NDLI: Hybrid Controls Combining First-Principle Calculations with Empirical Modeling for Fully Automated Fluid Bed Processing

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Best Practices for Drug Substance Stress and Stability Studies During Early-Stage Development Part I—Conducting Drug Substance Solid Stress to Support Phase Ia Clinical Trials

Journal of Pharmaceutical Innovation : Volume 7, Issue 2, June 2012

Journal of Pharmaceutical Innovation : Volume 7, Issue 1, March 2012

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Journal of Pharmaceutical Innovation : Volume 5

Journal of Pharmaceutical Innovation : Volume 4

Journal of Pharmaceutical Innovation : Volume 3

Journal of Pharmaceutical Innovation : Volume 2

Journal of Pharmaceutical Innovation : Volume 1

Hybrid Controls Combining First-Principle Calculations with Empirical Modeling for Fully Automated Fluid Bed Processing

Content Provider	Springer Nature Link
Author	Zacour, Brian M. Drennen, James K. Anderson, Carl A.
Copyright Year	2012
Abstract	The US Food and Drug Administration has encouraged the use of the guidelines put forth by the International Conference on Harmonization (ICH-Q8) that allow for operational flexibility within a validated design space. These guidelines make possible fully automated control systems that incorporate information about a process back into the system to adjust process variables to consistently hit product quality targets. Traditionally, fluid bed control systems have used either first-principle calculations to control the internal process environment or purely empirical methods that incorporate online process measurements with process models and real-time data management. This study demonstrates the development and implementation of a novel hybrid control system that combines the two traditional approaches.Granules containing gabapentin, and hydroxypropyl cellulose were prepared in a high-shear granulator and dried in a fluid bed processing system (Diosna Minilab). The fluid bed dryer was outfitted with near-infrared (NIR), pressure, temperature, and flow sensors which were connected to a distributed control system (DCS) that was used to exercise control of the system. The control system itself consisted of a Delta V DCS (Emerson Process Management, Equipment and Controls, Inc., Lawrence, PA, USA) that was used to interface the fluid bed dryer with SynTQ (Optimal, Bristol, UK). The dried granules were characterized by median particle size and quantity of gabapentin lactam formed (a chemical degradant).Control of a fluid bed dryer utilizing both a first-principle control strategy and empirical model-based controls was demonstrated. First-principle control was based on an environmental equivalency factor model to maintain a constant thermodynamic environment. Empirical models included a pressure drop across the bed and NIR measurement of water content. These systems were combined effectively to consistently dry granules prepared by high-shear wet granulation. Utilization of this system greatly reduced the number of experiments necessary to characterize the performance of the system and facilitated control of the process with respect to the two properties of interest, median particle size and chemical stability during drying.
Starting Page	140
Ending Page	150
Page Count	11
File Format	PDF
ISSN	18725120
Journal	Journal of Pharmaceutical Innovation
Volume Number	7
Issue Number	3-4
e-ISSN	19398042
Language	English
Publisher	Springer US
Publisher Date	2012-10-23
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Fluid bed processing Process analytical technology Multivariate modeling Online monitoring Real-time data management Industrial and Production Engineering Biotechnology Biochemical Engineering Pharmacology/Toxicology
Content Type	Text
Resource Type	Article
Subject	Drug Discovery Pharmaceutical Science

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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A PAT Approach to Enhance Process Understanding of Fluid Bed Granulation Using In-line Particle Size Characterization and Multivariate Analysis

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Hybrid Controls Combining First-Principle Calculations with Empirical Modeling for Fully Automated Fluid Bed Processing

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