Implementation Activities for QbD: FDA Office of Biotechnology Products

WCBP CMC Strategy Forum QbD for Biologics Bethesda, MD 7/19/2010

Steven Kozlowski, Director Office of Biotechnology Products OPS, CDER

Quality by Design

• A systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management (ICH Q8R) • QbD concepts apply to complex products • Implementation strategy may differ – Product heterogeneity may complicate the definition of the CQAs – Processes are often also more complex, with multiple interactions

Potential Benefits for Embracing QbD

• Smoother transitions from IND to Licensure • Increase productively/efficiency • Less lot rejections, recalls, and investigations for manufacturing deviations • Expedited implementation of process changes • Manufacturing processes that are adaptable •

Reliable supply of high quality products

• Fewer inspections • Fewer submissions to the Agency

QbD Implementation

• • • Link to small-molecule learnings – ONDQA pilot and application experience • ICH IWG, Q8R, Q9, Q10 • ICH Q11 • OBP staff participating in conferences, forums and training on QbD – Design of Experiments Training

Mock Case Studies OBP Pilot

Biotech QbD Mock Case Studies

• EFPIA drafting a case study • Industry CMC Biotech Working Group Publishes a QbD Case study (10/31/09) – A-Mab: a Case Study in Bioprocess Development Abbott, Amgen, Eli Lilly & Company, Genentech, GlaxoSmithKline, MedImmune, and Pfizer – Available on the ISPE Website Nov 2009 Workshops on case study planned (ISPE & CASSS) – 278 pages

not….

• A template for a QbD submission • A definitive source of regulatory definitions & terminology • The final ideal scientific approach to biotech QbD

A Mab is … but it can be….

• A source of challenging, well thought out examples • The basis for discussions and forums likely to contribute to QbD implementation • A tremendous effort by Ken Seamon, John Berridge and the top scientific talent of multiple companies – Thanks to Anjali Katarina & Conformia

ICH Q8R: Design Space

• Definition – The multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality • Regulatory Flexibility – Working within the design space is not considered a change • Important to Notice – Design space is proposed by the applicant and is subject to regulatory assessment and approval

pyro-E O D D O G D G

Many Attributes

O D D G O D pyro-E G K K •

(9600) 2 ≈ 10 8

• Biological Studies – In vitro – Animal – Clinical • Prior Knowledge – Platform Risk Assessment & Ranking Approaches Good Science

From Attributes to Spaces

FMEA • Assign relative risk for each factor = [severity] x [occurrence] x [detectability]

Risk assessment includes process develop., manufact., QC staff, etc.

& trained facilitator

Severity • Risk Ranking • Screening DOE • Optimization • Process Characterization

Contour Profiler

A-Mab Design Space Based on

Current X Horiz Vert Factor

Temperature (C) 35 pH [Medium] (X) Osmo (mOsm) 50 40 6.85

1.2

360 Feed (X) 12 Example: Day 15, Osmo=360 mOsm and pCO2=40 IVCC (e6 cells/mL) 1 15

Response

Titer (g/L) aFucosylation Galactosylation (%) HCP (ppm) DNA (ppm) CEX % Acidic Variants

Contour

3 11 40 675000 2250 40

Current Y

5.3408326

9.1879682

38.227972

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1382.1644

34.420095

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>99% confidence of satisfying all CQAs 7.1

aFucos >11%

7 6.9

7.05

7 6.95

0 .2

5 6.9

0.9

5 0 0.

.8

7 0 .9

9 0 .5

0.9

0.9

5 0.9

9 0.99

pH 6.8

Galactosylation (%) 6.8

0.5

0.25

0.95

0.99

0.9

0.8

0.7

0.5

0.95

0.9

0.8

0.7

0.5

aFucosylation pH 0.25

0.25

6.75

Galact >40% 6.7

6.7

6.6

34 34.5

35 35.5

36 6.65

6.6

34 34.2

34.4

34.6

34.8

35 35.2

Temperature (C) 35.4

35.6

35.8

36 10

pH Load Conductivity

Critical Process Parameters (CPP)

•

Critical Process Parameter (CPP):

A process parameter whose variability has an impact on a critical quality attribute and therefore should be monitored or controlled to ensure the process produces the desired quality. (ICH Q8(R2))

What else is in the Design Space?

• Are only CQAs used to defining Design Space?

Acidic variants used in A-Mab Production Bioreactor • Are only CPPs used in a design space?

• A CPP is a function of the range evaluated (either experimentally or through prior knowledge) 5 o C 40 o C CPP 15 o C KPP 25 o C 18 o C 22 o C GPP

5 o C Can a Design Space be larger than the Knowledge Space?

Fundamental Models

15 o C 18 o C

Experiments

25 o C

Prior Knowledge

22 o C 40 o C

No failures seen; Models, Prior Knowledge & Experiments show interactions are unlikely

If not included in the Design Space (not a CPP), is the Design Space infinite for that parameter?

Temperature Cycle # pH Load Conductivity

Design

–

Space

The multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality

Equilibration pH

Initial Design Space Weaknesses

• Based on model (DOE) – Predictions are extrapolations • inside as well as outside explored space • Missed factors • Missed interactions at screening – Each factor alone has little impact – Larger risk with complex processes – A-Mab interaction risk score is of value • Missed important responses – Larger risk with complex products – Interactions between responses • Experiments done at lab scale

Lifecycle Approach

• Managing uncertainty –

Complex products

–

Complex processes

–

1st Prin. Models rare

• Multivariate SPC –

Facilitates moving across scales

Load

Adapted from T. Kourti

Dimensionless Variables Engineering Approaches To Modeling pH

A-Mab Engineering Design Space

Design Space for scale independent parameters was developed using qualified scale down models Design Space applicability to multiple operation scales demonstrated using PCA/MVA models

500 L – 25,000 L Al l 2L Scale

Includes bioreactors of multiple scales and designs (2L -25K L)



Based on keeping microenvironment experienced by cells equivalent



between scales Includes bioreactor design considerations and scale-dependent process parameters linked to fluid dynamics and mass transfer

Can a Design Space Specify Evaluation Methods & Criteria ?

Designing Spaces

Fixed equipment, scale, etc.

Load pH Conductivity Moving within the Design Space Control Strategy (CS) & Quality System (QS): Evaluation beyond CS not filed

Fixed resin characteristics & methodology; Scalable

Load pH Evaluation and criteria beyond routine CS filed

Adaptive Control Strategy

Control Strategy definition from Q10

• Control Strategy: A planned set of controls,

derived from current product and process understanding

, that assures process performance and product quality. • The controls

can include parameters and attributes

related to drug substance and drug product materials and components, facility and equipment operating conditions, in-process controls, finished product specifications,

and the associated methods and frequency of monitoring and control

.

Designing Spaces

Flexible methodology & Scale

Non-ionic Interactions Design Space Charge Separation Working within the design space is not considered a change Moving within the Design Space QS: evaluation and criteria beyond SC filed; Change reported (e.g. AR) Use of Expanded Change Protocol or Post-market Management Plan

OBP Pilot Program

FR Notice July 2, 2008

• To define clinically relevant attributes for protein products (regulated by OBP) and link them to manufacturing processes • To consider quality-by-design (QbD) approaches to unit operations in supplements (10) as well as original applications (5) • To explore the use of protocols submitted under (21 CF 314.70(e) and 601.12(e)) • Notice of Extension of Deadlines and Increase in the Number of Original Applications to 8 – Federal Register/Vol. 74, No. 179 /Sep 17, 2009

Biotechnology QbD Pilot Status

• Applications Accepted in QbD Pilot – 5 Original Applications • 4 Monoclonal Antibodies and 1 Fc Fusion Protein – 4 Post-approval Supplements • 2 Monoclonal Antibodies, 1 Therapeutic Protein, 1 multi-product – 2 with site transfers; Working closely with Compliance • MAPP 4730.3 OBP & DMPQ Interactions on BLAs • OBP QbD Pilot Meetings – 6 meetings held with Pilot sponsors in 2009

QbD Pilot 2009 Meeting Questions

• 29 questions – Questions with subparts were counted separately if they covered a different set of QbD categories or topics • 25 associated only with Mabs – 4 included other therapeutic proteins • Question General categories – Design Space 13 – Risk Assessment Methods – Control Strategy 6 4 – Expanded Change Protocols 4 – Small-scale Models 3

QbD Pilot Meetings

• Typical Question – Here is our plan and some example data – Is this acceptable?

• Typical Answer – In principle YES… • but we will need to see that actual submission – Comments on clarifying ranges, scoring, definitions • Occasionally closer to NO (“Only” or “All”) – Only small scale stability on significant changes – ECP covering all changes

Design Space Comments

• Factor choices (e.g. raw materials) • Prior knowledge base • Appropriateness of the experimental design and statistical analysis • Impact of assay variability on design space • Viral clearance • Linkage to other steps • Claims for scale in design space • Protocols as part of a design space • CPPs alone do not define a design space-assurance of quality does • Limits for parameters that may not be critical parameters; Relationship to Design Space

2010 (Very) Preliminary Update

• 10 meetings total so far • 47 questions used for initial analysis – within a meeting some questions counted separately; some fused based on topics – monoclonal antibodies with some multiproduct – 4 companies for 5 pilot applications • 3 original: 2 supplements – Typical question; Typical Answer -- still true • Comments a bit more granular

Questions Per Meeting (Avg)

General Categories Risk Assessment Methods Design Space Scaled down models Expanded Change Protocols Control Strategy

0.00

1.00

2.00

2009 Meetings 2010 Meetings

Questions Per Meeting (Avg)

Neutral/Decrease Process characterization Model qualification Attribute criticality Viral Clearance

0.00

2009 Meetings 0.40

0.80

2010 Meetings 1.20

Questions Per Meeting (Avg)

Increase Parameter Criticality Scope Change Evaluation Strategy Regulatory Filings Inspection/Facility Experimental Design & Statistics

0.00

0.40

0.80

1.20

2009 Meetings 2010 Meetings

Topics

•

Design space & CPPs

– Review issue • • Details on criteria for ECP – Statistics; trend analysis • Complex risk tools for process –

Thresholds

– Linking product and process risks – Factors & details

Definitions

– –

Cannot be company specific Even ICH definitions need a shared commentary

•

CPPs

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NIR surrogate for ribbon density This process understanding may establish the independence of site, scale, and equipment.

Looking Forward

• Continue to learn from small-molecule QbD • ICH Q11 • Clarity on definitions • Reviewer Training – Risk Assessment – DOE • Mock Case Studies – Conferences • OBP Pilot • Get into the details

Credits

• Barry Cherney • Patrick Swann • Keith Webber • Susan Kirshner • Ken Seamon • John Berridge • Janet Woodcock • Helen Winkle • Moheb Nasr • Christine Moore • Jon Clark • Joe Kutza