Download our Advanced Analytics in the Pharma and Life Science Industries webinar where we will demonstrate how Seeq enables the integration of myriad data sources for rapid investigation and insight to drive improved decision-making.
The 4th CCP Summit will return to Boston as the only commercial pharmaceutical meeting dedicated to continuous processing, helping you accelerate the switch from batch to CM. Join members of Seeq, Amgen, Sanofi, Merck & Co., and AstraZeneca as we discuss if continuous manufacturing is for legacy products only.
Regulatory support and innovations in technology have fueled the adoption of continuous manufacturing in pharma over the last several years, which exhibits a move toward operations excellence marked by rapid production within multi-use facilities, reduced scale-up risk, and greater quality expectations. The end-to-end, integrated, and intensified processing approach to drug production offers a wide range of benefits that help drive the industry’s goals to increase efficiency in drug development and manufacturing while lowering costs.
With patient health and safety on the line, it is not uncommon for any promising technology or solution aimed at delivering added efficiency and safety to drug development and manufacturing to gain the attention of pharma’s subject matter experts (SMEs). Intellectual analysis combined with justified skepticism help vet each one to determine how far these movements and their buzzwords make it into our strategies as well as our lexicon.
Advanced analytics streamlines continuous manufacturing by providing improved insights to data.
How advanced analytics is being used to drive desired business outcomes in pharma.
Process control enables biomanufacturers to ensure that operating parameters are within defined specifications. A control strategy should be established during early stages of process development while process and product performance are being defined using risk-based methods such as quality by design (QbD) and process analytical technologies (PATs).
Advanced analytics and modeling can be used to predict downstream failures, allowing for corrective action before batches are lost.
“In the past, predictive analytics on a set of many assets was too time consuming to be practical, but advanced analytics enables faster, cost-effective insights,” explains Michael Risse, vice-president and chief marketing officer at Seeq.
While instruments have been getting smaller and more dependable, computers are also getting faster and less expensive. With a typical PAT/QbD or a continuous manufacturing (CU) process, the amount of data that is produced needs to be converted into information.