PPQ-to-Approval Timelines—Acceleration Approaches at BMS

Marcus Boyer

Bristol-Myers Squibb

Associate Director

Process Life-cycle Management

Syracuse, NY

USA

Kristen Manchester

Bristol-Myers Squibb

Sr. Engineer

Drug Substance Process Champion

Syracuse, NY

USA

Discussion Points

• Distinction between continuous and ongoing or continued process verification

• How does continuous process verification differ from traditional process validation?

• Advantages and challenges of continuous process verification

• BMS case-studies: Departure from traditional process validation

2

Manufacturing Control Strategy

Critical Quality Attributes

Quality Target Product Profile

Process Reproducibility

Continuous versus Ongoing Process Verification

ContinuousProcess Verification

• An alternative approach to process validation in which manufacturing process performance is continuously monitored and evaluated. (ICH Q8)

Ongoing or ContinuedProcess Verification

• Assuring that during routine production the process remains in a state of control. (EU Draft Guideline on process validation for the manufacture of biotechnology-derived active substances and data to be provided in the regulatory submission) (FDA Guidance for Industry; Process Validation: General Principles and Practices)

3http://www.acdlabs.com/solutions

/pharma/verification_nmr/

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consultants.com/2014/10/stat

istical-process-control/http://vietnaminvestigat

ion.com/verification/

Traditional Process Validation (Eudralex Annex 15)

• Use of a minimum of three consecutive batches manufactured under routine conditions to confirm reproducibility during process performance qualification (PPQ) is generally considered acceptable.

• A process validation protocol should leverage development data or documented process knowledge to define:

• Critical quality attributes

• Critical process parameters

• Associated acceptance criteria

4

Continuous Process Verification (Eudralex Annex 15)

• Alternative approaches may be justified where the control strategy demonstrated that the process is capable of consistently delivering quality product with a high degree of assurance during development.

• The control strategy should define:

• Incoming materials

• Critical quality attributes

• Critical process parameters

• Regular evaluation of the control strategy

• Process Analytical Technology and multivariate statistical process control may be used as tools for verification.

5

Challenges of Continuous Process Verification

• Manufacturers and regulators share the goal of increasing the speed of getting drug to patients

• True continuous process verification may be difficult to implement, especially for accelerated programs due to:

• Limited time for process development and characterization

• Limited manufacturing experience to set meaningful statistical process control limits

• Maturity of data collection and monitoring systems

• Concurrent review and accelerated approval timelines may limit launch supplies

Process

Knowledge

+

Robust

Monitoring

Risk-Based

Continuous

Verification

Speed

to

Patients

Departure from Traditional Process Validation

• BMS has recently commercialized multiple molecules with “breakthrough” or “fast track” designation; working with Health Authorities on low-risk acceleration within the traditional framework

• Extension of risk-based acceleration begins to approach the continuous process verification paradigm

• A hybrid approach requires a substantial amount of product and process knowledge from manufacturing experience

• Use of platform technology to support development

• Widespread implementation of statistical process control program(s) for ongoing process verification

• Especially useful for post-commercial process and facility changes

7

CASE STUDY 1Equipment Grouping

8

BMS Case Study 1: Equipment Grouping

• BMS has submitted applications with process performance qualification (PPQ) data from a subset of bioreactors, plus equipment equivalency data.

• US approval of first such submission for a new facility resulted in post-marketing commitments to provide additional data.

• Data could have been monitored or reported under an ongoing process verification plan.

3x 1x

1x 1x

1x

1x

3x 1x

N/A N/A

1x

N/A

Risk-based

Approach

Equivalency:

• Design and installation data

• Operability data (temp profiles, addition volumes, kLa)

• Data from previous products

Traditional “n+2”

Approach: 8 PPQ

Runs

Grouping

Approach:

5 PPQ Runs

Extension of Equipment Grouping Strategy

• No requirement for all bioreactors, no replication within one train

• 8-lot campaign becomes 3, preserving the 3-lot paradigm

• Justification for this approach may be stronger when the facility has been previously qualified for other product(s)

3x 1x

1x 1x

1x

1x

1x 1x

N/A N/A

1x

N/A

Risk-based

Approach

Traditional “n+2”

Approach: 8 PPQ

Runs

Grouping

Approach:

3 PPQ Runs

Equivalency:

• Design and installation data

• Operability data (temp profiles, addition volumes, kLa)

• Data from previous products

CASE STUDY 2Prospective Capacity Expansion Planning

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BMS Case Study 2: Prospective Capacity Expansion Planning

• Manufacturing capacity expansion often necessary as demand grows

• Variations for expansion require significant time

• Initial file might be accelerated if the path to expansion is smoothed

• BMS proactively discussed within-site expansion with FDA during initial review

• FDA agreed to inspect manufacturing area not included in initial file

• Supplement was ready and agency expected submission as soon as initial approval was granted

http://www.bluearbor.com/blog/tag/fact

ory-workers-jacksonville-nc/

Extension of Proactive Capacity Expansion Planning

• Within-site expansion using continuous process verification

• Limit the scope of initial full-scale demonstration to speed completion

• Comparable equipment, people, and analytical tests across site

• Leverage ongoing process verification knowledge from statistical process monitoring program

• Approval based on a continuous process verification protocol would be low-risk

• Post-approval scale up or tech transfer using continuous process verification

• Example: launching at clinical scale speeds initial file

• Continuous process verification protocol for post-approval scale-up or transfer measured against clinical and launch lots

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ctory-workers-jacksonville-nc/

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CASE STUDY 3Risk-Based Stability Requirement

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BMS Case Study 3: Risk-based Stability Requirement

• Drug substance (DS) and drug product (DP) stability data often on the critical path for CMC file

• A year may pass between start of DS production and 6 month stability data http://www.binaryoptionswire.com/launching-risk-

based-supervision-framework-cysec/

• Especially for capacity expansion filings, stability profile may be well established and favorable

• Low risk that comparable DS material from new site will have a different stability profile

• Even lower risk that unchanged DP process will interact with new DS site to produce a different stability profile

• BMS submitted a new DS site without DP stability data

• Data collection in parallel with review

Extension of Risk-based Stability Requirement

• A comparable product has a low risk of a different stability profile

• Submit variation based on time zero data (release and characterization results)

• Example: No DS stability data at time of filing for DS site change

• No DP data

http://www.bigvisible.com/wp-content/uploads/2013/08/

Conclusions

• To accelerate approval of exciting new drugs, BMS has employed risk-based compression of traditional process validation data requirements.

• These modest departures remain within the current paradigm, but offer tangible timeline benefits.

• Further defendable options for acceleration exist which begin to approach the continuous process verification paradigm.