Creating Digital Twin
to execute simulations
of biopharma processes

Industry

Life Sciences

Scope

Cloud / Architecture / Development / DevOps / Digital Twin

Timeframe

10 months

01

CLIENT

A global leader in the life sciences, pharmaceutical and healthcare sector with a long history in pioneering medical research and innovations.

02

BUSINESS NEED

As a global leader, our client aimed to empower biopharma customers, enhance their processes, and drive innovation within the industry. To achieve this goal, the company wanted to create an efficient and scalable cloud-agnostic platform for the digital simulation of biopharma processes. The platform should provide end users with a single-access portal, offering a suite of applications, including no-code tools, data management, visualization and a dedicated tool for executing biopharma digital twin applications and simulations.

03

CHALLENGE

How to develop a biology-centered digital twin with a focus on cost efficiency and collaboration

  1. Costs of digitizing biotech processes

    Costs of digitizing biotech processes Costs associated with the entire process of digitization are complicated and time-consuming, which makes the costs very high.

  2. Complexity of Biological Systems

    Complexity of Biological Systems Biological systems are highly complex so creating a platform that can simulate these complexities is a significant challenge.

  3. Lack of Standardization

    Lack of Standardization The lack of industry-wide standards for digital twin development in biotechnology can hinder collaboration and data sharing between organizations.

A scientist in a protective overall and a mask, dispensing a liquid into a flask in a lab

04

SOLUTION

To address these challenges and meet their objectives, our client chose to develop a robust and versatile platform, consisting of the following key components

  • Develop the digital twin of a bioreactor using agnostic cloud computing
  • Demonstrate and leverage the benefits and potentials of digital twins
  • Capture and digitize process know how in form of models, converging science and technology
  • Use predictive model for finding the best conditions for the process performance
  • Use data-driven preprocessing manager to execute simulation workflows
Piotr Pawlak, Project Tech Lead

In the realm of digital twins for biopharma processes, success is born from the intricate dance of interdisciplinary collaboration. Engineers, data and IT architects, scientists, and experts with profound knowledge of both mechanistics and data-driven models join forces to choreograph simulations that propel innovation in the biopharma industry.

Piotr Pawlak

Project Tech Lead

Technology used

OT (PLC) Cloud OpenShift AWS Microservices Serverless Event driven system Python Java TypeScript React Docker Azure DevOps Swagger

05

OUTCOME

Releasing a prototype of a leading edge data science application that can be used by bio-engineers as an intuitive tool focusing on the bioprocess.

This is achieved by
automating the modern model-based solutions for fed-batch and perfusion bioprocesses and developing a process optimizer.

Also helpful was the Digital Twin Maturity Model, which supplements the fascinating technology part with the identification of business needs and goals.

  • One central execution process for the simulation or co-simulation of all Digital Twin applications inside the platform.
  • Digital Twin Platform 100% readiness for performing simulation and integration with Lab data monitoring systems
  • 10 months -> full digital twin development process
  • 3 cloud environments tested for platform

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