Insilico Biotechnology
Insilico Biotechnology is dedicated to developing digital twin technology for biopharmaceutical process development and manufacturing, aiming to benefit biomanufacturing through innovative, data-driven solutions.
Industries
Nr. of Employees
small (1-50)
Insilico Biotechnology
Meitnerstraße 9, 70563 Stuttgart, Germany
Products
Technology platform for predictive digital twins (process development)
A technology platform described as implementing predictive digital twins for CHO cultivations and bioprocess development to support simulation-driven process design and manufacturing.
Technology platform for predictive digital twins (process development)
A technology platform described as implementing predictive digital twins for CHO cultivations and bioprocess development to support simulation-driven process design and manufacturing.
Services
Application of predictive digital twins and integrated modeling to support process design, optimization, and manufacturing decision-making for cell-culture processes.
Application of predictive digital twins and integrated modeling to support process design, optimization, and manufacturing decision-making for cell-culture processes.
Expertise Areas
- Digital twins for bioprocessing
- Systems biology and kinetic modelling
- Metabolic flux analysis
- Bioprocess development and scale-up
Key Technologies
- Digital twin simulation
- Hybrid mechanistic and machine-learning models
- Kinetic/dynamic modelling
- Metabolic flux analysis (13C MFA)
News & Updates
Discover the Insilico Technology Platform for process development and manufacturing. Read our poster presented at BPI Boston 2020.
A publication by S. Nargund and K. Mauch in 2020 discussing hybrid models for biopharmaceutical process development.
An article by Nargund, Guenther, and Mauch in 2019 about the company's development of smart processes for biomanufacturing.
A 2018 publication by Barbosa, Niebel, Wolf, Mauch, and Takors on gene regulatory network inference.
A 2016 publication by Popp, Müller, Didzus, Paul, Lipsmeier, Kirchner, Niklas, Mauch, and Beaucamp on metabolic signatures for clone selection.
A 2016 publication by Boi, Diaz Ochoa, Gajewska, Kovarich, Mauch, Paini, Péry, Vicente, Benito, Tenga, and Worth on multiscale modelling.
Discover the Insilico Technology Platform for process development and manufacturing. Read our poster presented at BPI Boston 2020.
A publication by S. Nargund and K. Mauch in 2020 discussing hybrid models for biopharmaceutical process development.
An article by Nargund, Guenther, and Mauch in 2019 about the company's development of smart processes for biomanufacturing.
A 2018 publication by Barbosa, Niebel, Wolf, Mauch, and Takors on gene regulatory network inference.
A 2016 publication by Popp, Müller, Didzus, Paul, Lipsmeier, Kirchner, Niklas, Mauch, and Beaucamp on metabolic signatures for clone selection.
A 2016 publication by Boi, Diaz Ochoa, Gajewska, Kovarich, Mauch, Paini, Péry, Vicente, Benito, Tenga, and Worth on multiscale modelling.