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Transcript of Bio g strategic capacity assessment
© Bioproduction Group | www.bio-g.com 8/28/2013
Briefing:
Strategic Capacity Assessment (3-10 year time horizon)
Rick Johnston, Ph.D. Principal, Bioproduction Group Gary Wright Senior Account Director, Bioproduction Group [email protected]
© Bioproduction Group | www.bio-g.com
Bioproduction Group
Biomanufacturing
Operations Experts
Enterprise software and services
Consolidation and visualization of
production & capacity planning data
Real-Time Modeling System delivers
Debottlenecking
Process Optimization
Real-Time Scheduling
Quality by Design (QbD)
Capacity Planning
Improving Productivity, Flexibility, Quality
and Operations at the World’s Largest
Biomanufacturers
© Bioproduction Group | www.bio-g.com 8/28/2013 2
Bio-G Real-Time Modeling System The next generation toolset for biomanufacturing analysis
Multiple
Real-Time
Data Sources
Consolidate,
View and
Analyze Data
Real-Time Model
of the
Complete System
Real-Time
Scheduling
Process
Optimization
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Building the right amount of capacity
Mantra in Biotech: “No patient shall go without”
• Drugs are typically life saving or preserving
• Products have a limited period of patent protection
• Manufacturing costs are typically 10%-20% of sale price
• Drug shortages (capacity < demand) have an outsize impact on share price
In short: high reliability / service levels are important
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
However, the drug discovery and manufacturing process is fraught with uncertainty
• Uncertain clinical trial outcome (‘PTS’)
• Uncertain patient dosing
• Uncertain titer ranges
• Variability in supply capacity
• + many others
8/28/2013 4
Manufacturers must therefore manage significant variability, while also shielding the effects of that variability from their
customers.
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Two tasks:
1. Accurately assess demand
2. Accurately assess capacity to meet demand for those products
8/28/2013 5
Build simple visualizations that allow us to
understand the impact of variability
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Per Indication:
8/28/2013 6
One typical calculation path to determine demand
Patient Count Expected number of
patients per year
Dosage Assumption Baseline, as well as high / low
dosage assumptions
Titer Assumption Baseline, as well as high / low
titer assumptions
PTS Probability of technical success
KG demand / year The number of kg / year
needed to supply the patient population
Future Commercial Demand
Including Baseline / High / Low cases per indication
Safety Stock Assumption
Assume we build XXX days safety stock per product
Conversion Use characteristic curves:
batches to production days
Campaigning Can we make more than one
year of demand in one campaign?
Production Losses Harvest Yield, Purification Yield, Fill Yield, Pack Yield
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Visualization 1: Histogram of Pipeline, with probabilities
8/28/2013 7
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Like
liho
od
Number of Commercial Successes, 2010-2020
Histogram of Number of Successes by Indication
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
The business typically plans to a particular confidence level
8/28/2013 8
25% >8 indications
5% >=11 indications
50% >6 indications
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Like
liho
od
Number of Commercial Successes, 2010-2020
Histogram of Number of Successes by Indication
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission. 0
5000
10000
15000
20000
25000
30000
35000
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026
KG D
eman
d (w
ith S
S)
Sensitivity Analysis: Future Commercial KG Demand (with SS) (Base Case Demand)
90%ile - Max
75%ile - 90%ile
50%ile - 75%ile
25%ile - 50%ile
10%ile - 25%ile
Min - 10%ile
Min
Expected
0
5000
10000
15000
20000
25000
30000
35000
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026
KG D
eman
d (w
ith S
S)
Sensitivity Analysis: Future Commercial KG Demand (with SS) (Base Case Demand)
90%ile - Max
75%ile - 90%ile
50%ile - 75%ile
25%ile - 50%ile
10%ile - 25%ile
Min - 10%ile
Min
Expected
There is also significant variability in future demand (driven by PTS)
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Plan for a high service level (90%ile of demand)
Demand by year (kg) at various confidence levels
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Decision Tree Visualization: variability is resolved closer to launch
8/28/2013 10
June 2013 Jan 2014
Interim Analysis
Mar 2015
Competitor Launch
Competitor Launch
Dec 2016
Ph-III Clinical Trials
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Visualization 2: Demand Pareto Chart
• We would try to include high, base and low cases for patient dosage and other variations in demand, conditioned on the product being approved.
• It is sorted by expected demand, so the largest ‘blockbusters’ are shown first
• This chart allows the impact of demand variability to be understood. Thicker bars mean there is more variability, and may indicate areas where more data or investigation is needed on a product (particularly if the expected demand is also high)
• We would probably expect to plan to a higher service level than the average, or mean, for most products in the pipeline.
8/28/2013 11
A Demand Pareto Chart shows the range of possible demand for a product over its lifetime (or standardized to a year).
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Demand Pareto Chart
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0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
400.00
450.00
Tota
l Nu
mb
er
of
Ru
n S
tart
s 2
01
1-2
02
1
Indication
Top 30 Indications: Expected Total 12.5KL Run StartsIncluding Sensitivity in Dosage and Titer
84%ile-96%ile
72%ile-84%ile
68%ile-72%ile
32%ile-68%ile
28%ile-32%ile
16%ile-28%ile
4%ile-16%ile
Weighted Average
Large volume products (critical to plan accurately)
Shaded region indicates uncertainty in supply and demand for a particular indication
Dem
and
(ki
logr
ams
/ ye
ar)
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
*Reproduced from Tim Moore, Genentech, Presented at UC Berkeley Jan 2008
1. Titer Evolution:
Doubling every 18
months – 2 years
2. Significant
variability in titers
between products
Supply side: Titer variability
(bioreactor size) x (titer) x recovery rate = kilograms produced
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission. 8/28/2013 14
Titer vs. Kilograms D
em
and
in k
ilogr
ams
/ ye
ar (
kg)
Mega-blockbuster
Mid-range
Small Scale
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission. 8/28/2013 15
De
man
d in
kilo
gram
s /
year
(kg
)
Projected Titer (grams / liter)
Mega-blockbuster
Mid-range
Small Scale
8+g/L 2-5g/L < 1g/L
Titer vs. Kilograms
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission. 8/28/2013 16
De
man
d in
kilo
gram
s /
year
(kg
)
Projected Titer (grams / liter)
Mega-blockbuster
Mid-range
Small Scale
8+g/L 2-5g/L < 1g/L
“Black Swan”
Size of circle indicates comparative likelihood of launch
Titer vs. Kilograms
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Supply Side: Capacity is not measured in lots per year.
That concept is now recognized to be fundamentally flawed:
• Making 10 batches of one product takes much less time than 1 batch of 10 products (due to changeover)
• High titer processes are more difficult to purify than low titer processes
• Variability in supply is significant, especially when considering the impact of contamination events.
8/28/2013 17
“Our facility can make 50 batches of product X in a year”
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Supply Side: Use Characteristic Curves
• A simple visualization can be used called a characteristic curve
• This curve helps us understand the ability for the facility to supply different products and titers
• It incorporates the impact of variability and titer.
8/28/2013 18
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Characteristic Curves allow us to understand the time in days, to make a certain amount of product.
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Nu
mb
er
of
com
ple
ted
bat
che
s
Day since 12KL Bioreactor Inoculation
Characteristic Curves 2 sample products
Product A, 2.5g/L
Product B, 5.0g/L
“It takes 91 days to produce 5 batches of product B. In the
same time we can produce 7 batches of product A.”
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
A Real Characteristic Curve
8/28/2013 20
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Characteristic Curves also evaluate the impact of changeovers.
8/28/2013 21
“It will take us 201 days to make 7 batches of Product A and
5 batches of Product B.”
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1
Nu
mb
er
of
com
ple
ted
bat
che
s
Day since XX L Bioreactor Inoculation
Day 0:
Innoculation of 1st batch
in XX L Bioreactor
30 days to first
batch out
Day 88:
Innoculation of XX
L Bioreactor
Day 201: reach
production target of 5
batches
35 days to first
batch out
Day 58:
Innoculation of last batch
in XX L Bioreactor
Day 92:
last batch out
Product A Product B
Changeover
time
Product A
XX L Innoculation
Product B
XX L Innoculation
Product A
Batches Complete
Product B
Batches Complete
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Occupancy Chart
• The chart is expressed in production days per year, and includes ramp-up, changeover and batch interarrival time metrics for each product.
• Days are used as the primary metric since they provide a unit of measure that is easy to understand. For example, if the occupancy time of the campaigns in a year is less than 365, the plan is feasible.
• If the occupancy time is more than 365 days, we can get an estimate of the number of ‘equivalent facilities’ we would need to accommodate demand. For example, if the occupancy time was 550 days, we would need another facility about half as large as the current one.
• This approach also allows the incorporation of facility utilization, for example a utilization of 90% would mean we plan to have no more than 328 days of occupancy.
• This diagram uses expected clinical demand and expected future commercial production, i.e. it does not explicitly consider risk.
8/28/2013 22
An Occupancy Chart shows the allocation of campaigns to the facility,
and plots how long each campaign will spend in the facility by year.
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Sample Occupancy Charts
8/28/2013 23
“We have sufficient capacity until 2016. We may be able to
stretch out to 2017, with overtime and increased efficiencies.”
0 100 200 300 400 500 600
2013
2014
2015
2016
2017
2018
2019
2020
2021
Production Days
Facility Occupancy Chart
Product B
Product C
100% occupancy
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
8/28/2013 24
0 100 200 300 400 500 600
2013
2014
2015
2016
2017
2018
2019
2020
Production Days
Facility 1 Occupancy Chart
Product A
Product B
“Current Capacity is sufficient for our products.”
100% occupancy
Sample Occupancy Charts
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
0 100 200 300 400 500 600
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
Production Days
B633 Occupancy Chart
Synagis (RSV-633) Expected Future Commercial Production Expected Clinical Support
Overall Model produces an ‘occupancy chart’ of campaigns for expected future demand.
8/28/2013 25
Future Commercial
Demand
Expected Clinical
Demand
Current
Commercial
Demand
Overall occupancy chart, detailing the
number of production days in the
current or proposed facility
© Bioproduction Group | www.bio-g.com. Do not distribute without prior written permission.
Summary of Visualizations
• Demand Planning
– Histogram of pipeline in aggregate
– Decision tree of pipeline by year
– Demand pareto chart (variability)
• Demand vs Supply
– Titer Variability
• Supply Planning
– Characteristic Curve
– Occupancy Charts
8/28/2013 26