continuous manufacturing: an industry view · 2017-02-03 · continuous quality monitoring and...
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Continuous Manufacturing: An Industry View Diane Zezza Novartis Pharmaceuticals FDA/PQRI Conference on Advancing Product Quality March 22, 2017
Novartis Pharmaceuticals
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Commercial Application
Where are we today? Continuous Manufacturing Journey
2017
Technical Feasibility
Scientific Principles
Broad Acceptance?
Prototypes
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Commercial Application
Where are we today? Continuous Manufacturing Journey
2017
Technical Feasibility
Scientific Principles
Broad Acceptance?
Prototypes
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Where are we today? Conferences
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Discussions on CM as new technology Created sound business justifications Discussed scientific principles Identified challenges Shared experiences
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Where are we today? Publications
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Some of the publications...
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Where are we today? Expertise
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Regulatory Agencies
Specialized teams to support new technologies FDA’s Emerging Technology Team EMA’s PAT Team PMDA’s Innovative Manufacturing Technology Work Group
Industry Possess and continuing to build specialized expertise
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Where are we today? Regulatory Landscape
ICH
• Q8, Q9, Q10, Q11
FDA
• DRAFT Guidance: Advancement of Emerging Technology Applications to Modernize the Pharmaceutical Manufacturing Base
• Other Guidances
EU
• Good Manufacturing Practice, Annex 15: Qualification and Validation
• Good Manufacturing Practice, Annex 17: Real Time Release Testing
• Process Validation • Real-time release testing
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• Existing framework supports CM approaches • No specific regulatory barriers exist
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Where are we today? Approved Products
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Seeing industry investment and regulatory approvals for products using CM approaches:
Vertex’s cystic fibrosis drug Orkambi (lumacaftor/ivacaftor]
Janssen’s HIV-1 treatment Prezista (darunavir ethanolate )
Many others in later stages of development
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Quality Systems
and Controls
Scientific
and Engineering Principles
Regulatory Guidelines, Guidances,
and Directives
Where are we today? Current framework
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Existing framework supports CM
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But...
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Batch manufacturing is not continuous manufacturing...
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What is unique to consider? Some Considerations
Regulatory Regulatory
expectations and
Dossier content
Flexibility and flexible approaches
Quality
State-of-control operation
and batch release
Process validation/verification
approach
Technical
Control strategy complexity
Spectrum of implementation
approaches
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Novartis Continuous Manufacturing
Ultimate Goal: Complete end-to-end Process
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Reaction Work-up Crystalisation Filtration Granulation Drying Tabletting Coating
raw materials drug product
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Unique Considerations Technical
Overall system and process performance more meaningful than parameter/attribute
relationships
Process description and lot traceability based on mean residence time distribution
System dynamics used to determine and justify sampling frequency
Sampling points, diversion points, and buffers part of control strategy
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Integrated thinking is critical: Process design, process control, process dynamics
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Quality in space and time, random scatter Simulated data, normalized space and time, 500 mg assay
CM mode Batch mode random inhomogeneity ↔ random noise
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Swapping space axis and time axis allows translation of quality metrics from batch processing to CM processing.
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Example: Rapid reaction optimization using inline analysis and feedback
• Automated system with feedback capabilities for optimization – Plug-and-play – Different in-line analysis methods,
e.g., HPLC, FTIR – Self calibrating – Customizable, experimental
optimization algorithms
Parameters: temperature, residence time, catalyst/ligand loading, solvent composition, ionic strength, pH
J.P. McMullen and K.F. Jensen, Annu. Rev. Anal. Chem. 3, 19–42 (2010). Org. Proc. Res. Dev. 14, 1169–1176 (2010)
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A reactor, a sensor, system response
Conjugate Gradient Steepest Descent
• Variety of optimization techniques • System performance is critical
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O
O
2,5-hexanedione
NH2OH
ethanolamine
+ NOHDMSO
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Example: Dryer in “state of control”
Perfect agreement with step data
Razor-sharp process appears poor
6 min
Apparent dispersion of CQAs is in reality instable process
Affects observed process capability
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Example: Dryer in “state of control”
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Choice of solution drives apparent performance
Optimal control may give better performance
Equipment improvements may even be better
Performance is what matters in the end
Batch it
Backmix
Optimal control
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Options for process control
Add Backmixing Creates apparent homogeneity potentially outlier product is included
Batch it
Truncate, divert Creates real homogeneity, yield lower
Apply active control Creates real homogeneity, yield high
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Evaluating overall performance and process performance matters!
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Potential approach to control strategy
Determine key quality attribute control points in process where relevant specifications can be verified
Determine system dynamics at these points for a given material flow rate • Derive the necessary measuring frequency
Verify process performance based on the points
Optionally disturb the process with small spikes to demonstrate effectiveness of the process control system
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Sample rate of CPPs/CQAs/IPCs reflecting material characteristics and process dynamics
Qua
lity
para
met
er
Minimum sampling period
This is what we need to avoid and discard
USL
LSL
UAL
LAL
Usable material
Usable material
Safety buffer
• Define when we need to know an unstable process can leave the spec limit (pre-warning time leads to action limits)
• Determine maximum rate of change of process and align sampling frequency with maximum rate of change such that no process change exceeding suitable ranges can be missed
• Link action limits with sampling period and rate of change • Measure constantly at this sampling rate • Effectively 100% controls of product quality, as process can not deviate undetected
Time axis
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Understanding process dynamics (rate of change) and process sensitivity allows to set the frequency of observation/sampling/measurement
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Unique Considerations Quality
Definition of a batch
State of control operation
Control strategy Batch release
Validation approach
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Quality considerations
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Batch Definition 21 CFR 210.3
2) Batch means a specific quantity of a drug or other material that is intended to have uniform character and quality, within specified limits, and is produced according to a single manufacturing order during the same cycle of manufacture. (10) Lot means a batch, or a specific identified portion of a batch, having uniform character and quality within specified limits; or, in the case of a drug product produced by continuous process, it is a specific identified amount produced in a unit of time or quantity in a manner that assures its having uniform character and quality within specified limits.
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Glossary of the EU GMP Guideline: A batch is a defined quantity of starting material, packaging material or product processed in one process or series of processes so that it could be expected to be homogeneous. Note: In the case of continuous manufacture, the batch must correspond to a defined fraction of the production, characterized by its intended homogeneity. EU GMP Guide, Part II (ICH Q7), Glossary: A batch is a specific quantity of material produced in a process or series of processes so that it is expected to be homogeneous within specified limits. In the case of continuous production, a batch may correspond to a defined fraction of the production. The batch size can be defined either by a fixed quantity or by the amount produced in a fixed time interval.
Batch Definition EU
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Batch Size
• In traditional batch manufacturing, the lot size is a technical consequence, e.g. limited by the amount of incoming mass.
• In the continuous manufacturing mode, batch and lot sizes are decoupled from such constraints.
• The batch size (and run times) can now be based on the size of each order, balancing acceptable business risk and effectiveness.
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State of Control Operation
Key characteristics: Material collection in state of control operation Events are basis for flagging and diversion decision Divert material at the appropriate point of the CM process
State of Control Operation
State of Control Operation
even
t Lot 1 Lot Lot N
t
t = 0 Start up
waste
Lot
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Control Strategy
Multiple points assess state of process Primary objective: verification of robust operation, but
allow feedback and feedforward loops, if required
Mixing & Granulation
API
Feeder
Excipients
Drying Sieving Tableting
LOWAPI
LOD (NIR)
BU (NIR)
Feeder
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Continuous Monitoring Automation and Big Data
Data collection • CPPs • Parameters that
influence process performance
• CQAs • PAT • Events • Room monitoring
Process Control System
State of Control Operation
Release
Data evaluation
Data Storage
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Batch Release
Material collection in state of control operation Material from events or deviations diverted / segregated Deviations investigated and closed Batch records reviewed Process data, IPC, PAT, room, and media data meet requirements Final product attributes characterized or RTRT done
Ramp down
State of Control Operation
Lot 1 Lot N
t t = 0
Start up
Lot 2
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Continuous verification occurs over the lifecycle of a product:
Validation Approach: Continuous Verification
Product and process
understanding
Continuous quality monitoring
and control
Process performance evaluation
Acceptance and release
Continuous process
improvement
Based on the large amount of data generated until and including process performance qualification (PPQ), no classical validation batches will be manufactured. The continuous performance verification shall be used as an alternative validation approach.
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Lifecycle Approach: DoE – CpV – Routine
GMP
Pharmaceutical Development
Commercial Manufacturing Discontinuation
Investigational products
DoE & process verification
Continuous Performance Verification
Product & process understanding
System
Equipment Room Media
People Training
Quality Culture
Continuous Improvement
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Unique Considerations Regulatory
Regulatory expectations
Dossier content
GMP vs. dossier
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Regulatory considerations
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Regulatory dossier content Goals
Provide sufficient transparency of development work and decision-making
Demonstrate product, process, control understanding
Identify and manage risk
Sufficiently express the control strategy
Facilitate compliance and lifecycle management
Optimize change control
Ensure quality
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Regulatory dossier content CM Considerations
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More sophisticated systems and controls
• Measurement frequency and traceability based on system dynamics
• Measurement nodes may cover multiple material transformation steps
• PAT with feed-forward/feed-back control • Modeling and multivariate analyses are likely to play a role
Adapting batch size (e.g., run time) through continuous performance verification is anticipated
Some CTD modules will differ, especially for an end-to-end continuous process
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Manufacturing Process Description
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• Unit operation typically defines equipment type, operating principle, capacity • Blending: blend specified quantities of ingredients for x revolutions • Wet granulation: granulate for x minutes at an impeller speed of x rpm and a spray rate of x
g/min • Drying: inlet air temperature of x°C at x m3/min until a product temperature of x°C is reached • Compression: compression force of x kN with a dwell time target of x ms • Measure x material attribute at x measurement node (may include frequency, e.g., compression
or endpoint, e.g., drying)
Batch
• Unit operation sequence defined with associated material transformation principles • Mass flow rate of x kg/hour with ability to adapt at constant residence time, constant residence
time distribution, and constant material transformation conditions to larger-scale equipment • Blending: Mean residence time of x sec with associated residence time distribution • Wet granulation: Mean residence time of x sec with associated residence time and temperature
distribution • Drying: Mean residence time of x sec with associated residence time at inlet air temperature of
x°C and flow rate of x m3/min/kg material • Compression: compress at x kN at a dwell time of x ms • Measure x material attribute every x minutes at x measurement node
Continuous
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CTD Module 3 Complete End-to-end Process
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S1 - General information
S2 - Manufacture
S3 – Characterization
S4 – Control of DS
S5 – Reference Standard
S6 – Container Closure
S7 - Stability
P1 – Description & Composition
P2 – Pharmaceutical Development
P3 - Manufacturers
P4 – Control of Excipients
P5 – Control of DP
P6 – Reference standard
P7 – Container Closure
P8 - Stability
S1 DS properties from a non-commercial batch synthesis, not the commercial CM process
S2 CM manufacturing process provided in P3 Control of materials provided in P4
S3 Characterization from batch synthesis, not CM (see S1)
S4 N/A – DS not isolated or released
S5 N/A – Addressed in P6
S6 N/A – DS not isolated or packed
S7 N/A – DS not isolated or stored
P1 Description & Composition
P2 Includes elements of DS synthesis
P3 Includes information on DS and DP
P4 Includes DS solvents, reagents, etc.
P5 Integrated DS and DP specification
P6 Reference standard
P7 Container Closure
P8 Stability
Current structure CM structure
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Ultimate goals
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Batch manufacturing is not continuous manufacturing...
We will need: • Open mind
• Batch mode approach is not directly superimposable • Unique considerations for CM
• More dialogue to align expectations • Additional Points to Consider or Q&A
• Science-based and risk-based approaches • Flexibility
• Product-specific and company-specific approaches
• Global acceptance The overall goal is the optimal usage of continuous manufacturing technology to assure quality with maximum flexibility and effective oversight
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Commercial Application
Where are we today? Continuous Manufacturing Journey
2017
Technical Feasibility
Scientific Principles
Broad Acceptance?
Prototypes
Thank you