Role Of Digital Twin in Biopharmaceutical Manufacturing
Several digital technologies are currently used to develop and increase biopharmaceutical products’ production efficiency, including vaccines, medicines, etc.
One of these technologies is the
digital twin technology, an essential Industry 4.0 technology widely used in
all the industrial sectors, including the biotechnological and biopharmaceutical industries.
Digital twins provide insights into all aspects of the production line,
including the manufacturing process. These insights together help to make
mindful decisions related to the product. They can also automate the decision-making
process by recalibrating the dynamics of pharmaceutical laboratory equipment,
production lines, manufacturing processes, and systems.
A digital twin incorporates virtual
reality (VR), augmented reality (AR), 3D graphics, and data modeling to build a
virtual model of processes, systems, services, products, or other physical
objects related to the prospected innovation. This technology creates a replica
of the physical operations. This replica is further maintained using real-time
data.
Digital twin applies to various
environments, including monitoring products used throughout the entire product
manufacturing life cycle. In manufacturing operations, digital twin technology
is applied at multiple levels:
1. Component stage – At this
stage, it focuses on a single, the most complex component of the manufacturing
process.
2. Asset stage – At this
stage, digital twin creates a replica of any piece of equipment used in a
production line.
3. System stage – At the
system level, the digital twin is used to monitor and improve an entire
production line’s efficiency.
4. Process stage – Use of
digital twin at this stage is to look after the entire manufacturing process,
starting from product designing to manufacturing and final production. It also
monitors the distribution, the usage of the finished products by consumers
throughout the entire product’s life cycle and improves future outcomes.
Another excessively used
technological approach is the digital twin. Digital twins currently occupies
the core of this industrial revolution (industry 4.0), bringing in impeccable
possibilities. The next evolution of machine learning combines advanced data
analytics and equipment simulation with comprehensive system models. These
models blend historical information with real-time data; this helps to predict
the results of any biopharmaceutical process.
Digital twins are employed in all
stages of a product’s lifecycle. From the initial design phase to the ultimate
deployment step, the digital twin approach helps revolutionize the operation
process. Nowadays, organizations aim to have a complete digital footprint for
each of their products. The introduction of digital twins has replaced
traditional methods with a more virtual system-based on design processes.
Atos (a leading name in digital
transformation) and Siemens (a global engineering leader) have collaborated
with the pharmaceutical industry (like GSK) to optimize the production process
using innovative solutions that mainly are the digital replicas of the pharma
laboratory processes. These creative digital twins enabled approaches powered
by technologies like IoT, AI, and advanced analytics provide improved
efficiency and flexibility in biopharmaceutical products’ manufacturing
processes.
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