10th— 11th - February 2015 – Radisson Blu, Heathrow Airport, Hayes, London, UK Annual BIOINNOVATION | Seamless, Integrated & Innovative BioManufacturing http://www.bioinnovation.gb.com/ Annual PIMS | 2015 |Pharmaceutical Innovation, Operational Excellence & Manufacturing Strategies Summit http://www.pims.gb.com/ 16th & 17th September 2015 | Boston Marriott Cambridge, MA | USA Annual ManuBIO | 2015 Flexible, Integrated & Innovative Biological Manufacturing Excellence USA http://www.manubio.com/ VIDEO WATCH

1. CASE STUDY
se nsitivity analysis
at a new plant
GOAL
To accurately prioritize Operational Excellence initiatives
at a new plant based on simulation technology.
• Simulation model built before a plant became operational to quantify
key bottlenecks and areas of risk within the plant
• Model quantified those areas of the plant needing Operational
Excellence projects to decrease cycle times and/or waste streams
• ‘Not just where, but how much’: allowed Operational Excellence staff
to see how much improvement was needed before another area became
the bottleneck.
high level
summary
THE BRI EF
How We Did It
“Understanding how different
pieces of equipment will
perform with and around
each other is the most
difficult and rewarding task.”
In an environment with increasing cost pressures from biogenerics,
dwindling product pipelines and a difficult global economic climate it is
becoming increasingly essential to streamline operations. Biopharmaceutical
manufacturers are investing in Operational Excellence (OE) programs that
aim to drive waste streams from the manufacturing process.
One of the most significant problems for new OE groups, however, is the
complexity of the biopharmaceutical manufacturing process and the need
to determine where to focus process improvement efforts. Bioproduction
Group’s brief was to create a simulation model of a fill/finish facility as the
new plant finished qualification runs. The simulation could then be used to
suggest the most ‘sensitive’ areas of the plant to variability and risk, allowing
OE groups to proactively control and manage them.
David Zhang, Principal
% OVERALL CYCLE TIME DECREASE
FILL/PACK ACTIVITIES*
Component Prep
Thaw
Formulation
Fill
Packaging
Capping Inspection
* Indicative, not actual data
SMALL
EFFECT ON
SCHEDULE
IGNORE
MEDIUM
EFFECT ON
SCHEDULE
TRACK
LARGE
EFFECT ON
SCHEDULE
FOCUS
IMPROVEMENT
EFFORTS
© Bioproduction Group. All Rights Reserved. 1

2. Bioproduction Group’s approach was to construct a very detailed facility
simulation model, in conjunction with dozens of engineers performing the
construction and validation of process equipment. “The devil is in the detail
with new plants”, comments Principal David Zhang. “Understanding how
different pieces of equipment will perform with and around each other is
the most difficult and rewarding task.” The completed model provided a
comprehensive value stream map of the plant as well as identifying resources,
scheduling and operational considerations critical to plant operations.
Bio-G’s approach was to then use the model to perform ‘sensitivity analysis’,
an approach that examines each of the activities in the plant to see which
are critical to throughput, and those that can be ignored.
The graph above shows a tolerance diagram of those activities that are
critical to plant performance amongst around 200 possible activities.
The deeper the spike, the more critical this activity is to overall plant
performance.
Results:
A Quantitat ive
Tool for
Operational
Exce llence
The finalized tool did more than identify key areas of the plant, however. It also
provided the ability for OE staff to prioritize areas for improvement based on
relative importance, and to target how much improvement was required. In
the example below, a 10% reduction in process times delivers 25% increase in
throughput but any greater reduction has no incremental benefit. As such, the
tool provides highly accurate quantitative answers that are immediately useful
to OE groups.
AVERAGE BATCH CYCLE TIME (DAYS)
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
25% IMPROVEMENT IN CYCLE TIME
Baseline 9% Reduction 10% Reduction 11% Reduction 12% Reduction 13% Reduction
NO VALUE TO A REDUCTION LARGER THAN 10%
IMPROVEMENTS IN
KEY PLANT ACTIVITIES
A 10% reduction in key plant
activities results in a 25%
performance improvement
MORE INFORMATION
BIOPRODUCTION GROUP
CONTACT@BIO-G.COM
www.bio-g.com
© Bioproduction Group. All Rights Reserved. 2