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An Optimization-Based Framework to Define the Probabilistic Design Space of Pharmaceutical Processes with Model Uncertainty

Journal Article · · Processes
DOI:https://doi.org/10.3390/pr7020096· OSTI ID:1870498
 [1];  [1];  [1];  [2];  [2];  [3]
  1. Purdue Univ., West Lafayette, IN (United States)
  2. Eli Lilly & Company, Indianapolis, IN (United States). Lilly Research Laboratories
  3. Purdue Univ., West Lafayette, IN (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
+ Show Author Affiliations
To increase manufacturing flexibility and system understanding in pharmaceutical development, the FDA launched the quality by design (QbD) initiative. Within QbD, the design space is the multidimensional region (of the input variables and process parameters) where product quality is assured. Given the high cost of extensive experimentation, there is a need for computational methods to estimate the probabilistic design space that considers interactions between critical process parameters and critical quality attributes, as well as model uncertainty. In this paper we propose two algorithms that extend the flexibility test and flexibility index formulations to replace simulation-based analysis and identify the probabilistic design space more efficiently. The effectiveness and computational efficiency of these approaches is shown on a small example and an industrial case study.
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
NA0003525
OSTI ID:
1870498
Report Number(s):
SAND2022-4856J; 705168
Journal Information:
Processes, Journal Name: Processes Journal Issue: 2 Vol. 7; ISSN 2227-9717
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (1)

Model-Based Tools for Pharmaceutical Manufacturing Processes journal January 2020

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Related Subjects

60 APPLIED LIFE SCIENCES
flexibility analysis
global optimization
pharmaceutical processes
probabilistic design space