Continuous Manufacturing: An Industry View

Transcription

1 Novartis Pharmaceuticals Continuous Manufacturing: An Industry View Diane Zezza Novartis Pharmaceuticals FDA/PQRI Conference on Advancing Product Quality March 22, 2017

2 Where are we today? Continuous Manufacturing Journey 2017 Broad Acceptance? Commercial Application Technical Feasibility Prototypes Scientific Principles 2

3 Where are we today? Continuous Manufacturing Journey Broad Acceptance? 2017 Commercial Application Technical Feasibility Prototypes Scientific Principles 3

4 Where are we today? Conferences Discussions on CM as new technology Created sound business justifications Discussed scientific principles Identified challenges Shared experiences 4

5 Where are we today? Publications Some of the publications... 5

6 Where are we today? Expertise 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 6

7 Where are we today? Regulatory Landscape Existing framework supports CM approaches No specific regulatory barriers exist ICH FDA EU Q8, Q9, Q10, Q11 DRAFT Guidance: Advancement of Emerging Technology Applications to Modernize the Pharmaceutical Manufacturing Base Other Guidances Good Manufacturing Practice, Annex 15: Qualification and Validation Good Manufacturing Practice, Annex 17: Real Time Release Testing Process Validation Real-time release testing 7

8 Where are we today? Approved Products 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 8

9 Where are we today? Current framework Scientific and Engineering Principles Quality Systems and Controls Regulatory Guidelines, Guidances, and Directives Existing framework supports CM 9

10 But... Batch manufacturing is not continuous manufacturing... 10

11 What is unique to consider? Some Considerations Regulatory Quality Technical Regulatory expectations and Dossier content State-of-control operation and batch release Control strategy complexity Flexibility and flexible approaches Process validation/verification approach Spectrum of implementation approaches 11

12 Novartis Continuous Manufacturing Ultimate Goal: Complete end-to-end Process raw materials drug product Reaction Work-up Crystalisation Filtration Granulation Drying Tabletting Coating 12

13 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 Integrated thinking is critical: Process design, process control, process dynamics 13

14 Quality in space and time, random scatter Simulated data, normalized space and time, 500 mg assay Batch mode 14 random inhomogeneity random noise Swapping space axis and time axis allows translation of quality metrics from batch processing to CM processing. CM mode

15 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 J.P. McMullen and K.F. Jensen, Annu. Rev. Anal. Chem. 3, (2010). Org. Proc. Res. Dev. 14, (2010) Parameters: temperature, residence time, catalyst/ligand loading, solvent composition, ionic strength, ph 15

16 A reactor, a sensor, system response O O 2,5-hexanedione OH + NH 2 N DMSO ethanolamine OH Steepest Descent Conjugate Gradient Variety of optimization techniques System performance is critical 16

17 Example: Dryer in state of control 6 min Perfect agreement with step data Razor-sharp process appears poor Apparent dispersion of CQAs is in reality instable process Affects observed process capability 17

18 Example: Dryer in state of control Optimal control Batch it Backmix 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 18

19 Options for process control Batch it Add Backmixing Creates apparent homogeneity potentially outlier product is included Truncate, divert Creates real homogeneity, yield lower 19 Apply active control Creates real homogeneity, yield high Evaluating overall performance and process performance matters!

20 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 20

21 Sample rate of CPPs/CQAs/IPCs reflecting material characteristics and process dynamics Minimum sampling period Safety buffer Quality parameter Usable material Usable material This is what we need to avoid and discard Time axis USL UAL LAL LSL 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 21 Understanding process dynamics (rate of change) and process sensitivity allows to set the frequency of observation/sampling/measurement

22 Unique Considerations Quality Definition of a batch State of control operation Control strategy Batch release Validation approach Quality considerations 22

23 Batch Definition 21 CFR ) 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. 23

24 Batch Definition EU 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. 24

25 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. 25

26 State of Control Operation t t = 0 Start up State of Control Operation event State of Control Operation Lot 1 Lot Lot Lot N 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 26 waste

27 Control Strategy API LOW API Excipients BU (NIR) LOD (NIR) Feeder Feeder Mixing & Granulation Drying Sieving Tableting Multiple points assess state of process Primary objective: verification of robust operation, but allow feedback and feedforward loops, if required 27

28 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 Data Storage Data evaluation Release 28

29 Batch Release t = 0 Start up State of Control Operation Ramp down t Lot 1 Lot 2 Lot N 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 29

30 Validation Approach: Continuous Verification Continuous verification occurs over the lifecycle of a product: Continuous process improvement Acceptance and release Product and process understanding Continuous quality monitoring and control Process performance evaluation 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. 30

31 Lifecycle Approach: DoE CpV Routine Pharmaceutical Development Commercial Manufacturing Discontinuation Investigational products DoE & process verification Continuous Performance Verification GMP Continuous Improvement System Product & process understanding Quality Culture People Training Equipment Room Media 31

32 Unique Considerations Regulatory Regulatory expectations Dossier content GMP vs. dossier Regulatory considerations 32

33 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 33

34 Regulatory dossier content CM Considerations 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 34

35 Manufacturing Process Description Batch 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 m 3 /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) Continuous 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 m 3 /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 35

36 CTD Module 3 Complete End-to-end Process 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 36 Current structure S1 S2 DS properties from a non-commercial batch synthesis, not the commercial CM process CM manufacturing process provided in P3 Control of materials provided in P4 S3 Characterization from batch synthesis, not CM (see S1) S4 S5 S6 S7 P1 P2 P3 P4 P5 P6 P7 P8 N/A DS not isolated or released N/A Addressed in P6 N/A DS not isolated or packed N/A DS not isolated or stored Description & Composition Includes elements of DS synthesis Includes information on DS and DP Includes DS solvents, reagents, etc. Integrated DS and DP specification Reference standard Container Closure Stability CM structure

37 Ultimate goals Batch manufacturing is not continuous manufacturing... We will need: Open mind 37 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

38 Where are we today? Continuous Manufacturing Journey Broad Acceptance? Commercial Application Technical Feasibility Prototypes Scientific Principles

39 Thank you