Technology Transfer and the Insilico Software Platform

Klaus Mauch

“Combining modern bio-analytical methods with high performance computing spurs innovation and accelerates growth.”
Klaus Mauch, CEO

Four software modules are available today which are combined to support specific workflows in upstream bioprocess development and analysis.

The heart of Insilico's cutting edge technology is the predictive Insilico Digital Twin. Each Insilico Digital Twin is a virtual representation of a specific real biomanufacturing process and includes a genome-based metabolic network model of the production cell line, a process model and an artificial neural network. The combination of these model components enables an unprecedented predictive quality using standard data from time-series measurements of extracellular metabolites which are required to train and validate the Insilico Digital Twin.

Once setup the Insilico Digital Twin delivers automated and standardized predictions for improved bioprocesses. The Insilico Digital Twin allows for seamless integration with existing databases and IT infrastructure. 

We support our customers on their journey towards digitalized biomanufacturing by transferring Insilico's cutting edge technology and thus making it an integral part of their workflows. Technology transfer includes on-premises or cloud installation of the Insilico Software Platform, bespoke training workshops, and expert consulting to make sure our customers can apply our technology's full potential.

More workflows will be supported and automated by Insilico software modules in the near future, resulting in highly scalable and flexible digital bioprocess development and manufacturing capabilities.

Insilico Discovery™ Insilico Discovery™ is a comprehensive tool for reconstruction, verification, and simulation of compartmented cellular metabolic network models.

Insilico Discovery™ allows for integration of bioprocess data and metabolomics data to generate an individualized model of a specific host and bioprocess. By integration of transcriptomics or proteomics data, metabolic pathways can be coupled to gene regulatory networks. The software features three different modules allowing for model reconstruction, integration of experimental data, and simulation of network models. Simulation methods include transient 13C flux analysis, Metabolic Flux Analysis (MFA), Flux Balance Analysis (FBA), Minimisation of Metabolic Adjustment (MOMA), and simulation of kinetic differential-algebraic systems.

Applications of Insilico Discovery include:

  • Reconstruction of individualized network models as a representation of a specific cell line and bioprocess to make them available to other modules of the software platform
  • Detailed quantification and analysis of intracellular flux distributions
  • Identification of bottlenecks in cellular reaction pathways
  • Prediction of the impact on cellular metabolism of genetic modifications or alterations in medium composition

Insilico Analyzer The Insilico Analyzer is a unique tool to perform sensitivity analysis and time-resolved analysis of intracellular fluxes.

On the basis of cell line type, growth medium and feeding data, the Insilico Analyzer executes two analyses sensitivity and intracellular flux analysis. The sensitivity analysis evaluates how sensitive a product reacts to small changes in input parameters in terms of quantity and quality, e.g. concentrations of extracellular components of growth medium. The intracellular flux analysis depicts bottlenecks limiting growth and product formation in the host cell during a bioprocess. The Insilico Analyzer is a tool that exploits its potential in combination with our solutions on media and feed design where it provides the customer with a deeper understanding of the specific cell line and bioprocess improvement potentials.:

Insilico Composer The Insilico Composer represents a Digital Twin designed to optimize media compositions for mammalian cell cultivations.

Insilico Composer systematically simulates numberless media compositions in order to predict the optimal media for improving objectives like productivity or product quality for a specific cell culture process. The core of the Composer is based on Insilico’s unique predictive model, which delivers high quality predictions after it is trained and validated on standard customer bioprocess data. The Insilico Composer will automatically predict optimal media compositions and therefore saves costs and time. In combination with the Insilico Feeder you will have an extremely powerful set of tools for state-of-the-art process development.:

Insilico Feeder The Insilico Feeder is a Digital Twin that predicts improved feeding strategies for a new product.

Insilico Feeder systematically simulates and evaluates feeding strategies to predict those feeding strategies that have a decisive influence on product yield, cell growth, product quality and reduction of toxic by-products. The result is a feeding strategy with an optimized timeline and feed levels. The number of wet lab experiments are reduced to a minimum, which leads to a significant reduction of costs and time during the early process development. The Insilico Feeder will automatically predict the optimal feeding strategy once it is connected to a datasource and trained using standard customer bioprocess data. The combination of the Insilico Feeder with the Insilico Composer creates an extremely powerful set of tools that drastically increases the improvement of feed and medium design in one go for state-of-the-art process development.: