Future API Manufacturing Excellence

Loading...
Thumbnail Image
Penn collection
Senior Design Reports (CBE)
Degree type
Discipline
Subject
Biochemical and Biomolecular Engineering
Chemical Engineering
Engineering
Funder
Grant number
License
Copyright date
Distributor
Related resources
Contributor
Abstract

Many pharmaceutical manufacturing processes are costly, time-intensive, and energy-intensive. Due to the high operational costs, optimization of these processes would result in large economic savings. Fluid bed granulation takes inputs of air temperature, air flow rate, phase duration, binder spray rate, and inlet air humidity. A series of simulations were run to determine optimal operating conditions. It was determined that the process parameters should be limited to the following to meet product standards and reduce costs: air flow rate of 2800 (m3/h), inlet air temperature of 55˚C for spraying and 75˚C for drying, phase duration 124 minutes , binder spray rate of 900 g/s, and inlet air humidity can range from 1-20 g water/kg air. The lyophilization simulation takes process inputs of maximum process time, temperature, pressure, and vial type and returns outputs of peak product temperature, drying time, and maximum sublimation rate. Several primary drying simulations were run for an 8R vial dose and a 20 mL vial dose to determine the optimal operating conditions. The conditions that resulted in the greatest operational cost savings for both the 8R vial and the 20 mL vial were a pressure of 30 Pa, an initial temperature of -9˚C and a final temperature of 1˚C. Based on the proposed conditions, both operational cost and equipment depreciation savings were identified mainly due to lower run times across both processes. For fluid bed granulation, $31,136 operational annual savings were identified amounting to $467,000 over the 15-year project. For lyophilization, $23,500 in annual operational cost savings amounting to $352,000 over the 15-year project life were found. Further operational savings only yielded marginal improvements in profitability.

Advisor
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Publication date
2019-05-20
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation
Collection