Artificial intelligence (AI) is a lot more sophisticated today than it was just a few years ago. Its impacts are felt outside of technology applications such as computing, malware, and natural language processing. For example, Google’s AI (called DeepMind) recently solved one of biology’s greatest problems: It determined a protein’s three-dimensional shape from its amino acid sequence. Now, AI is making a foray into drug development processes. Drug development is a risky, expensive, time-consuming, yet often lucrative venture. The costs…
November-December 2021 Featured Report
Working with Big Data in Healthcare and Bioprocessing Settings: A Brief Introduction to Key Components and Considerations
Artificial intelligence (AI) in healthcare and biopharmaceutical industries still is in early stages of development and use, yet proper data management is critical to successful implementation at any stage of the enterprise continuum. AI is applied to help researchers understand and analyze biology, diagnose diseases, design new drugs, and predict clinical potential and treatment outcomes. AI has been applied in the discovery and development of novel drugs and for repurposing existing drugs, manufacturing different types of drug products, and optimizing…
Pathogen Safety Digital Platform for Biopharmaceuticals: The Journey from Ground to Cloud
Digital transformation is at the heart of many biopharmaceutical companies’ strategies for ongoing success. However, the definition of digital transformation and what it consists of differ within the bioprocess industry (and might even vary within a single company), specifically as it applies to the overall value chain from R&D to clinical trials, manufacturing, supply chain, and eventually commercial operations. To provide a perspective on what digital transformation could look like in bioprocessing, we present a case study about an exploratory…
Automated Process Control Based on In Situ Measured Glucose Concentration
A process analytical technology (PAT) strategy involves defining critical process parameters (CPPs) of a biomanufacturing process that influence critical quality attributes (CQAs) and controlling those CPPs within defined limits. Doing that enables consistent product quality and helps companies reduce waste and costs. Glucose is an important CPP in bioprocessing and cell therapy. Glucose often is fed as a bolus addition based on daily off-line measurements, but that can lead to high glucose fluctuations and to excessive glucose feeding, which can…
Realization of Quality By Design and Beyond: The Intelligent Cell Processing System
Cells are used as raw materials, intermediates, and final products in biopharmaceutical and cell therapy manufacturing. Because living cells are always in a dynamic state, their characteristics must be kept within specified ranges throughout bioprocessing to preserve their utility. Cell population expansion without changing the original cell properties is key for obtaining the required number of cells at the next step. However, limited process data are collected during the expansion phase — information that could be used to understand and…