(451a) Economic Evaluation Tool for Holistic Design of Solid Drug Product Manufacturing Processes Considering Continuous Technology
- Conference: AIChE Annual Meeting
- Year: 2019
- Proceeding: 2019 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
- Time: Wednesday, November 13, 2019 - 8:00am-8:19am
This work presents an economic evaluation tool for the design of solid drug product manufacturing processes considering continuous technology. The tool integrates our previous studies [2, 3] and consists of three steps: (i) comprehensive alternative generation, (ii) input parameters settings, and (iii) stochastic economic evaluation. In the first step, 4,477 alternatives of processes including the choice of continuous technology are generated by representing possible combinations of unit operations using a superstructure. Estimated values of input parameters are set considering characteristics of target products, and probability density distribution of all parameters are defined in the second step. Finally, in the third step, stochastic economic evaluation is performed for all alternatives by Monte Carlo simulation. Net present value was applied to an evaluation indicator, which considers clinical development cost as well as annual cash flow in the production stage. Estimated ranges of net present value for all alternatives are output at the end.
We performed several case studies, which differ in product characteristics such as demand and raw material price, to demonstrate the effectiveness of the developed tool. Appropriate technology was found to depend on defined probability density distribution of input parameters. For some cases, batch technology was better in terms of expected values while continuous technology was better in terms of probability. Sensitivity analysis was performed for the situations which are difficult to interpret, and then, high effective parameters were analyzed. In these ways, we confirmed that the developed tool works for the rational design including the technology selection and the investigation of high effective parameters for decision making.
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