Advancements in cell and gene therapy hold promise for the future of personalized medicine, especially for cancer treatments. However, bioprocessing methods for autologous cellular therapies, and CAR-T in particular, often present unique challenges in manufacturing due to the variability of the starting material and unique nature of each batch. Is there a way to create more efficient processes in order to bring down costs and make personalized medicine a viable option for more patients?
Could data analytics aid in the diagnosis of severe neurological diseases? In a recent study, a research group at Umeå University has conducted statistical data analysis of biomarkers from patients suffering from Amyotrophic lateral sclerosis (ALS, also known as Lou Gehrig’s disease) and Parkinson’s disease to investigate whether data analytics could help in the diagnosis of – and help distinguish between – the two diseases.
Pressure to cut development costs and lower regulatory barriers while assuring product quality has stimulated the pharmaceutical industry to apply Quality by Design (QbD) to manage risk and gain process and product understanding. As a result, QbD is being widely promoted by regulatory authorities such as the Food and Drug Administration, and the International Conference on Harmonization.
For pharmaceutical and biopharmaceutical manufacturers it’s common to generate and store large amounts of data originating from a variety of sources. This valuable asset has the potential to deliver critical benefits if the right applications are built around it. Data analytics tools are an important component in making that happen.
Mining information in unstructured text can be a real challenge. Patent documents, for example, provide a rich source of technological and scientific knowledge that can reveal technological trends as well as information on the legal landscape of the market. This makes analysis of the vast and ever-growing number of patents an important part of corporate business strategies.
Making the perfect bar of chocolate is not just about mixing the right amount of sugar and cocoa, or adjusting the process for product quality. Another factor that must be taken into account to optimize both taste and profits is the grinding time of the cocoa beans. Let’s take a look at how data analytics can be used to elevate both, and to find the right combination of ingredients and process to support the business goals — an important factor in the food and beverage industry.
Making sure your data and processes from research and development through to production are compliant is essential in today's highly regulated life science, biopharma, pharmaceutical and food industries. But it's no easy task. Following all of the required steps and ensuring the integrity of your data at every stage is easier and more successful when you use a product designed to keep your data compliant.
On the west coast of southern Sweden, facing the expanse of the ocean, is the beautiful city of Gothenburg. Surrounded by a string of islands, this city has been the home for sailors and merchants, seafaring and shipping, since ancient times. One of the islands to the north of Gothenburg is the picturesque island of Tjörn. Once every year, Tjörn is the location for one of the most famous sailing races in Sweden – “Tjörn Runt” or “Around Tjörn”.
In a manufacturing setting where consistent quality matters, variability in how individual technicians and operators perform their jobs can be frustrating for managers. Companies need a way to achieve consistent quality, without reducing the capacity for innovation and improvement.
In production, your media will pass several different refinement steps. To really understand and be assured about a good progression and state of the production, all of these processing steps need to be monitored continuously. With SIMCA® and SIMCA®-online, both part of the Umetrics® Suite of Data Analytics Solutions, you can confidently monitor and control every step of your process. The web clients allow you to access manufacturing data anytime, anywhere.