Continuous Manufacturing: An Industry View -...

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

Novartis Pharmaceuticals

FDA/PQRI Conference March 2017 2

Commercial Application

Where are we today? Continuous Manufacturing Journey

2017

Technical Feasibility

Scientific Principles

Broad Acceptance?

Prototypes




2017



Broad Acceptance?

Prototypes

FDA/PQRI Conference March 2017

Where are we today? Conferences

4

Discussions on CM as new technology Created sound business justifications Discussed scientific principles Identified challenges Shared experiences


Where are we today? Publications

5

Some of the publications...


Where are we today? Expertise

6

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


Where are we today? Regulatory Landscape

ICH

• Q8, Q9, Q10, Q11

FDA

• DRAFT Guidance: Advancement of Emerging Technology Applications to Modernize the Pharmaceutical Manufacturing Base

• Other Guidances

EU

• Good Manufacturing Practice, Annex 15: Qualification and Validation

• Good Manufacturing Practice, Annex 17: Real Time Release Testing

• Process Validation • Real-time release testing

7

• Existing framework supports CM approaches • No specific regulatory barriers exist


Where are we today? Approved Products

8

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


Quality Systems

and Controls

Scientific

and Engineering Principles

Regulatory Guidelines, Guidances,

and Directives

Where are we today? Current framework

9

Existing framework supports CM


But...

10

Batch manufacturing is not continuous manufacturing...


What is unique to consider? Some Considerations

Regulatory Regulatory

expectations and

Dossier content

Flexibility and flexible approaches

Quality

State-of-control operation

and batch release

Process validation/verification

approach

Technical

Control strategy complexity

Spectrum of implementation

approaches

11


Novartis Continuous Manufacturing

Ultimate Goal: Complete end-to-end Process

12

Reaction Work-up Crystalisation Filtration Granulation Drying Tabletting Coating

raw materials drug product


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

13

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


Quality in space and time, random scatter Simulated data, normalized space and time, 500 mg assay

CM mode Batch mode random inhomogeneity ↔ random noise

14

Swapping space axis and time axis allows translation of quality metrics from batch processing to CM processing.


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

Parameters: temperature, residence time, catalyst/ligand loading, solvent composition, ionic strength, pH

J.P. McMullen and K.F. Jensen, Annu. Rev. Anal. Chem. 3, 19–42 (2010). Org. Proc. Res. Dev. 14, 1169–1176 (2010)

15


A reactor, a sensor, system response

Conjugate Gradient Steepest Descent

• Variety of optimization techniques • System performance is critical

16

O

O

2,5-hexanedione

NH2OH

ethanolamine

+ NOHDMSO


Example: Dryer in “state of control”

Perfect agreement with step data

Razor-sharp process appears poor

6 min

Apparent dispersion of CQAs is in reality instable process

Affects observed process capability

17


Example: Dryer in “state of control”

18

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

Batch it

Backmix

Optimal control


Options for process control

Add Backmixing Creates apparent homogeneity potentially outlier product is included

Batch it

Truncate, divert Creates real homogeneity, yield lower

Apply active control Creates real homogeneity, yield high

19

Evaluating overall performance and process performance matters!


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


Sample rate of CPPs/CQAs/IPCs reflecting material characteristics and process dynamics

Qua

lity

para

met

er

Minimum sampling period

This is what we need to avoid and discard

USL

LSL

UAL

LAL

Usable material

Usable material

Safety buffer

• 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

Time axis

21

Understanding process dynamics (rate of change) and process sensitivity allows to set the frequency of observation/sampling/measurement


Unique Considerations Quality

Definition of a batch

State of control operation

Control strategy Batch release

Validation approach

22

Quality considerations


Batch Definition 21 CFR 210.3

2) 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


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.

Batch Definition EU

24


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


State of Control Operation

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



even

t Lot 1 Lot Lot N

t

t = 0 Start up

waste

Lot

26


Control Strategy

Multiple points assess state of process Primary objective: verification of robust operation, but

allow feedback and feedforward loops, if required

Mixing & Granulation

API

Feeder

Excipients

Drying Sieving Tableting

LOWAPI

LOD (NIR)

BU (NIR)

Feeder

27


Continuous Monitoring Automation and Big Data

Data collection • CPPs • Parameters that

influence process performance

• CQAs • PAT • Events • Room monitoring

Process Control System


Release

Data evaluation

Data Storage

28


Batch Release

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

Ramp down


Lot 1 Lot N

t t = 0

Start up

Lot 2

29


Continuous verification occurs over the lifecycle of a product:

Validation Approach: Continuous Verification

Product and process

understanding

Continuous quality monitoring

and control

Process performance evaluation

Acceptance and release

Continuous process

improvement

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


Lifecycle Approach: DoE – CpV – Routine

GMP

Pharmaceutical Development

Commercial Manufacturing Discontinuation

Investigational products

DoE & process verification

Continuous Performance Verification

Product & process understanding

System

Equipment Room Media

People Training

Quality Culture

Continuous Improvement

31


Unique Considerations Regulatory

Regulatory expectations

Dossier content

GMP vs. dossier

32

Regulatory considerations


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


Regulatory dossier content CM Considerations

34

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


Manufacturing Process Description

35

• 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 m3/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)

Batch

• 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 m3/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

Continuous


CTD Module 3 Complete End-to-end Process

36

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

S1 DS properties from a non-commercial batch synthesis, not the commercial CM process

S2 CM manufacturing process provided in P3 Control of materials provided in P4

S3 Characterization from batch synthesis, not CM (see S1)

S4 N/A – DS not isolated or released

S5 N/A – Addressed in P6

S6 N/A – DS not isolated or packed

S7 N/A – DS not isolated or stored

P1 Description & Composition

P2 Includes elements of DS synthesis

P3 Includes information on DS and DP

P4 Includes DS solvents, reagents, etc.

P5 Integrated DS and DP specification

P6 Reference standard

P7 Container Closure

P8 Stability

Current structure CM structure


Ultimate goals

37

Batch manufacturing is not continuous manufacturing...

We will need: • Open mind

• 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




2017



Broad Acceptance?

Prototypes

Thank you

Continuous Manufacturing: An Industry View -...

Documents

Transcript of Continuous Manufacturing: An Industry View -...