Bio g defense in depth presentation

© Bioproduction Group | www.bio-g.com 10/24/2013

Defense in Depth

Increasing Redundancy in Biomanufacturing Facilities

October 24, 2013

Rick Johnston, Ph.D. - Principal and Founder

Gary Wright - Sr. Account Director

[email protected]

© Bioproduction Group | www.bio-g.com

“Defense in Depth”

• Strategy for increasing the robustness of manufacturing

systems

• Introduces redundancy in manufacturing to mitigate the

impact of failures

• Key idea: system must be tolerant to failures

• Implemented in many manufacturing environments and

high risk operational settings (such as jet-liners)

• When used successfully, avoids disruptions while

maximizing likelihood of on-time batch release

10/24/2013 1


Bioproduction Group

Founded in 2007 with an exclusive focus on

Biomanufacturing Operations

Primary goal of improving Quality,

Productivity, Flexibility and Operations in

Biomanufacturing

World Class “real time” data collection,

modeling, and simulation software

Technology Assisted

Knowledge Generation Tool

Specifically designed for the unique

needs of Analysts

Improving Quality, Productivity, Flexibility

and Operations at the World’s Largest

Biomanufacturers


Why “Defense in Depth”?

• Current biomanufacturing systems exhibit significant

operational variability:

– Batch-to-batch titers

– Manufacturing times

– Number of deviations per batch

• There are also still a relatively high number of

contamination events in the industry

• The industry currently “hides” these issues behind large

quantities of safety stock inventory and idled capacity

10/24/2013 3


Variability is seen throughout the

manufacturing process.

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WFI Demand During Rituxan 3.5 rpw 2/09/09 to 3/30/09 (50 days) (PI Data: tank level drop plus distillate flow sums)

0

200

400

600

800

1000

1200

1400

024

48

72

96

120

145

169

193

217

241

265

289

313

337

361

385

409

434

458

482

506

530

554

578

602

626

650

674

698

723

747

771

795

819

843

867

891

915

939

963

987

1012

1036

1060

1084

1108

1132

1156

1180

LP

M

WFI consumption

(L/min)

Cadence of

batches in

production fermentor

Even run-rate cadence implies a ‘cyclic’ pattern of usage

But, pattern of consumption is NOT cyclic


Temperature bands in a freezer

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Batches lost due to

temperature

malfunction


Lactate levels in bioreactor: significant

batch to batch variability

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Non-stationary processes (i.e. process

drift)

10/24/2013

Most modern biomanufacturing data exhibits both significant variability

and significant process drift.

CIP Times, 2002 - 2008

Ho

urs


Comparative variability: semi-conductor

vs. biopharmaceuticals

Semiconductor Biopharmaceuticals

Variation in per batch

output (lower is better)

* 3% ** 30%

Number of deviations

per batch

2 80

10/24/2013 8 * Standard deviation of performance per chip, http://spectrum.ieee.org/semiconductors/design/the-threat-of-

semiconductor-variability

** Standard deviation of bulk manufacturing quantity per batch, internal Bio-G data, based on Mab production.

The data suggests that biopharmaceutical manufacturing

exhibits more significant process variability than other

industries

http://spectrum.ieee.org/semiconductors/design/the-threat-of-semiconductor-variability










Designing “Defense in Depth” into

biomanufacturing systems


Traditional Risk Mitigation vs. Defense

in Depth

Traditional Defense in Depth

Core Philosophy “Fixing each issue in

turn will enhance

reliability”

“Avoid inevitable

issues from affecting

reliability”

Focus Specific problem or

issue identified

Holistic view of

manufacturing process

Data Batch report or

historian data for the

issue

Entire manufacturing

system

Method Root-cause

identification and

remediation

Process as “Black

Box”

Tools Ishikawa, SPC,

regression modeling,

correlations, manual

effort

Discrete Event

Simulation, automated

analysis

10/24/2013 10 These two approaches are highly complementary


“Defense in Depth”: elements of

successful risk mitigation

10/24/2013 11

Process Robustness

Scheduling Redundancy

“Surge” Capacity

Inventory Buffering

Equipment Redundancy


“Defense in Depth”: How

• Bio-G has performed defense in depth analysis for more than 7 years

for leading biopharmaceutical manufacturers

• Our approach focuses on a data-driven approach to increasing

robustness (rather than a consensus driven approach, relying on

expert opinion)

• Process Robustness: identify variability in processes and improve

the systems that manage that variability. Includes items like

unplanned maintenance and process restarts.

• Scheduling Redundancy: introduce ‘holes’ in the schedule where

significant variability occurs and that variability has a large impact

• “Surge” Capacity: create the ability for parts of the facility to be able

to ‘catch up’ when delayed or recover quickly due to an outage

• Inventory Buffering: place intermediate WIP or raw materials such

that they allow optimal recovery due to a failure

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Demonstration: How we model process

robustness

• Using data from automation systems / historians

• Creating a model of the facility

• Creating an automated robustness analysis


“Take home” messages

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• Increasing redundancy requires us to probe a manufacturing system,

‘imagining’ the effect of different kinds of failures

• Most of the time, failures will have little or no impact to the metrics

we care about (throughput, overtime etc.) – but the 5% of those that

do matter are critical

• An automated evaluation tool can be used to evaluate the impact of

these failures

• Single variable analysis shows us some impacts, but the best kinds

of analysis look at multiple factors at the same time (DOE approach)

• We must also look at multiple replications (i.e. repeating the same

experiment multiple times) to ensure the answers are consistent

Case Study

• From: Expanding Production at Biologics facilities: Effective strategies and Planning

Ken Hamilton, Genentech Oceanside, Biomanufacturing Conference, Boston, June

27-28 2013


Installing an additional CIP skid produced the

same result as optimizing existing equipment

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Confidence Histogram - By Resource

0

5

10

15

20

25

30

3.355 3.379 3.402 3.426 3.450 3.478 3.503 3.528 3.554 3.580

Run Rate (rpw)

Nu

mb

er

of

ob

serv

ati

on

s

3 Upstream CIP Skids Upstream CIP Cycle Reductions

No difference in the run rate

and distribution of probable run

rates between case for

additional skid vs optimizing

exiting skid

http://www.bio-g.com/




“ROBUSTNESS” ANALYSIS

• Examines the effect on run-rate of delays in manufacturing

operations

• Goal: to allow for a robust schedule that, despite inevitable

delays, will still allow us to reach our production targets

• Robustness analyses look at varying levels of delays, typically

from 1-8 hours (8 hours being an entire shift)

• Can also be used to analyze the ‘white space’ available for

preventative maintenance and calibration activities

• Gives engineering groups targets for further improvement and

areas to enhance operational efficiencies

Credit: Expanding Production at Biologics facilities: Effective strategies and Planning

Ken Hamilton, Genentech Oceanside, Biomanufacturing Conference, Boston, June 27-28 2013




© Bioproduction Group | www.bio-g.com Credit: Expanding Production at Biologics facilities: Effective strategies and Planning


* No manufacturing specific data shown. Graphs

show sample data only.





RISKS AND “WATCH OUTS”

• Finding the optimum of likelihood of attaining target sustained

capacity increase, cost and any shutdown durations is key

– Find balance between optimizing existing equipment

versus installing back up systems

• Ensure capacity increase projects are always linked back to

business needs

– Business needs could change thru life of the project

• Ensure scope of changes is thoroughly defined at the outset

• Need to ensure operations groups and teams remain fully engaged

thru life of project

– Ideally transition project to an operations group toward

end of implementation phase

• Develop accurate cost estimates early in the project – Avoids recycle

Credit: Expanding Production at Biologics facilities: Effective strategies and Planning





Scheduling Redundancy


Key idea: do robustness analysis in

real-time and use that to schedule

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Real-time analysis and optimization is critical to

achieving ‘Best-in-Class’ performance





Collect feedback on robustness from

Outlook (automated toolset)

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Allow manufacturing

to instantly react





… or using smart phones that are on the

manufacturing floor

10/24/2013 24

* http://www.cocoanetics.com/2011/12/myth-busted-iphones-wont-work-with-gloves/




http://www.cocoanetics.com/2011/12/myth-busted-iphones-wont-work-with-gloves/














These toolsets have a real impact on

manufacturing

10/24/2013 25

Reactionary

Expediting

86

13

Year 1 Year 2

8

86%

fewer

91%

fewer

Before

Hours Spent

(Mfg + Scheduling)

1837

1322

Year 1 Year 2

900

28%

less

51%

fewer

Before

Adherence to

Plan

76

%

88

%

Year 1 Year 2

98

%

Before





Conclusions

• “Defense in Depth” is a holistic approach to designing redundancy

into manufacturing systems

• The approach requires toolsets that ‘understand’ variability and the

impact it could have

• Rather than ask for people’s view on risks, it uses a data driven

approach that is based on past performance

• Designing robust systems is a complementary approach to root

cause analysis

• These approaches do not require massive investment in

infrastructure

• When used, it can have significant benefits to the business for

metrics like reactionary expediting and performance against plan

10/24/2013 26




Questions and Discussion

Documents

Bio g defense in depth presentation