Transcript Document 7549817

PAT for Biologics
Ensuring Quality of Biologically
Produced Drugs
FDA Advisory Committee on Pharmaceutical Sciences
April 13, 2004
Parrish Galliher and Elizabeth Fowler
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Outline
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Xcellerex View of PAT
Importance of PAT for Biologics
Value of PAT
Implementation of PAT – Xcellerex Program
Summary
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Xcellerex View of PAT
• Process knowledge gained through process
analytics and statistically designed process
optimization studies
• Processes designed for quality
• Continual monitoring ensures process control
• Risk based approach to quality; PAT provides
data
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Key Issues in Biologics
Production
• Biological variation in production of material
– Animal to animal variation
– Cell culture variation
• Biological safety – unknown pathogens
• Unrelated impurities with unknown activities
More
biological
variables
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Greater
need for
PAT
Product Risk Management
Present: Minimal process change allowed
Process parameters used as surrogates for
product quality monitoring
Release and some in-process testing used to
ensure product consistency
Future:
Real-time monitoring provides increased
assurance of process and product quality
consistency
Increased process understanding enables riskadjusted evaluation of process & product data
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Real-Time Process Monitoring
Biotechnology Drugs
Fermentation
Purification
Formulation
Fill Finish
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Purpose
Present
Future
Control
product quality
Cell growth
Cell viability
Metabolic parameters
(dO2, pH, glucose)
API content
API quality
Impurities
Bioburden & viruses
Process parameters
(OD, pH, Flow rate,
Conductivity)
API concentration
API quality
Impurity clearance
Bioburden & viruses
API concentration
Environment
Fill volume
API quality
Content uniformity
Excipient uniformity
Impurity levels
Sterility
Ensure
biosafety
Control product
quality
Ensure impurity
removal
Ensure biosafety
Ensure product
Ensure uniformity
Ensure safety
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Value of PAT for Biologics
• Ensure product quality remains consistent
• Assess deviation impact in real time
– Avoid costs of processing unreleasable batches
– Data justification of batch release
• Continual process monitoring obviates need for
process validation
• Reduce testing requirements at end of process
• Increase process knowledge
– Identify critical steps and parameters that
impact quality
– Improve risk assessment validity
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Manufacturing Investment Risk
• Savings via On-Line Bioburden QC
– Assumptions:
 20 batches attempted/year
 $20,000,000 annual budget, fully loaded
 $1,000,000 cost per batch, fully loaded
 90% overall batch success rate – 18 batches
– Cost of lost batches: $2,000,000/year
Possible savings via on-line fermentation
bioburden: $1,000,000/year
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Xcellerex PAT Program
Process Development & Analytics
Program Initiative
• Process Development
– Automation - High throughput
screening
– Statistical process
optimization
Benefit
• Optimized process from start
of clinical manufacturing
• Examine more parameters in
less time
• Process Analytics
– Product Quality – microarray
glycosylation analysis
– Process control via noninvasive sensors – pH, DO2,
optical density, IR
– On-line environmental
monitoring – non-viable
particulates
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• Real time assessment of
product quality
• Non-invasive monitoring of
process parameters
• Real-time assessment of
environmental control
Xcellerex PAT Program
Manufacturing
Program Initiative
• Automation
– Electronic batch records
– Non-invasive sensors – pH
and DO2
– On-line quality assurance
Benefit
• Controlled environment
modules
– Operator separation
• Minimize environmental
contamination
• Increase flexibility
• Disposables
• Minimize cross-contamination
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• Minimize operator errors
• Early detection of deviations
• Protect product quality
• Rapid batch release
Knowledge Management
eFactory™
MyProject
secure portal
Proj. Mgmnt
Supply Ops
Quality Control
Finance
Reg Affairs
•Contract
•Vendors
•Test Methods
•Contract
•FDA contact
•Phases
•Mat. flow
•Sample status
•Invoices
•IND outlines
•Your project
•Inventory
•Trending
•Accruals
•Submissions
eFACTORY™ Knowledge Management
•Data
•Batch data
•Doc Approvals
•Data
•Lot release
•Experiments
•Trending
•Doc Revisions
•Protocols
•Exceptions
•Methods
•BPRs
•Change control
•Methods
•Deviations
PD
Mfg
QA Documentation
Quality
QA Release
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Process Optimization by DOE
Figure 1. Quality Control Plot: Replicate Wells Ploted vs. Average of Wells
0.36
0.34
Factorial Rep 1
Factorial Rep 2
Center Pts
Sigma Media
Best condition: 1.9 MM
cells/ml
Cells still 94% viable!
OD of Replicates
0.32
0.3
Fractional
Factorial Wells
Center Point
Wells
Sigma Medium
Wells
256
20
12
0.281
0.305
0.323
3.7%
3.6%
7.6%
Approximate
Cell Density at
average OD600
(MM cells/ml)
1.2
1.5
1.7
CV based on
approximate
cell density, MM
cells/ml
10.2%
8.7%
17.0%
0.28
0.26
Number of
Wells
0.24
Average OD600
0.22
0.22
0.24
0.26
0.28
0.3
Average OD of Replicates
Normal MHB ~ 0.8 MM
cells/ml
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0.32
0.34
CV of OD600,
avg
0.36
Automation: eBatch Record
Purification
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Statistical Process Control
Step 1
Step 2
Step 3
Step 4
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Challenges in Applying PAT to Biologics
• Investment in bringing analytics on-line
• Innovation to develop analytical tools to assess
critical attributes
• Extensive data accumulation needed during
development to identify critical attributes and
appropriate limits
• Regulatory uncertainty
– More data may reveal more variation
– Stringency of limits related to criticality of impact
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Regulatory Risk with On-line Analytics
• Data
– How much data is too much data
– Collection interval - Continuous versus intermittent
– How to use the data – speeding release or real-time
release?
• Noise
– How to handle spurious spikes in continuous on-line
data
– May need extra validation to ignore these
Lost productivity, lower plant output, high mfg. costs
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Particulates ≥0.5 µ per ft3 (x 10-3)
Continual Environmental Monitoring
Total Particulates during Chromatography Step
1000
800
600
400
200
0
Summary
Impact of PAT
• Measure product quality in process stream
• Increased understand of process – product quality
relationship
• Continual process monitoring obviates need for process
validation
• Enables science-based decision making in manufacturing
• Reduces batch release time, increases plant capacity
• Lower manufacturing risk and COGS
• Can be a very cost effective investment
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Opportunity
Process Knowledge
Future
T
A
P
Present
Efficiency
Result: Better Quality & Lower
COGS for Entire Industry