Research and Development

The KYNOTA open bioreactor solution enables researchers to achieve Operational Excellence with improved efficiency in data collection automation. A subscription-based evergreen bioreactor software system, KYNOTA is designed for flexibility and configurability which allows researchers to speed the R&D process and improve the quality of data analytics with real-time monitoring. KYNOTA combines equipment and software with a seasoned team of specialists to provide a bioreactor platform that manages data, accommodates change, and supports process development over the duration of the research project.

NECI supports Product Quality with Continuous Improvements through its Process Analytical Technology (PAT) platform. This platform enables researchers to understand molecules and potential products in development using industry-leading analytical technology and tools. Our all in one compliant, easy-to-use transfer platform reduces development and manufacturing costs while increasing data quality. 

We facilitate improved decision making by providing faster data access that boost lab efficiencies while decreasing costs. These solutions are available at every stage beginning with initial discovery to regulatory approval. This allows us to empower our customers to increase productivity, elevate experimental data quality, and reduce lab process cycle times through improved data management and integrity, advanced analytics, closed-loop control and complete lab instrumentation integration. 

We empower our partners in the Life Sciences industry to advance the world by providing them with the tools they need in order to transform from a physical plant to a digital one. This is significant in Research & Development where the efficient collection and analysis of data is essential. We help our clients become leaders in the industry by transforming how they create, manage, and effectively use data to improve the speed and quality of science. This digitally transformed lab leads to a harmonized platform that brings new scientific business models to help support the supply chain, a greater adoption of Artificial Intelligence, whole lab automation, and implementation of silico methods and simulations.