Efficient process development and robust manufacturing

Stefan Rännar, PhDSenior Application Specialist, Umetrics AB

Quality by Design (QbD) leads toCost Savings, Risk Mitigation, and more…

Process Optimization & Process Understanding

Critical Process Parameters Design Space

à Ease of process changes à Robust Manufacturing

Process Analytics

Sensors

SCADA DoE

MVDA

Yields & Titers à CoGs | R&D costs à Tech Transfer à Time to Market

•  DoE (Design of Experiments)–  Knowledge building tool for process development–  Product optimisation–  Critical Process Parameters–  Design Space–  Umetrics Software

•  MODDE

•  MVDA (Multivariate Data Analysis)–  Tool for process understanding and process monitoring–  Robust manufactoring–  Umetrics Software

•  SIMCA (offline modelling) •  SIMCA-online (online monitoring)

DoE and MVDA

Shake flasks

2 l fermentors

10 l fermentors

Pilot

Production

Use of DOE and MVDA, Example from Fermentation

“Design space”

On-line applications:Monitor Design space

DOE

MVDA

4

Umetrics, The Company•  The market leader in software for

multivariate analysis (MVDA) & Design of Experiments (DOE)

•  25+ years in the market•  Off line analysis tools•  On-Line process monitoring and fault

detection•  700+ companies, 7,000+ users•  Pharmaceutical, Biotech, Chemical,

Food, P&P, M&M, Semiconductors and more

•  Worldwide Presence with MKS (2006)•  Offices: USA: Boston MA, San Jose CA

Sweden: Umeå, Malmo UK: London, England Singapore China, Japan, Israel & More

•  Close collaboration with universities in USA, Sweden and Canada

•  All software are fully validated–  Software development and QA audited and approved by big pharmaceutical

companies on regular basis

•  World leading user friendly solutions for PAT and QbD–  More than 700 leading companies & organizations

•  World leading graphically driven software solutions–  More than 7000 users

•  World leading consulting, support and training services–  More than 15000 engineers, scientists and managers educated

•  Strong research cooperation with leading Chemometric research groups

Why Umetrics?

In-house training Open courses

Explore, analyze and interpret

For ensuring process quality

For easier DOE and QbD For embedded OEM

solutions

Design of Experiments (DoE)

MODDE Software

Motivation for Design of Experiments (MODDE software)

§  Key technology in Quality by Design (QbD) discussions REGULATORY §  Improve process understanding with a clear project scope KNOWLEDGE §  Increase manufacturing efficiency and lower production costs MONEY §  Speed up development of new therapeutics with less experiments TIME §  Statistically verified statements with graphical representation COMMUNICATION §  ... and many more

￭  “A structured, organized method for determining the relationship between factors affecting a process and the output of that process.” [FDA, Q8(R2)]

DoE – The Efficient Way of Experimentation

Random Approach Efficient Approach (DoE)  Intuitive Approach (COST)

§  Changing all factors arbitrarily

§  High number of experiments

§  Pure luck to find optimum

§  Changing One Single factor at a Time

§  High number of experiments

§  Only “quasi”-optimum can be found

§  Changing all factors at the same time according to a well designed plan

§  Perform least number of experiments

§  Optimum can be found

Design Space Estimation (and definition)

§  Probability plot illustrates risk of not meeting the specifications

Classical Contour Plot Design Space = Probability Plot

Three Typical DoE-Applications in Biotechnology Processing

Medium Optimization Parameter Optimization  Parameter Screening

¡  Optimization of the composition of growth and production culture media

¡  Screening of control parameters and basic process state variables

¡  Critical Process Parameters (CPP)

¡  Optimization of control parameters including feeding strategy

Page 28

DoE integrated with equipment – MODDE-Q

Multivariate Data Analysis (MVDA)

SIMCA software

13

INFORMATION

Multivariate data analysis (MVDA)

Converts data into informative plots

DATA

MVDA Objectives for the pharmaceutical & biopharmaceutical industry

•  Increase of process understanding–  Identification of influential process parameters–  Identification of process signatures–  Relationship between process parameters and quality attributes

•  Increase of process control–  Efficient on-line tool for

•  Multivariate statistical control (MSPC) •  Analysis of process variability •  Real time quality assurance

–  Online early fault detection–  Excellent tool for root cause, trending analysis and visualization–  Fundament for Continued Process Verification (CPV)

Developm

ent Production

Why Multivariate Analysis and Monitoring?

The information is found in the correlation pattern - not in the

individual variables!

Multivariate Monitoring

Multivariate Control Limits

MVDA - The Art of Compressing and Visualizing Information

Data

§  Post-batch MVDA enables easy interpretation and analysis of large process data sets

§  Find key trends, correlations, patterns and relationships from historical data

§  Improved process understanding & performance resulting in e.g. yield increase or impurity reduction

§  MVDA used for Continous Process Verification (CPV)

Multivariate Modeling

Information

File

ModelDBDBHistorical

dataMVDA offline

Model Generation

MVDA online Data Interpretation

DBDBProcess

data

offli

ne

onlin

e

historical

real-time

Multivariate Data Analysis for Continuous Process Verification

§  Build models offline to find key trends, patterns and relationships from historical data

§  Real-time process monitoring for quality control and early fault detection

What makes SIMCA-online so powerful?

•  Data from all relevant process parameters are condensed into a few highly informative variables–  Simplifies overview, analysis

and interpretation–  Enable use of data by

increasing ease of use

•  Early fault detection with simple drill-down functionality for analysis of root cause

•  Works for both batch and continuous processes

Early fault detection

§  SIMCA-online technology is acknowledged for its ability to detect process issues before they become critical

§  Full drill-down to raw data for cause analysis

§  Instant analysis of process changes improves understanding

§  Easy-to-grasp graphics makes the process status accessible to colleagues at all levels

Early Detection of Process Deviations with Guiding to Potential Root Cause

•  Biogen – fermentation monitoring applications.•  Novartis – tableting & bioprocess monitoring•  AstraZeneca – drug screening & production monitoring (packaging)

applications•  Tembec – production monitoring and product change-out optimization

–  Published savings of $1M per year•  Merck– SIMCA-online and SIMCA-Q for production monitoring and

PAT–  Published savings of $2M per year

•  PepsiCo – prediction of product quality•  GSK – real-time batch production monitoring•  DuPont – production monitoring•  Sunoco – Oil production monitoring•  IBM – Real-time monitoring of silicon chip wafer production

–  Published savings of $10M+ per year

Umetrics online references

Novartis: Root Cause Analysis and Parametric Release

•  Novartis is one of the largest Pharma companies in the world with drugs in a large amount of disease areas.

•  Presented by Marianna Machin and Lorenz Liesum at UUM in Frankfurt 2011

Customer Results / Benefits

•  Improved process consistency

• Enabled Root Cause Analysis

• Established key parameters for cell cultivation

Solution

•  Statistical process control i.e. SBOL/ SIMCA-online

• Validation of model •  Simulate an incident by

for example changing the flow rate of a pump.

Customer Business Challenge

• Established process, most of process understanding based on experience

• Root Cause Analysis and Statistical Process Control for Proof of specificity

Lonza: Multivariate Online Batch modeling•  Lonza is a global company serving the needs

of the pharmaceutical and specialty ingredients markets.

•  Presented by Christine Bernegger / Head Program Management, Visp Seminar 2013-02-28. February - Workshop der ISPE Affiliate D/A/CH

Solution

Six sigma approach variability analysis for Yield optimization And Time Based MVA of On-line Process Parameters .

Customer Results / Benefits Customer Business Challenge

•  Average Yield was lower than expected

•  Variation in Yield gave a more difficult situation to plan work and delivery to end customer

Biogen: Development to Manufacturing

“SBOL has increased our real-time fault detection capabilities. We have improved process and equipment knowledge and understanding. It has expanded our capability to prevent deviations.”

–  Jeff Simeone, Process Engineer

Customer Results / Benefits

•  Proven as extremely useful •  SIMCA-online has improved

real time fault detection to prevent deviation

•  SIMCA-online has improved process and equipment knowledge

•  Deployed to 3 sites •  Site-wide acceptance with

large LCD monitors displaying SIMCA-online real time trends

Solution

•  Use SIMCA for developing

MVA model using batches with appropriate control

•  Use SIMCA-online to provide real time indication of batch

Customer Business Challenge

•  Evaluate batch consistency •  Analyze relationship

between all measured process variables

•  Compare current batch in real time against the golden batch

•  Improved understanding

•  Enhanced productivity and efficiency

•  Reduced risk

•  Continuously meet product specifications

Benefits of DOE & MVDA

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