Information Technology

Harnessing the Power of Big Data to Improve Drug R&D

Like many other industries, biotechnology is being transformed by the emergence of big data — extremely large data sets that can be analyzed to reveal patterns, trends, and associations — and advanced analytics. Information from multiple sources such as electronic health records, payer claims, and mobile health platforms is growing exponentially. When used and harnessed properly, these data can boost the efficiency of drug research and development (R&D) in three critical areas: early R&D investment, drug development, and personalized medicine.…

14-6-Pall-AllegroMVP-F1

Flexible Automation for Continuous Unit Operations

Continuous processing has the potential to provide significant cost and time savings for biopharmaceutical manufacturing, but that potential can be realized only if appropriate automation solutions are available for continuous flow between disparate upstream and downstream operations. Pall Life Sciences’ Allegro MVP system, a fully automated bioprocessing system designed for use in upstream and downstream single-use processing, enables flexible automation and thus facilitates continuous biopharmaceutical manufacturing. This article presents the results obtained using the Allegro MVP system in combination with…

WWW.GRAPHICSTOCK.COM

The Year of Data Integrity: 2015 Brought a Worldwide Focus on Training, System Design and Control, and Data Management

Each year, regulatory agencies from around the world focus on critical aspects of the pharmaceutical quality management system, bringing awareness to the industry and continuing to effect positive change. In the past five years, risk assessments, electronic records, and outsourced activities have been in the spotlight. As 2015 closed out, it was clearly the year of data integrity. In March 2015, the UK’s Medicines and Healthcare Products Regulatory Agency (MHRA) published its GMP Data Integrity Definitions and Guidance for Industry,…

Elucidation: Strict, but Flexible, Industrial Automation for Biopharmaceutical Manufacturing

Biopharmaceuticals are the fastest growing sector of the pharmaceutical industry, making up about 20% of the market, with annual growth rates of about 8% (double that of more traditional pharmaceutical sectors). To increase capacity and uphold stringent quality and regulatory demands, manufacturers often reassess their operational and technology strategies while focusing on rising manufacturing costs and the pressure of delivering cost-effective new drug products. Bioproduction can range from small batches to low-cost, high-volume campaigns. Few manufacturers have the required in-house…

WWW.GRAPHICSTOCK.COM

From Chips to CHO Cells: IT Advances in Upstream Bioprocessing

Advances in our capabilities for data acquisition, storage, and manipulation are providing the biopharmaceutical industry with an increased understanding of what must be controlled in bioproduction as well as the ability to control it. Developments in hardware, processing algorithms, and software are changing the landscape of bioprocess administration. Increased power for information gathering and processing began with the remarkable increases in microprocessor speed, pipelining, and parallelism over the past couple of decades (1); it continues with advances in data handling…

Figure 1: Summary of discussion

Decision-Support Tools for Monoclonal Antibody and Cell Therapy Bioprocessing: Current Landscape and Development Opportunities

Industrial-scale manufacturers in a number of fields — from automobiles to biotherapeutics — have long relied on powerful computational and mathematical tools to aid in the scale-up, optimization, quality control, and monitoring of product development (1–5). Typical process pathways are highly multifactorial, with numerous branch points, feedback steps, instrumental attributes, and target parameters. Moreover, margins for error are minimal for most industrial processes, requiring high standards of precision from industrial and operational pathways (6). For those reasons, the complexity of…

Photo 1: A user-centered human–machine interface creates optimized working sequences, supports and offloads plant operators, and ensures improved plant efficiency.

Information Instead of Data: User-Friendly HMI Concept Increases Process Control Efficiency

Today, most plant operators are much more than classic process operators. In addition to operational process control, their range of tasks includes product quality assurance, optimization of resources, and maintenance of high‑throughput rates. Qualified information is necessary to reliably perform those tasks. The human–machine interface (HMI) of a process control system provides visualization. Siemens regards new HMI concepts such as advanced process graphics (APG) as the key to task‑specific or situation‑specific decision‑making (Photo 1). Graphics Monitor: the Process Window Before…

WWW.GRAPHICSTOCK.COM

Outsourced Data Integrity: Are Short-Term Financial Gains Worth Long-Term Headaches?

Competitive pricing and continued cost pressures have contributed to the need for many US biopharmaceutical companies to outsource manufacture of active pharmaceutical ingredients (API) and finished products from countries with lower costs for labor, material, and equipment. The main benefit of doing so is lower costs of manufacturing with quality standards comparable to those found in the United States. India and China now account for 80% of API production. But those countries have received media attention because of biopharmaceutical manufacturing…

WWW.GRAPHICSTOCK.COM

Bioconjugation Reaction Engineering and Kinetics Simulation

Bioconjugates represent an important and growing class of pharmaceuticals that include PEGylated proteins, vaccines, and antibody-drug conjugates (ADCs) (1–8). Numerous protein conjugation techniques exist (9). Among the more important conjugation chemistries used for protein therapeutics are N-hydroxysuccinimide (NHS), aldehyde, and maleimide (10–13). To date, process development of industrial biopharmaceutical conjugation reactions has largely been empirical in nature. Typically, many experiments testing different reaction parameters are required to identify optimal process conditions. In some instances, nonmechanistic statistical models can be used,…

Figure 1: The collaborative ecosystem

Managing Collaboration Across the Extended Organization

In an increasingly competitive life-science landscape that includes numerous mergers, acquisitions, and changing business models, the demand for collaboration is increasing at such a pace that it exceeds information technology (IT) capabilities. The need to manage and control this collaboration across the supply chain has become mandatory. That is particularly true for larger organizations with hundreds or thousands of partners that are finding new ways to connect, interact, and conduct business. Individual businesses are forming contractual affiliations that extend beyond…