Process Validation of a Multi-SKU Drug Product Kevin Maloney, PhD Biogen, Technical Development, Cambridge, MA

Transcription

1 Process Validation of a Multi-SKU Drug Product Kevin Maloney, PhD Biogen, Technical Development, Cambridge, MA CASSS CMC Forum, DP Validation, July 2016, Gaithersburg, MD 1

2 Multi-SKU, Weight-Based, DPs Versus Fixed Dose DPs: More to Contend with in Lifecycle Approach to Validation SKU = defined here as a single dose contained in one container Fixed Dosing Weight-Based Dosing Example Weight (kg) Delivered Volume (ml) of for Fixed Versus Weight (kg) Fixed Concentration (e.g., 150 mg/ml) Fixed Container Size (e.g., 5 ml) 1X mg/kg 10X mg/kg 1X mg/kg 10X mg/kg One Container, One Strength, One Fill Target N = 3 PPQ ml required for 70 the full dose level range Multiple DP fill volumes 100 required for single strength N = Bracketed PPQ Min. 2 doses required Potential lifecycle issues with weight-based DPs: Improper # of SKUs and fill targets can encourage dose -splitting and impact COGs Number of SKUs can complicate Design/PPQ Activities, DP design work can mushroom Bracketed stability design and expiry management Label/pack can further expand finished goods configurations Significant resource burden for DS/DP Mfg changes (Changes, or New Sites) 2

3 Weight-Based DPs: Leverage Science to Select Design Elements to Control Complexity Case Study Fully formulated DS at the highest expected DP dose strength helps maintain flexibility Eliminates the need for DP compounding unit operations. Single-concentration, varied fill volume approach can help simplify with process and stability control strategies For well-formulated proteins, concentration will drive stability. Expect a reasonably broad, dose-independent stability profile. Aside from fill weight controls, enables a common, dose-independent, process-wide control strategy to be developed Enables future lifecycle options for alternate routes of delivery Benefits of approach are more apparent for large # of doses Maximize DS utilization, minimize DP leftover volumes 3

4 Expected Stability Outcomes: Constant Strength vs Constant Volume Vary fill volume, same conc. Vary concentration, same fill vol. Stability Stability Lowest Vol. Highest Vol. Lowest Conc. Highest Conc. Would expect very limited or no impact of fill volume on stability for the same formulation matrix and product concentration Contrast to same matrix but with different product concentrations; expect regions of similar stability but overall trend towards decreasing stability Design of pre-validation activities will inform the likelihood of this approach Managing a varied stability profile more complex situation to manage overall 4

5 Stage 1 Design Stage 2 - Qualify Stage 3 - Verify Case Study: Stage 1 and 2 Lifecycle Strategy File ICH Stage 1/Design Stage 2/PPQ markets Follow-on Site PPQ Pre-Launch Line Commercial Launch Line Post-Launch, New DS/DP Sites File ICH, Global Dose Selection Knowns: 2 or more ISO vial container sizes, 6-8 DP doses, same formulation, same concentration, vary fill volume per dose, use of a platform fill-finish process Challenges: Process and stability design work being performed on Pre-Launch line in commercial DP facility. PPQ to be performed on Launch Line in same facility. Both lines considered equivalent. Dose selection could vary 10-fold, may need to initiate PPQ prior to final dose selection Expecting 2 or more manufacturing sites to meet global supply demands What enables this approach? What are the risks? 5

6 Stage 1 Enablers: Stability Bracketing on Line 1 Fill-finish platform established on Pre-Launch Line Stage 1 Design Stage 2 - Qualify Stage 3 - Verify Weight (kg) Delivered Volume (ml) of X mg/ml strength 1X mg/kg 10X mg/kg ml required for the full dose level range Multiple DP fill volumes required for individual doses (eg, 150 mg/ml) Container 1: 2 fill targets (smallest doses) Container 2: 6 fill targets (largest doses) 6 of the 8 doses intermediate doses Stability Bracketing (reduced design per ICH Q1D): N=3 coverage for extreme conditions ; process & stability (bracket ends) Factors: Surface/Vol, Headspace/Vol, Stopper area/volume, etc. One lot each for the 6 intermediate doses, multiple DS batches to be used to evaluate risk of DS variation on DP stability 12 ICH studies from pre-launch Line to establish stability bracket ahead of PPQ on Launch Line. For PPQ & follow on-sites, how long do you continue repeating brackets? Stability and bracketing is also a significant issue for other non-ich adopters. 6

7 Stage 1 Design Stage 2 - Qualify Stage 3 - Verify Stage 1 2 Enablers: Process and Facility Platform process with prior knowledge of antibodies ( mg/ml) Pre-Launch vs Launch Line: shared technologies, equivalent capabilities Both lines in the same facility risks of transfer will be documented Raw materials will be identical. Control strategy will be the same. Goal with successful transfer, and comparability package is leveraging of stability data from Pre-Launch to PPQ/Launch material Mitigates launch risks of limited PPQ stability data availability at time of BLA/MAA filing 7

8 Stage 1 Design Stage 2 - Qualify Stage 3 - Verify Stage 2 PPQ: 12 runs for 8 SKUs SKU: Lowest to Highest dose SKU 1 (lowest dose) Container Size: A or B PPQ Run s CCI val. Stability Lots Batch Size Hold Time A 3 Y 3 1 max Max (2) SKU 2 A 1 N 1 SKU 3 B 1 N 1 SKU 4 B 1 N 1 SKU 5 B 1 N 1 SKU 6 B 1 N 1 SKU 7 B 1 N 1 SKU 8 (highest dose) B 3 Y 3 1 min Max (1) PPQ approach mirrors strategy started from Pre-Launch line 3 runs at both best/worst-case process & stability conditions: 6 runs including hold time, batch size and CCI validation activities. 1 PPQ run for each of the intermediate strengths Issues/Risks for Intermediate SKUs and non-ich markets. Requirements for complete, non-bracketed data sets. Contrasts greatly with bracketing approaches for ICH-regions, highly impactful to drug development and filing process. 8

9 Stage 1 Design Stage 2 - Qualify Stage 3 - Verify Follow On DP Mfg Sites; Leveraging Site 1 Prior Knowledge for Risk-Based Site 2 PPQ Site 1: PK = 24 stab lots, 12 PPQ runs Site 2; N =? PPQ runs SKU: Lowest to Highest dose SKU 1 (lowest Container Size: A or B PPQ Runs CCI val. Stability? A 3 Y Y (3) dose) SKU 2 A 1 N Y SKU 3 B 1 N Y SKU 4 B 1 N Y SKU 5 B 1 N Y SKU 6 B 1 N Y SKU 7 B 1 N Y SKU 8 (highest dose) B 3 Y Y (3) Batch Size 2 max/1 min 1 max/2 min Hold Time Max (3) Max (3) SKU: Lowest to Highest dose SKU 1 (lowest dose) SKU 2 SKU 3 SKU 4 SKU 5 SKU 6 SKU 7 SKU 8 (highest dose) Container Size: A or B PPQ Runs CCI val. Stability? A 3 Y 3 A B B B B B B 3 Y 3 Batch Size Hold Time Validate at site 2 focusing on risks (CCI, 6 runs across 2 containers): Same platform process & control strategy, no new facility, raw material or equipment risks 9

10 Bracketing and Risks Don t assume you can bracket Establish it: Stage 1 can drive PPQ scope of work, or establish in Stage 2 for follow on sites Change in dose after Stage 2 initiation to either widen or narrow the initial bracketing Narrowing No technical impact to state of validation of the process, nor any impact on stability, still within your bracket What is the regulatory risk? The original high & low SKUs at time of filing will not be marketed. The new bracket data set is not n=3. Widening To either higher or lower dose SKUs A more impactful technical and regulatory issue, you have exceeded the bracket 10

11 Summary Validation concept for a high volume, multi SKU DP requires effective use of bracketing, identification of best/worst case process and stability conditions, and leveraging of prior knowledge should be used for follow on manufacturing sites. Design elements can be chosen ahead of time to minimize complexity for multi-sku DPs Stage 1 activities are opportunities to assemble significant knowledge space information on the process and establish stability profiles well ahead of PPQ stage This equates to significant reduction in risk at both initial and follow-on DP sites. Due to risk being low (Stage 1 and Stage 2 prior knowledge), follow-on site Stage 2 activities should be feasible under reduced protocols, scope, and filing burden. 11

12 Acknowledgements Biogen colleagues: Technical Development: Curtiss Schneider, Steve Lantz, and John Ruesch Quality Stability: Brian Nunnally, Philip Pue-Gilchrist Regulatory: Kimberly Wolfram 12