719 Predictive Scale-up/Scale-down for Production of Pharmaceuticals and Biopharmaceuticals


Description:
Manufacturing in the pharmaceutical industry involves a series of chemical and physical processes to produce the desired product with intense focus on quality and reproducibility. The goal to meet quality standards with increasing process understanding in the pharmaceutical industry is made more challenging by the desire to increase speed-to-market for these products and to find more efficient approaches to develop processes. In order to meet these objectives, deeper understanding of, and novel approaches to, scale-up from lab scale to pilot-and commercial-scale processes is needed. The chemical and physical processes used by the pharmaceutical industry involve heat, mass, and momentum transfer as well as kinetic and thermodynamic driving forces, all of which have potential scale-dependence. Additionally, operational issues at scale (out of specification investigation, new impurity, raw material vendor change, new equipment, etc.) require a systematic scale-down approach to lab-scale to facilitate experimental investigation and develop solutions. These challenges are found in batch and continuous processes for the chemical and biological synthesis of drug substance and drug product. Predictive scale-up and scale-down, based on first-principle models and understanding, is essential to development and manufacturing in the pharmaceutical industry. The fundamental insight provided by these models and their application to scale-up/down can reduce development costs and provide increased knowledge of at-scale process performance, leading to improved process control and product quality. This session invites papers that cover both theoretical approaches to and demonstrated implementation of scale-up/scale-down analysis across drug substance and drug product processes for small molecules, antibody-drug conjugates, and biological products.

Sponsor:
Pharmaceutical Discovery, Development and Manufacturing Forum
Co-Sponsor(s):
Pharmaceuticals (15B)


Chair:
Christopher H. Marton
Principal Engineer
Celgene

Email: cmarton@celgene.com

Co-Chair:
Moiz Diwan
AbbVie
Process Research and Development
1401 Sheridan Road
North Chicago, IL
60064
Email: moiz.diwan@abbvie.com


Papers:
Exploring the Kinetics of API Degradation Under Hot Melt Extrusion Conditions
Anuj A. Verma, AbbVie Inc.; Kushal Sinha, AbbVie Inc.; Moiz Diwan, AbbVie
Towards Predicting the Quality of HME Products
Josip Matić, Research Center Pharmaceutical Engineering; Carolina Alva, Research Center Pharmaceutical Engineering; Hannes Bauer, Research Center Pharmaceutical Engineering; Johannes G. Khinast, Graz University of Technology
A Predictive Transport Model for Drying of Polymer Strip Films
Alireza Naseri, New Jersey Institute of Technology; Eylül Cetindag, New Jersey Institute of Technology; Joseph Forte, New Jersey Institute of Technology; Ecevit Bilgili, New Jersey Institute of Technology; Rajesh Davé, New Jersey Institute of Technology
High Shear Wet Granulation Scale-up Study Using Discrete Element Modeling
Maitraye Sen, Eli Lilly and Company; Jonathan Brett Wade, Eli Lilly and Company; Salvador García-Muñoz, Eli Lilly and Company; James E. Miesle, Eli Lilly and Company; Mark Schrad, Eli Lilly and Company
Predicting Shear, Energy Dissipation, and Blending in Bioreactors for Mammalian Cells
Brian DeVincentis, M-Star Simulations; John A. Thomas, M-Star Simulations; Kevin Smith, M-Star Simulations
Simulation of Industrial-Scale Aerated Bioreactors
Christian Witz, Graz University of Technology; Philipp Eibl, Graz University of Technology; Johannes G. Khinast, Graz University of Technology
Abstract Submissions Closed