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CASE STUDY 
Drug Substance 
Campaign Optimization 
GOAL 
To unde rsta nd the impact of changeovers and 
hold ing costs on invento ry management for drug 
su bsta nce product ion. 
• Analysis for a manufacturer producing 2 years supply of material in long 
campaigns, generating large amounts of excess inventory. 
• Project looking at the timing and length of campaigns to optimize 
production and minimize cost. 
• Working in conjunction with Finance and planners, Bio-G evaluated 
different methods for optimizing inventory quantities. 
• The strategy suggested by Bio-G decreased inventory while maintaining 
same service levels to customers. 
• Savings of $5MM a year in direct operational costs, with no investment. 
high level 
summary 
The traditional paradigm for operating large scale bulk manufacturing plants 
is to maximize their throughput, a strategy that involves long campaigns 
with very few changeovers. Plants have been traditionally rewarded for 
this strategy since each additional gram of material lowers the per-unit 
production cost. 
THE BRI EF 
Long campaigns 
result in high inventory 
Short campaigns 
result in less inventory 
Higher average inventory 
with longer campaigns 
Average inventory 
(long campaigns) 
Average inventory 
(short campaigns) 
TIME 
INVENTORY 
LEVEL 
However, supply chain planners have begun to realize that such a 
paradigm generates a large amount of excess inventory that must 
be stored for months or years before it is shipped to patients. Single 
campaigns can produce up to 1-2 years of inventory that must be stored, 
using not just premium warehouse space but tying up valuable capital. 
In worst cases, a classic ‘bullwhip effect’ arises where bulk manufacturing 
is highly unresponsive to actual customer demand, creating either large 
gluts of supply or supply shortfalls. The key challenge for manufacturers 
is therefore to trade off campaign lengths with overall plant capacity 
to minimize not just production cost, but holding costs throughout the 
supply chain network. 
INVENTORY LEVELS OVER TIME 
FOR TWO CAMPAIGN STRATEGIES 
© Bioproduction Group. All Rights Reserved. 1
EOQ MODEL: OPTIMAL TRADE-OFF OF 
HOLDING COSTS & CAMPAIGN LENGTH 
How We Did It 
“Intuitive findings are 
important when you’re 
trying to drive such a 
large-scale change.” 
Rick Johnston, Principal 
OPTIMAL CAMPAIGN 
LENGTH (weeks) 
50 
45 
40 
35 
30 
25 
20 
15 
10 
5 
0 
14 
0 
2 
4 
6 
8 
10 
12 
1 
2 
3 
HOLDING COST 
($ / g / year) 
CHANGEOVER 
COST ($MM) 
Results Bio-G’s recommendations were to dramatically increase the number of 
MORE INFORMATION 
BIOPRODUCTION GROUP 
CONTACT@BIO-G.COM 
www.bio-g.com 
Bioproduction Group’s methodology was to establish a strategy based on a 
variant of the classic ‘Economic Production Quantity’ (EOQ) model, adapted 
for the biopharmaceutical manufacturing environment. “EOQ-style modeling 
was simple, understandable and produced great results”, comments Principal 
Rick Johnston. “Intuitive findings are important when you’re trying to drive 
such a large-scale change.” 
Working with finance planners, the Bio-G team suggested a strategy for each 
product that balanced raw materials, insurance and other real costs against 
the loss of plant capacity resulting from more changeovers. The result was 
a simulation model that incorporated detailed costing and time aspects, to 
show cash inflows and outflows over time. 
Not content with a deterministic solution, the team used simulation modeling 
to show that the risks to the business were the same as, or lower than, the 
existing strategy. 
campaigns, halving the campaign length for many products. The resulting 
strategy minimized inventory on-hand, resulting the manufacturer meeting 
lean targets in terms of raw materials and drug substance. 
More importantly, the output of the simulations showed that these lower 
inventory targets could be met without increasing the risk to the business, 
and in many cases decreased the overall risk of stockout. The value shown 
was $5MM a year in direct costs saved, with no capital outlay required. 
© Bioproduction Group. All Rights Reserved. 2

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Optimizing bulk campaign lengths

  • 1. CASE STUDY Drug Substance Campaign Optimization GOAL To unde rsta nd the impact of changeovers and hold ing costs on invento ry management for drug su bsta nce product ion. • Analysis for a manufacturer producing 2 years supply of material in long campaigns, generating large amounts of excess inventory. • Project looking at the timing and length of campaigns to optimize production and minimize cost. • Working in conjunction with Finance and planners, Bio-G evaluated different methods for optimizing inventory quantities. • The strategy suggested by Bio-G decreased inventory while maintaining same service levels to customers. • Savings of $5MM a year in direct operational costs, with no investment. high level summary The traditional paradigm for operating large scale bulk manufacturing plants is to maximize their throughput, a strategy that involves long campaigns with very few changeovers. Plants have been traditionally rewarded for this strategy since each additional gram of material lowers the per-unit production cost. THE BRI EF Long campaigns result in high inventory Short campaigns result in less inventory Higher average inventory with longer campaigns Average inventory (long campaigns) Average inventory (short campaigns) TIME INVENTORY LEVEL However, supply chain planners have begun to realize that such a paradigm generates a large amount of excess inventory that must be stored for months or years before it is shipped to patients. Single campaigns can produce up to 1-2 years of inventory that must be stored, using not just premium warehouse space but tying up valuable capital. In worst cases, a classic ‘bullwhip effect’ arises where bulk manufacturing is highly unresponsive to actual customer demand, creating either large gluts of supply or supply shortfalls. The key challenge for manufacturers is therefore to trade off campaign lengths with overall plant capacity to minimize not just production cost, but holding costs throughout the supply chain network. INVENTORY LEVELS OVER TIME FOR TWO CAMPAIGN STRATEGIES © Bioproduction Group. All Rights Reserved. 1
  • 2. EOQ MODEL: OPTIMAL TRADE-OFF OF HOLDING COSTS & CAMPAIGN LENGTH How We Did It “Intuitive findings are important when you’re trying to drive such a large-scale change.” Rick Johnston, Principal OPTIMAL CAMPAIGN LENGTH (weeks) 50 45 40 35 30 25 20 15 10 5 0 14 0 2 4 6 8 10 12 1 2 3 HOLDING COST ($ / g / year) CHANGEOVER COST ($MM) Results Bio-G’s recommendations were to dramatically increase the number of MORE INFORMATION BIOPRODUCTION GROUP CONTACT@BIO-G.COM www.bio-g.com Bioproduction Group’s methodology was to establish a strategy based on a variant of the classic ‘Economic Production Quantity’ (EOQ) model, adapted for the biopharmaceutical manufacturing environment. “EOQ-style modeling was simple, understandable and produced great results”, comments Principal Rick Johnston. “Intuitive findings are important when you’re trying to drive such a large-scale change.” Working with finance planners, the Bio-G team suggested a strategy for each product that balanced raw materials, insurance and other real costs against the loss of plant capacity resulting from more changeovers. The result was a simulation model that incorporated detailed costing and time aspects, to show cash inflows and outflows over time. Not content with a deterministic solution, the team used simulation modeling to show that the risks to the business were the same as, or lower than, the existing strategy. campaigns, halving the campaign length for many products. The resulting strategy minimized inventory on-hand, resulting the manufacturer meeting lean targets in terms of raw materials and drug substance. More importantly, the output of the simulations showed that these lower inventory targets could be met without increasing the risk to the business, and in many cases decreased the overall risk of stockout. The value shown was $5MM a year in direct costs saved, with no capital outlay required. © Bioproduction Group. All Rights Reserved. 2