Digital twins represent the shape of physical objects in 3D. A virtual twin experience starts with designing a 3D model that represents the shape, dimensions and properties of a physical product or system. Simulations are run on that virtual model to explore how the product will behave when assembled, operated or subjected to a range of events. The presentation elaborates through practical examples and software solutions how modeling and simulation can aid in having better products to market faster in the era of digitalization. If you have further interest contact us to know more and see how we can help with a consulting based approach.

1. Digital Twin based Product
Development in Life Science
Industry – Sustainable &
Predictable Success Path
www.VIAS3D.com
Confidentiality Statement: Any technical and commercial information contained in this document should not
be disclosed or shared with any third-party other than the end client without written prior approval from VIAS.
May 2023
Dr. Arindam Chakraborty, CTO – Engineering Services
achakraborty@vias3d.com
https://vias3d.com

2. Engineering Services - Global Excellence
2
CONFIDENTIAL
Client First
Quality & Integrity
Excellence
Sustainability | Innovation | Efficiency

3. VIAS3D in Life Science
3
CONFIDENTIAL
Ingredient Screening
Implant Design
Electromagnetic Field Effect
• Applications:
• Orthopedic Implants
• Stents
• Drug Delivery
• Heart valves
• Smart Health Stent
Vapor / Particulate Dispersion
Bioimpedance
Device
Blood Flow
Smart Health

4. Digital Twin and Beyond
4
CONFIDENTIAL
Going beyond digital twin technolog
What is the difference between a digital twin and a virtual twin?
• Digital twins represent the shape of physical objects in 3D.
• A virtual twin experience starts with designing a 3D model that
represents the shape, dimensions and properties of a physical product or
system. Simulations are run on that virtual model to explore how the
product will behave when assembled, operated or subjected to a range of
events.
Example:
• Using a virtual twin of the human body, your doctor could simulate what
impact medicine could have on your brain should you ever have
Alzheimer’s
• Using a virtual twin view of each person’s unique heart and real world
data from similar hearts, you predict the likelihood of developing heart
disease.
• We can also simulate the impact of certain drugs on the cells in an
individual’s heart using its virtual twin – something the more simple digital
twin technology could never do!

5. Medical Device Market Outlook
5
Medical Device Market Outlook:
• The global medical devices market size was USD 465.55 billion in 2022
• Based on analysis [1], the market is projected to grow to USD 657.98 billion in 2028
• The growing prevalence of chronic diseases, and the increasing emphasis of healthcare agencies towards early diagnosis
and treatment, is leading to increasing number of patients undergoing diagnostics and surgical procedures
• The riser in the number of inpatient admission and the increasing number of surgical and diagnostic procedures is fueling
the demand for medical device
CONFIDENTIAL
[1] https://www.fortunebusinessinsights.com/industry-
reports/medical-devices-market-100085

6. Testing Based Design
6
CONFIDENTIAL
Medical Device product development is dominated by in-vivo testing
R&D costs are already driven strongly by expensive physical testing and trials. Considerations of testing and
trial costs already strongly influence the development program portfolio.
Design
Bench test
Virtual Bench
test
Animal tests Animal “Trial” Clinical Trial Patient Population
Cadaver
Fail, Learn & Revise
Candidate
device
YEARS
Source: Levine 2019
SIMULIS LS Market Opportunity.pptx
$ $$ $$ $$$ $$$$$$
$
$
This will worsen as patient populations grow to encompass more extensive patient variation and complex interaction
of medical conditions where one size will fit only a few. Physical methods will become prohibitively time consuming
and expensive.

7. 3DEXPERIENCE Platform
7
CONFIDENTIAL
Multiphysics
(Structures,
fluids,
electromagnetics,
thermal,
acoustics etc.)
Fatigue and Life
Assessments
Process
Automation,
Design Studies,
and parametric
optimization
Non-parametric
optimization
Virtual Human
Simulations
3DEXPERIENCE Platform
Simulation data management Collaboration

8. Better targeted and
lower risk In-Vitro and
In-Vivo testing
In-Silico testing and
trials now possible
Greater acceptance
of In-Silico by
regulatory bodies
DISCOVERY
+
IDEATION
INVENTION
+
PROTOTYPING
PRE-
CLINICAL
CLINICAL
REGULATO
RY
DECISION
POST-
MARKET
MONITORING
PRODUC
T
LAUNCH
ASSESSMENT BASED ON REVIEW
OF PRE-MARKET SUBMISSION
→ DEVELOP
→ VALIDATE→ DESIGN →
→
BENCH
TEST
→
REDESIGN
→
DESIGN & DEVELOPMENT PHASE INVESTIGATIONAL PHASE
Medical device
development pathway, ref.
FDA.gov
SIMULATION EVERYWHERE
Quality
Objectives:
Innovate for
better
outcomes and
minimum
patient risk
Time
Objectives:
Reduce
development
timelines
Cost Objectives
Reduce overall
development costs
and economic risk
Why Simulation?
CONFIDENTIAL

9. Simulation in Life Science
CONFIDENTIAL
• What if simulation could reduce the overall cost of a program by 10%? SIMULIA has the capabilities, and we are now
formally developing the proof of savings potential - with the FDA-CDRH, and with our customers.
Let us together make this year when you prove to your satisfaction that:
• In Silico trials can be done, and can be an advantageous augmentation to product ideation, development, validation and
approval.
• By dramatically changing the entire cost model of simulation, an In Silico trial can be completed with the necessary
economic advantage over physical validation methods, and that the net value will meet or exceed RoI targets.
Cycle
times
Cost of
validation
Pre- and Post-market
Patient Risk
Non-compliance
Use In Silico to reduce the drivers of cost
COST
https://www.outsourcing-pharma.com/Article/2019/07/24/The-Living-Heart-
FDA-renews-contract-with-Dassault-to-evaluate-3D-simulation-virtual-patients

10. Realistic Simulations
10
CONFIDENTIAL

11. Regulatory Space & Standardization
11

12. FDA Support
CONFIDENTIAL
• Computational Modelling and Simulation - CM&S can play a role in one of the FDA’s strategic priorities, such as:
• ‘Stimulate Innovation in Clinical Evaluations and Personalized Medicine to Improve Product Development and Patient
Outcomes, would involve the development of Computational models of cells, organs, and systems, such as virtual
physiologic patients, to better predict product safety and efficacy and performance of medical products.’ - FDA
The FDA Vision is:
Quick and predictable access of innovative
technologies to patients enabled by CM&S

13. Computational Modelling and Simulation (CM&S) Projects
The Computer Modeling and Simulation (CM&S) Projects were developed by Medical Device Innovation Consortium
(MDIC) to achieve the delivery of medical product solutions in a responsible, patient sparing way that balances the
desire for certainty in the device performance while limiting the delay in patient access associated with increased
certainty through the use of computer modeling and simulation as valid scientific evidence.
Projects:
• ENRICHMENT (in Collaboration with Dassault System and FDA)
• Blood Damage Modeling
• Virtual Patient (VP) Model
Based on stakeholder input, the steering committee formed working
groups tackling issues in 7 priority areas operated by member volunteers.
• Combining simulations and experiments to inform clinical trials.
• Simulation of the heart, vasculature, and related medical devices.
• Modeling and simulation in orthopedics.
• Neurostimulation electrochemical mechanisms of damage identification.
• Magnetic resonance-induced heating.
• Libraries for publicly sharing models, inputs, and validation data.
• Simulation of blood damage, hemolysis and thrombosis.
CONFIDENTIAL
https://mdic.org/

14. ENRICHMENT Project
In 2019, the Dassault Systèmes announced the five-year extension of its collaboration with the U.S. Food
and Drug Administration (FDA).
CONFIDENTIAL
Key Points:
• An in silico clinical trial is underway with the 3DEXPERIENCE
platform to evaluate the Living Heart simulated 3D heart for
transforming how new devices can be tested.
• Five-year extension of their collaborative research agreement
aims to spur medical device innovation by enabling innovative,
new product designs.
• Both Dassault Systèmes and the FDA recognize the
transformative impact of modeling and simulation on public
health and patient safety
“Our collaboration with the FDA underscores the relevance and sustainability of digital twin
experiences created with the 3DEXPERIENCE platform to test devices and drugs in scientific and medical innovation,”
said Claire Biot, Vice President, Life Sciences Industry, Dassault Systèmes

15. ASME V&V 40 - Assessing Credibility of Computational Modeling
15
ASME V&V 40 - 2018
• In 2018 ASME introduced its first verification and validation
standard for specific application to medical devices.
• This standard provides a framework for assessing the relevance
and adequacy of completed V&V activities that establish
credibility of a computational model.
• The standard shows the guidelines for assessing and
quantifying the accuracy and credibility of computational models
and simulations
• Standardized computational modeling techniques to aid in the
design, testing, and regulatory review of medical device
CONFIDENTIAL

16. Assessing the Credibility of Computational Modeling - Draft Guidance
16
Assessing the Credibility of Computational Modeling - Draft Guidance –
December 23, 2021
The Draft Guidance describes a 9-step framework for evaluating the credibility
of CM&S information submitted in pre-market applications.
There are three types of credibility evidence (code verification, calculation
verification, validation) and ten distinct categories within these three types of
credibility evidence that are discussed in the Draft Guidance.
• Code verification provides evidence demonstrating that a computational
model implemented in software is an accurate implementation of the
underlying mathematical model.
• Calculation verification determines the solution accuracy of a calculation.
• Validation can be provided by population-based evidence, emergent
model behavior, model plausibility and model calibration evidence.
CONFIDENTIAL

17. Data Security in Life Science and 3DEXPERIENCE
17
Personal data is at the very core of every life science business
Protecting data from unauthorized access and data corruption is key to
avoiding the inconvenience and upheaval of lost data, financial or even
criminal penalties, loss of reputation and patient trust, and associated
costs involved with data recovery.
When it comes to working in a cloud environment, the security landscape
is primarily focused on concerns around infrastructure, inventory and
configuration, encryption, monitoring and logging, and penetration testing.
3DEXPERIENCE platform constantly improves the confidentiality,
integrity, and availability of information and protection of the following:
• Customer intellectual property and user data, PII included
• Cloud availability and resilience
• Compliance with applicable cybersecurity and data protection
regulations and standards
CONFIDENTIAL

18. Digital Transformation – Deep Dive
18

19. Digital Twin Benefits
A virtual twin has benefits beyond helping humans get more precise diagnoses
and efficient treatments. Industry experts, researchers, and even patients can
visualize, test, understand and predict what cannot be seen:
• Surgeons can practice procedures on exact replicas of their patients before
the actual operation begins
• Medical devices and therapies can be developed, tested and manufactured
• Further understand of politicians and make them to propose new health
policies to improve healthcare for the general public
• Help educate and empower patients and their families according to their
disease and the available treatment options
By analyzing the continuous cycle of data generated in the virtual and real worlds,
we can make the life sciences & healthcare industry more efficient, innovative
and sustainable.
CONFIDENTIAL

20. Support for “Virtual Patience”
CONFIDENTIAL
“Modeling and simulation can help to inform clinical trial designs,
support evidence of effectiveness, identify the most relevant
patients to study, and assess product safety,” said In some
cases, in silico clinical trials have already been shown to
produce similar results as human clinical Trials” Tina Morrison,
Deputy Director in the Division of Applied Mechanics, Office of
Science and Engineering Labs, Center for Devices and
Radiological Health, FDA, 2019
• The Living Heart Project demonstrated the power of the virtual
twin to combine and apply cross-disciplinary experience –
creating a path to virtually model other organs and systems in
the body, starting with the brain and then moving to the lungs.
• It opened the door to not only the Living Lung and the Living
Brain, but to models of many elements of human physiology.
• Cristina Pop, a clinical research assistant at McGill University in
Montreal, is using the Living Heart model to understand the
impact of COVID-19 on people with heart condition.

21. What is the Living Heart Human Model?
CONFIDENTIAL
High fidelity representation of a normal (healthy) 4-chamber adult male
human heart – first commercial-grade simulated model
The dynamic response of the Heart Model is governed by a realistic
representation of the electrical, structural, and fluid (blood) flow physics.
Possible to study abnormal (diseased) cardiac function by modifying the
loads, boundary conditions, geometry, and/or material properties
Possible to add external parts representing medical devices to study their
influence on cardiac function and explore treatment options.
Based on SIMULIA finite element simulation technology – market-leading
nonlinear structural mechanics and multiphysics for more than 35 years

22. Living Heart Model – Complexity & Accuracy
CONFIDENTIAL

23. The Virtual Brain
CONFIDENTIAL
• The Virtual Brain serves as a powerful research tool that has the potential to utilize big data and to
develop and test advanced theories of brain dynamics.
• This approach naturally extends into clinical applications, deriving parameters that both relate to
biophysics and clinical outcome, thereby addressing current limitations in treating and predicting
outcome in neurological disorders such as epilepsy.

24. Simulation of Human Brain
CONFIDENTIAL
The mechanics of Decompressive Craniectomy:
Personalized Simulations
(https://pdfs.semanticscholar.org/f94a/512455c9eee0d
25a33e854c9bb9e78b77109.pdf )
Finite Element Analysis of Head Impact in Contact Sports
http://www.simulia.com/SCCProceedings2012/content/presentations
/Guttag_Brown_5112012_v2.pdf
Developing a Finite Element Head
Model for Impact Simulation in Abaqus
https://www.3ds.com/fileadmin/PRODUCTS/SIM
ULIA/PDF/scc-papers/2015/head-model-
simulation-abaqus-15.pdf

25. Digital Knee Twin
Problem Statement:
• Create virtual personalized models for each patient starting from imaging and then
use realistic simulation to determine the best possible treatment for that individual.
Values:
• The 3DEXPERIENCE is a key enabler to the success of Digital Orthopedics, offering:
• The potential to connect to hospital imaging systems, enabling the proposed
solution as a clinical decision-making service to orthopedic surgeons.
• Digital twin generation to realistically render the pathology and to better plan the
surgical approach.
• A machine learning to enrich the company’s knowledge and improve outcomes of
diagnostic support and personalized surgical simulation.
CONFIDENTIAL

26. Virtual Surgical Planning
Problem Statement:
• If we personalize surgical implants, can we radically improve a patient’s quality of life?
Values:
• The 3DEXPERIENCE® platform integrates complete surgical workflows from Idea to
Incision, including:
• Virtual surgical planning for 3D pre-surgical simulation
• Customized anatomical models for evidence-based mock surgical evaluation
• Intraoperative patient-specific surgical guides for surgical precision
• Personalized implants for perfect fitment
• Get a complete control over the surgical procedure and value-chain, resulting in
minimal tissue damage, reduced hospitalization time and lower cost-of-care.
CONFIDENTIAL

27. Virtual Reality (VR) Laboratory
CONFIDENTIAL
• “We are trying to develop a VR lab where students will be able to visualize computational
simulations,” says Prof. Damien Lacroix, Research Director of Insigneo, UK.
• “We would like to develop a portal where doctors of all backgrounds will be able to upload
imaging data from their patients. We then would use that information in a workflow in which we
would be able to preserve the images, develop patient-specific models, and eventually provide
the clinicians with predictions about the outcome of any given treatment”, says Prof. Damien
Lacroix
• Benefits:
• Study, interact with, and create biomechanical models based on real human geometry.
• Big savings from adopting simulation tools
• Reduce time-to-market
• Make medicine more accessible to patients around the world
https://blogs.3ds.com/simulia/applying-simulation-to-medicine/

28. Digital Initiatives by Industry Players
28
• Of the 50 biggest employers in the medical devices industry, Stryker Corp was the company which
referred to artificial intelligence the most between July 2020 and June 2021.
• 3D Systems and Stryker announced an exclusive distribution partnership for VSP (Virtual Surgical
Planning) and anatomical models for the craniomaxillofacial specialty. Established by 3D Systems,
VSP technology received FDA market clearance as a service-based approach to personalized surgery,
combining expertise in medical imaging, surgical simulation and 3D printing.
• Zimmer Biomet Introduces ZBEdge Connected Intelligence suite of integrated robotics and digital
health technologies. The ZBEdge Connected Intelligence Suite enables healthcare professionals to
connect the dots between procedural and patient data at every stage of the surgical journey.
• “Medtronic will become the first company to be able to offer an integrated solution including artificial
intelligence driven surgical planning, personalized spinal implants and robotic assisted surgical
delivery, which will significantly benefit our customers and their patients.” – Business Wire, News, 2021
CONFIDENTIAL
https://www.stryker.com/us/en/about/n
ews/2018/3d-systems-and-stryker-
team-up-to-advance-personalized-
surgery-.html
https://www.medicaldevice-
network.com/features/insilicotrials/
https://investor.zimmerbiomet.com/news-
and-events/news/2021/03-31-2021-
121518090
https://www.businesswire.com/news/ho
me/20200714006115/en/Medtronic-to-
Acquire-Medicrea

29. Modeling & Simulation
29

30. Patient-Specific Bone Geometry
30
The process for creating patient-specific model is as follows:
• A 3D (CT or MRI) image of the patient is acquired
• These images are structured as a stack of 2D slices and are manually/semi-automatically segmented
• These segment 2D slices are combined to generate 3D bone geometry
• These bone geometry can then be directly imported into Abaqus to create patient-specific models
CT or MRI scan (Step 1)
2-D cross
Sections (Step 2)
3D bone geometry
(Step 3)
Import geometry in
Abaqus (Step 4)
CONFIDENTIAL

31. Tibial Implant Analysis Using Patient Specific Data​
31
• Case Study: The objectives of this study was to make a relative comparison between two implant tray
materials (Co-Cr-Mo and Ti-Al) at the tibia-implant interface under the constant loading condition.​
• Tibia bone geometry represented through a cubic volume is reconstructed using images from a µCT scan
of the tibia sample image.​
• A representative volume element (RVE) approach was used to capture effective structural and material
properties of tibia.
Bone
Air
CONFIDENTIAL
Abaqus, RVE, Knee
Presented at ORS 2022 and SIMULIA Conference 2023

32. Knee Implant Simulation
32
Challenges:
• Uses a combination of patient specific bone and Abaqus FEA for a variety of product
design and development studies
Values:
• Validation of FEA provides metrics that can be incorporated into future design
requirements and recommendations to surgeons.
• Reduce Development time and increase confidence in the kinematic performance
design
• Improvement of designs enable patients to live a full, active life after surgery.
Solution:
• Analyzing contact position in patients who had undergone a full knee replacement
• Simulation of leg bone resorption occurring where the tibia meets a metal implant.
• Comparing different geometries of implant models and their effect on gait and knee
kinematics.
Abaqus, Knee, Optimization

33. Tibial Bone Graft in Total Knee Arthroplasty
33
• Case Study: Worked with a client to scan the bone, use scan images
to generate a micromechanics model for evaluating macroscopic
properties and then used that in a representative bone model to
evaluate two design variations of knee implants
• Achieving stability of the tibial implant is essential following
cementless total knee arthroplasty with bone grafting.
• Analyze the distribution of localized stresses, deformation and
contact pressure distribution on implants and the bone
• Save time and effort over physical testing.
CONFIDENTIAL
Abaqus, Arthoplasty, Design

34. Shoulder Implant Modelling
34
Challenges:
• Stress shielding around the stem component of shoulder
replacement implants can promote unfavorable bone remodeling
Values:
• Study of osteopenic and osteoporotic bones
• Investigation the bone-implant mechanics under various implant
design
• Optimization of implant design
Solution:
• Evaluation of bone and implant stresses for various loading
scenarios
Abaqus, Shoulder, Optimization
Workflow Diagram
CONFIDENTIAL

35. Hip Implant Design
35
Challenges:
• Design process is expensive and time consuming
• Predefined set of implant sizes to serve all patients
• Micromotion between the femur and the metal stem
Values:
• Reduce the expensive experimental trials
• Retain the mechanical performance
• Reduce the cost of design
Solution:
• Optimize the implant geometry and position of the implant
• Evaluation of bone and implant stresses for various loading
scenarios
Abaqus, Implant Design, Optimization
CONFIDENTIAL
Ploeg H-L, Bürgi M, Wyss U P.
‘Hip stem fatigue test prediction’.
International Journal of Fatigue 31
(2009) 894-905.

36. Electromagnetics in Life Science
• Wearable and implantable devices
• Treatment of cancer or tumor using
electromagnetic energy
• The use of electromagnetic waves to
image the internal parts of the body
• Magnetic Resonance Imaging
Hearing Aids
Pace-Makers
Microwave
Imaging
MRI
Microwave
Imaging
MRI
CONFIDENTIAL
CST Studio, Life Science, Electromagnetics

37. CFD in Life Science
Flow through Aneurysm
Blood Pumps
Microfluids Velocity profile during a Sniff
Aortic Coarctation - Windkessel model
Catheter – Drug Delivery
CONFIDENTIAL

38. Medical Device Lab Testing Automation with BIOVIA
CONFIDENTIAL
BIOVIA offers a solution that helps medical device manufacturers create and perform
analytical device testing efficiently and compliantly, reducing lab testing cycle times,
capture data and preserve it for future use, while eliminating paper and non-value
adding manual steps
Value of BIOVIA’s Solution for Medical Device Lab Automation:
• 50% reduction in analytical testing cycle time
• 50% less time spent on data review
• 40% less resources needed
• 15-25% improved scientist productivity

39. Democretization & AI-ML
39

40. Abaqus Knee Simulator (AKS)
Challenges:
• Expensive prototype cost and physical testing
Values:
• Automated modelling tool
• Build advanced knee implant simulations
• Based on well-known implant evaluation workflows
Solution:
• Five workflows which cover various aspects of knee implant design
evaluation
• Provides advanced tool to manufacturer to evaluate knee implants
early on in design phase
Abaqus, AKS, Automation
Basic TKR Loading
Tibiofemoral Constraint​ Wear Simulator
Contact Mechanics Implant Constraint
CONFIDENTIAL
40

41. Examples – Abaqus AKS Plug-in
41
CONFIDENTIAL

42. 42
MBSE for Life Science
CONFIDENTIAL
System Structure:
• Requirements traceability from development to market
• Model interactions between humans and devices
• Single platform for total knowledge capture
Values:
• Accelerate cycle time of medical device development for patients
• Promote safety and effectiveness throughout design
• Ensure requirements and regulations are met for FDA compliance and
approval
• Advance existing therapies and health care
• Streamline Research and (R&D) Development efforts

43. Simulation Using AI – Reduce Computation
Back to Agenda
RAW DATA
(INPUT)
DATA
STRUCTURING TRAINING
ML, ANN
PREDICTIONS Output of
Interest (stress,
deformation,
pressure,..)
ML, ANN,
autoencoder
CNN, RNN
CONFIDENTIAL

44. Virtual Patients: Machine Learning
Back to Agenda
CONFIDENTIAL
High Fidelity Mechanical LHM (Baseline)
 1 heartbeat = 1000 CPU hours
 Treatment outcome prediction
 Rich physical foundation
Machine Learning (ML) Model
 1 heartbeat = 1 CPU second
 Explore disease state space
 Deduce patient-specific
inputs for baseline model
First Principles/Mechanistic Model to generate Virtual Data for Machine Learning
Low Fidelity Mechanical LHM
 1 heartbeat = 1 CPU
second
 Based on human
cardiology
 Calibrated using baseline
model
 Augment virtual data from
baseline model
 Validate physiological basis
of ML model outputs
Disease- and Patient-specific input
parameters

45. Thank You
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