25.02.2021 | Insilico Biotechnology AG | News

Towards Smart Biofactories: Insilico and Meyer Chroma Technology link Upstream and Downstream Digital Twins for Biologics Production

(Stuttgart) - Insilico Biotechnology AG and Meyer Chroma Technology (MCT) announce joining forces to provide the biopharma industry with an eco-system of Digital Twins enabling integrated predictive process modeling for process development, manufacturing and product purification.

Insilico has been providing the biopharmaceutical industry with its unique Digital Twins based platform for the upstream process development and manufacturing since 2018. The Insilico Digital Twins allowed the biopharmaceutical companies to successfully simulate cell culture processes, resulting in robust process development and manufacturing.

Sharing the vision of the Smart Biofactory, MCT is now joining forces with Insilico to provide the industry with an integrated Digital Twins based solution for biologics manufacturing and purification. Since its start MCT is providing its customers with its purification Digital Twins based tools. The combined software platform that includes modeling tools for both the upstream and the downstream processes is intended to meet the high demand of the biopharmaceutical companies for a full process modeling of all phases of manufacturing and purification allowing the optimization of the whole process from production in cell culture to subsequent purification. This will result in processes with superior productivity and best-in-class product quality and robustness.

Klaus Mauch, the CEO of Insilico, says: "We are excited to establish our collaboration with MCT, and pleased to offer our customers a comprehensive solution platform that combines MCT experience in the downstream process modeling with Insilico’s upstream modeling tools. This would be an unprecedented step forward towards the full digitization of the biofactory."

Kristian Meyer, CEO of MCT, explains: “This partnership creates new opportunities by linking the core strengths of Insilico and MCT to bring a novel one-stop-shop solution for predictive technologies into the marketplace. This will ultimately enable our customers to build smarter biofactories for biologics production in future.”

About Insilico
Insilico Biotechnology AG develops and delivers predictive Digital Twins to advance biopharmaceutical process development and manufacturing. Insilico Digital Twins of cell culture processes lead to superior productivity, product quality and process robustness. Ground breaking predictive power is achieved by exploiting process data using artificial intelligence and biochemical networks. As a result, Insilco’s unique approach substantially reduces experimental effort, costs of goods and time to market. Leading biopharmaceutical companies worldwide use Insilico Digital Twins for cell line development, media design and process control. Founded in 2001, Insilico Biotechnology is a privately held company based in Stuttgart, Germany.

About MCT
MCT provide engineering services and a portfolio of digital twins to assist the biopharmaceutical industry in a digital transformation. The company is Danish based with offices in Copenhagen, Denmark and Shanghai, China. MCT’s core competencies are to design and operate downstream purification units using digital twins for process development and control. The MCT purification twins are based on novel scientific results and they are tailored to be used in disruptive technologies such as model predictive control. Our tools have already been used by world-leading biopharmaceutical companies to design purification units based on few experiments, relying instead on virtual exploration of the design space, to reduce experimental efforts, cost and time-to-market.

Bioproduction facility

Bioproduction facility

/
Copyright 2021 Insilico Biotechnology AG

Contact

Caroline Shafik
Public Relations Manager
Insilico Biotechnology AG
press@insilico-biotechnology.com

https://www.insilico-biotechnology.com

Quelle:
https://www.insilico-biotechnology.com/