Yokogawa Insilico Biotechnology Named Winner of 2022 Pharma Innovation Award

Originally Published in Pharma Manufacturing Magazine - Pharma Innovation Awards


Winning Technologies for a Bright Pharma Future

Our first winner leverages artificial intelligence and mechanistic knowledge to enable cell culture performance prediction. Yokogawa Insilico Biotechnology released its Insilico Digital Twin Factory, which can help drugmakers increase productivity and bring down manufacturing costs and time to market by potentially replacing up to 50% of the experiments needed during the process development, characterization and scale-up of biopharmaceuticals.

The digital twins use an advanced hybrid blueprint formed from a mechanistic model of the unique characteristics of an intracellular metabolic network and a data-driven model to allow for the constant prediction of elements such as the soft sensing of substance components that cannot be measured directly, or the early detection of process abnormalities. 




Last year, Yokogawa Insilico released its “Insilico Advisor,” to help improve the efficiency of biologics manufacturing by providing for model predictive monitoring of the cell culture process.

Another significant development challenge facing the industry is poor solubility, especially when it comes to antibody-drug conjugates (ADCs). This emerging class of medicines — designed to target and destroy cancer cells while preserving healthy cells — can fail in the clinic due to poor aqueous solubility.





  • Pharmaceutical

    Pharmaceutical companies must achieve increased flexibility and agility through better use and monitoring of manufacturing data to improve quality management in real time. Pharmaceutical experts work with Yokogawa to create manufacturing solutions that deliver safe and reliable medicines. Together, we use digital transformation and manufacturing advances to meet regulatory requirements, ensure quality, accelerate time to market, and thus providing a stable and reliable supply of medicine to patient.

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