Decision-Support Method for the Choice Between Single-Use and Multi-Use Technologies in Sterile Drug Product Manufacturing
Single-use technology has been applied to sterile drug product manufacturing processes as a new technology in contrast with the conventional multi-use technology. This study proposes a decision-support method for choosing between these two technologies in sterile drug product manufacturing.
The proposed method consists of four steps: create process evaluation models, calculate evaluation results, perform what-if analysis, and interpret results. We created models for evaluating the production cost and life cycle CO2 emissions of processes using either technology. “What-if” analysis quantifies the effect of the input parameters on the evaluation results, which supports more informed decision-making. Here, it is recommended that the filling speed, which was found to have a significant impact on filling accuracy—a critical quality attribute of sterile drug products—should be investigated.
As a case study, the method was applied in two cases of technology selection: (i) single-batch production of a product with different batch sizes and (ii) single-batch production with different production patterns. The single-use technology showed its economic superiority in producing small batches and in producing multiple small-scale products, whereas in the environmental evaluation, it was always better than multi-use technology. What-if analyses revealed the impact of changing input parameters on the economy, environment, and quality.
Our method can support the choice of single-use and multi-use technologies in plants having both technologies independently. In the case study, economic evaluation showed a critical point in each design case, whereas the environmental evaluation result was always better in single-use technology.
KeywordsPharmaceutical manufacturing Process design Process modeling What-if analysis Life cycle assessment Decision-making
Production cost [¥]
Life cycle CO2 emissions [kg-CO2]
Total numbers of batches [–]
Total numbers of products [–]
Unit preparation or waste treatment cost of component/medium [¥/kg-resin or ¥/kg-water]
Cradle-to-grave CO2 emission factor for the virgin or waste component/medium [kg-CO2/kg-resin or kg-CO2/kg-water]
Weight of component/medium [kg-resin or kg-water]
Labor cost [¥/h]
Cost for HVAC system [¥/m2/h]
Cradle-to-gate CO2 emission factor for HVAC system [kg-CO2/m2/h]
Number of required operators [–]
Manufacturing area [m2]
Time for preparation [h]
Time for after-treatment [h]
Batch size [L]
Filling speed [vial/min]
Number of filling needles [–]
Product volume [mL/vial]
Cost for CIP/SIP [¥/h]
Cradle-to-gate CO2 emission factor for CIP/SIP [kg-CO2/h]
Cost of cleaning validation [¥]
The estimated total number of batches for product j planned for the period during which the cleaning validation is valid [–]
SUT or MUT [–]
The authors acknowledge industrial experts from the International Society of Pharmaceutical Engineering (ISPE), Japan, especially Mr. Seiji Shimura from Nihon Pall Ltd. and Mr. Koji Takimoto from Daiichi Sankyo Propharma Co, Ltd. Financial support by Grant-in-Aid for Young Scientists (B) No. 26820343 from the Japan Society for the Promotion of Science, as well as Research Grant 2014 from The Nagai Foundation Tokyo are gratefully acknowledged. This research was supported through the Leading Graduates Schools Program, “Global Leader Program for Social Design and Management,” by the Ministry of Education, Culture, Sports, Science, and Technology.
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