Managing Risks in Pharma/MedTech with Digital Twins

Every industry leader will soon be applying these technologies – modeling, simulation, optimization and digital twins.

Digital Twin = Modeling + Simulation + Optimization + Real-world Data Analytics

This course will give you a comprehensive view on designing end-to-end ditial processes within a Pharma/MedTech company.


Proposed Audience:

Anyone interested to know how to add digital twin application and AI integration to a model (after simulation and optimization)


Why we need Digital Twins in Pharma & MedTech?

Pharma&MedTech companies struggle to make their digitally transformed processes resilient – to be both low risk and able to adapt quickly to disruption. To handle risk and disruption, and especially to be able to foresee and prepare for the ripple effect, managers need to have complete visibility of the complex interdependencies in their end-to-end discovery, design, development and commercial processes. To have both a low risk and an agile system, a manager needs to have complete visibility into its processes. This can be achieved through the use of simulation and optimization, which can then be further developed into a supply chain digital twin. The modern techniques of predictive and prescriptive analytics, such as optimization and simulation modeling, are proving to be the only ways capable of achieving this.

What is more, these techniques, together with data analytics and IoT, make possible the creation of an end-to-end digital twin – a special model that represents the state of any innovation as it is now, allowing it to be examined for risk resilience.


Case Studies for use of Digital Twins:

A Digital Twin for Pharma/MedTech RnD
A Digital Twin for Pharma/MedTech Supply Chain
A Digital Twin for Pharma/MedTech Manufacturing
A Digital Twin for Pharma/MedTech Market Access
A Digital Twin for Pharma/MedTech Consumer Partnership/Engagement/Education
A Digital Twin for Pharma/MedTech RWE


A Detailed Case Study for Digital Twin of Supply Chain:
Are you using your supply chain data effectively? Is your supply chain transparent and agile enough to quickly adapt to a changing environment? What are supply chain design best practices? This supply chain design module will give you a comprehensive view on designing end-to-end supply chain processes, including how to:
a) Build a digital twin of your supply chain, end-to-end;
b) Conduct experiments with your supply chain in a risk-free environment;
c) Capture a supply chain network’s real-time statistics;
d) Consider risks in your supply chain when developing a master plan;
e) Enhance the business performance of your logistics network


Course Outline:

a) Risks in Digital, Agile Pharma/MedTech
b) Ripple Effect
c) Protecting against the Ripple Effect
d) Tools to improve Resilience: Simulation and Optimization
e) Digital Twins: Modeling + Simulation + Optimization + Real-world Data Analytics


Detailed Course Contents (This is a Framework – will be customized to client needs):