– QC
• Need top management support• Change management: Changing the way we
normally work and co-operate together• The development and implementation strategy
for new products has to be reworked…
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Examples
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What Can Be Measured Using PATAPI/Raw Materials
• Chemical Interactions• Particle Size Distribution• Polymorphism• Reaction Rate & Endpoint• Concentration/Composition/Uniformity• Identification• Drying Rate & Endpoint• Adequacy of a Cleaning Process• Etc.
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What Can Be Measured Using PATDrug Product
• Particle Size Distribution• Blending Homogeneity & Endpoint• Granulation Rate & Endpoint• Drying Rate and Endpoint• Drying Temperature & Relative Humidity• Drying Airflow Rate• Tablet Identity• Tablet Uniformity/Potency• Dissolution Rate• Tablet Weight• Tablet Thickness• Tablet Hardness• Tablet Coating Thickness & Quality• Coating solution viscosity & specific gravity• Etc.
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Example 1, Solid dosage forms
• Sticking of blend to tablet punches• Creates damages tablets• Scrap!
• Why?
• Lack of process understanding• What is critical to the product and to
the process?
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Tablet Sticking during Production
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Vision System Theory
The Vision system takes an individual digital image of every particle of a dispersed sample then measures the size and shape from the image to produce a distribution
Glass Slide
Particles of sample
TelevisionCamera
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Magnesium Stearate - Japan vs. Brazil
Japanese material has 202 % the surface area of the Brazilian material
Brazil magnesium stearate
Japan magnesium stearate
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Sticking versus Dissolution Issues
• Mg stearate supplier was changed to increased surface area material, for all products following the successful work to eliminate sticking.
• New “Good” supplier material caused low and variable dissolution in a capsules product
• One PSD does not fit all– Some plants now uses one grade of material
for capsules and another grade for tablets
• Very robust processes with optimal material
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Example 2, Blend homogeneity
• How to avoid segregation? • When is a blend homogenate?• What is critical for our blend process
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V-blender, on-line NIR monitoring
Rodolfo J. Romañach, UPR-Mayagüez, PRPQA January 24, 2006
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Bohle-blender, on-line NIR monitoring
Experimental design for on-line
measurement of powder mixing
using a diode array NIR
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On-line NIR monitoring of powder mixing
-10
0
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20
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0 100 200 300 400 500 600
Rotations
Con
cent
ratio
n / %
On-line results using PLS calibration
On-line concentration of API
On-line concentration of mic. cellulose
On-line concentration of Mg-stearate
Step I: Mixing of API and talcum powder
Step II: Addition of mic. cellulose and otherexcipients
Step III: Addition of Mg-stearate
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Example 3, Crystallisation
• Separation of polymorphs• Crystal shape & size• PSD
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Crystallisation process
NIR
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Crystal forms, Raman
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Identification of different polymorphs, NIR
Amorphous
Crystal form α
Crystal form β
Crystal form α and β (1:1)
III
I
I + II
II
Amorphous
Crystal form α
Crystal form β
Crystal form α and β (1:1)
III AmorphousAmorphous
Crystal form αCrystal form α
Crystal form βCrystal form β
Crystal form α and β (1:1)Crystal form α and β (1:1)
III
I
I + II
II
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Crystallisation
Lasentec probeFocused beam reflectanse
Probe inserted into crystalliser
Circulating light beam bounces of particles suspended in solvent
Measures crystal diameter
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Crystal size during formation
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800
1000
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1:16:00 1:20:48 1:25:36 1:30:24 1:35:12
Reaction Time (hrs)
Part
icle
Cou
nt s
ec-1
0-50 microns
O-10 microns
50-100 microns
> 100 microns
Seed point
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Endoscope picture inside crystalliser
Possible benefits
Control of fines or agglomerates in API
Reduced need to mill
Control of particle size
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Warming to lower content of fines.
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12:28 12:57 13:26 13:55 14:24 14:52 15:21 15:500
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#/sec, No Wt 0 10 #/sec, No Wt 10 50 #/sec, No Wt 50 100 #/sec, No Wt 100 1000
50-100
0 - 10
10- 50
100- 1000
Temp
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Summary
• PAT is a science and risk based framework
• Process Understanding is the heart of PAT• PAT is a tool for managing the variability in
the various manufacturing steps• PAT is a tool for faster product development• PAT is design, analysing and controlling what
is critical• PAT is a tool for production optimisation• PAT is a tool for cost reduction• PAT is a not new but new to pharmaceutical
manufacturing!
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Acknowledge
• FDA, Ali Afnan and Chris Watts• Industrial colleagues:
– Ajaz Hussain, Sandoz– Ray Scherzer, GSK– Steve Hammond, Pfizer– Zhihong Ge, Merck– Casper Leuenhagen, Novo Nordisk– Mette Bryder, H. Lundbeck A/S – Lisbeth Thierry-Carstensen, H. Lundbeck A/S – Anette Hansen, H. Lundbeck A/S– Uffe Svare, H. Lundbeck A/S– Michael Hahn, H. Lundbeck A/S– Frank Høien Lendal H. Lundbeck A/S– Gert Mølgaard, NNE
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Questions?
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More examples
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Example 4, controlling reactions
• Conventional samples are taken at “appropriate time” and analysed in lab (take days or weeks)
• But what is happening during reaction?• What is critical to the process?• How can yields be optimised and
impurities minimised?
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On-line NIR, IR or Raman
On-line control of critical parameters
Feed back Process control loop
Raw materialsProduct
Adjustment
Production processes
Monitoring of critical parameters
Adjustment
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No samplingNo operator exposureAccurate end pointControl of impurities
Mid-IR to Monitor and Control Reactions
Curves generated using peak heights at 2-point baseline:Blue – starting material at 2239 cm-1Red – starting material at 930 cm-1Green – product at 1308 cm-1
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Typical reaction monitoring techniques - NIR
• NIR is a strong tool for controlling end-point reaction
• Note NIR does not see every thing, e.g. not generation of impurities
Progress of reaction Reaction
complete
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On-line Raman, monitoring Catalytic Hydrogenation Reaction
ReactantIntermediateProduct