Aizon announces today that the Aizon Bioreactor Application was awarded a Pharma Innovation Award from Pharma Manufacturing. Honored in the Bioprocessing category, the Aizon Bioreactor Application combines artificial intelligence (AI), machine learning (ML), cloud technologies, Internet of Things (IoT) and other data analytics tools in a single Software as a Service (SaaS) platform delivered through the cloud, making it the industry’s first predictive analytics and deep knowledge management application to improve the output of bioreactors in GxP environments.
“This year in particular, the pressure has been on pharma to keep pace with the ongoing demand for pandemic products, while also meeting the needs of rapidly expanding areas of the industry, such as advanced therapeutics. Without innovations that boost speed and efficiency throughout the development process — from early drug creation to packaging and shipping — the industry would surely stumble on this journey,” the editors wrote in its announcement.
The continued innovation in the industry achieved through new technology such as Aizon’s Bioreactor Application helps pharmaceutical manufacturers empower data-driven decision making in a way that streamlines production processes, reduces costs, improves yield and helps them keep up with today’s increasingly complex regulatory landscape.
“We work hard every day to help our customers use data science to optimize and standardize their manufacturing processes,” said Toni Manzano, Chief Scientific Officer and co-founder of Aizon. “Getting a better handle on their data allows them to easily generate actionable insights into complex processes in real time that open up a whole slew of use cases and benefits that enable business agility—such as real-time batch monitoring and autonomous manufacturing.”
Purpose-Built Solution for the Pharmaceutical and Biotech Industries
Aizon’s Bioreactor Application is a pre-built, cloud-based solution designed to meet the complex needs of modern pharmaceutical production for upstream processes. Designed to work with both continuous and fed-batch bioreactors, the platform provides a new, more efficient way to analyze process data, including real-time batches, finished batches and multivariate parameters inside the upstream process—including external, previous or downstream manufacturing steps.
This gives manufacturing operators and other stakeholders an easy and fast way to use any real-time sensor from a manufacturing site. The application scales across multiple bioreactors—providing a central dashboard for site managers and other stakeholders to make real-time decisions about batch processes and make highly-accurate yield predictions for future batches. It can also pull in critical data from other enterprise systems such as LIMS, ERP, MES and supply chain management solutions—further enriching decision-making beyond just manufacturing processes.
“The Aizon Bioreactor Application is a critical tool that pharmaceutical and biotech companies can use to further their digital transformation journey toward Pharma 4.0,” said John Vitalie, CEO, Aizon. “This award from Pharma Manufacturing editors and reviewers—the people who cover the industry—is validation for our data-driven approach to enabling flexibility, business agility and new levels of optimization.”
Aizon’s Bioreactor Application is already used by a number of leading pharmaceutical and biotech firms, and has become one of the flagship products of the company.
Aizon is a software application and solution provider that transforms manufacturing operations with the use of advanced analytics, artificial intelligence, and other smart factory technologies focused on optimizing production within highly regulated industries. The Aizon AI platform seamlessly integrates unlimited sources of structured and unstructured data to deliver actionable insights across all manufacturing sites. Aizon offers an intuitive way to gain meaningful operational intelligence by enabling real-time visibility and predictive insights in a GxP compliant manner with end-to-end data integrity.