Creating a Digital Twin to Simulate Biopharma Processes

Our global client aimed to empower biopharma customers with an innovative, cloud-agnostic platform for digital process simulation.

Solution

Enterprise AI

Industry

Life Sciences

Scope

Cloud / Architecture / Development / DevOps / Digital Twin

Timeframe

10 months

The client

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

Business needs

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.

The challenge

01

Costs of digitizing biotech processes
02

Complexity of Biological Systems
03

Lack of Standardization

Our 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

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. Łukasz Paciorkowski A4BEE CEO

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

The 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

What we implemented

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