University Report: Digital Twin in Healthcare Industry Analysis

This report delves into the burgeoning field of digital twins within the healthcare industry, examining their potential to revolutionize patient care and medical innovation. It provides an overview of digital twins, defining them as virtual replicas of physical assets, procedures, and even people, capable of simulating real-world scenarios. The report highlights the technology's role in personalized medicine, leveraging individual and population data to tailor treatments. It reviews existing literature on the subject, exploring various methods and approaches for implementing digital twins in healthcare, including integrating business goals, utilizing single digital twins, and incorporating compound digital twins. The report also discusses the benefits of digital twins, such as accelerating medical innovation and regulatory approval. It addresses the challenges associated with implementing digital twins, including the need for 3D models and digital manufacturing adoption. The report concludes by emphasizing the ethical and conceptual implications of this technology, with suggestions for future research, recommending a critical and beneficial use of digital technology within the healthcare domain. The study is based on data collected from online resources.

Running head: DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
Digital Twin in the Health Care Industry:
A Revolutionary View of How the Real Meet the Virtual
Name of the Student
Name of the University
Author note

1DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
Abstract
The increasing significance of digital twins in the internet of things projects, it is required to
research on the use of digital twins in health care industry. On the other hand, healthcare is
rapidly embracing digital twin technology for fulfilling the goal to deliver data driven
personalized medicine. These are developed based on computer and models, which are fed
individual as well as population data. In this perspective, the study covers introduction of the
concept, literature review and methods or approaches used for the topic. In addition, scope for
the research is also discussed in the present study.

2DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
Table of Contents
Introduction..........................................................................................................................3
Literature review..................................................................................................................3
Methods/ Approaches..........................................................................................................7
Conclusion and implications................................................................................................8
Scope for future research.....................................................................................................9
References..........................................................................................................................10

3DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
Introduction
Digital twins are the replica of physical assets, procedures, people as well as places,
which can be utilized for multiple purposes. The digital presentation provides components as
well as dynamics of the operating as well as living in internet throughput the lifecycle. The
personalized medicine generally uses fine-grained data on individual persons. In this perspective,
digital twins in the field of engineering give a framework in order to analyze the emerging data
drive practices regarding healthcare and conceptual as well as ethical implications for therapy,
human improvement and preventative care. The researchers are aided by the digital presentations
of human physiology in the studies of diseases, devices as well as drugs.
Digital Twins is referred as particular engineering paradigm, which can dynamically
reflect the status of the artifacts. A digital twin provides a safe environment where the influence
of possible change on the performance of the system through experimenting on a specific virtual
version of the system. Hence, digital twins can make prediction of the issues before occurring
and finding optimal solutions along with minimizes the risks.
The study has the purpose to deal with ethical aspects of the technology as well as its
applications. The advantages of the technology are analyzed with possible limitations that raise
specific questions regarding the future of digital twin. In addition, the study is based on the data
from online resources as well as generalized approach that is limited in the scope. On the other
hand, the study provides recommendations as well as suggestions in order to use digital
technology in the most critical way, which provide benefits to the society.
Literature review

4DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
Overview: Digital twin is used for explaining a computerized version of the physical
assets and procedures. It includes sensors for collecting data in order to represent real-time
information regarding physical asset. These are virtual replicas of the physical devices that the
scientist as well as IT pros utilizes for running simulations before developing and implementing
the actual devices. An example of using digital twin is optimizing machines with maintenance of
power production equipment like turbines for power generation, jet engines as well as
locomotives. Personalized medicines generally start from the process of assumption that is
refined as mathematical models of the patients that is fulfilled through big bio data. It will be
helpful in driving precise (Bruynseels et al., 2018). Hence, as an alternative of based on the
medical interventions on the average person’s responses and digital models that carry promise
for tailoring healthcare. The availability of molecular reading technologies as well as developing
tracked health as well as parameters of lifestyles. It results in digital representation of the
parameters. Gaggioli (2018) stated that the approaches of digital twins in health care have
potential increasing resolution and comprehensive way by which people are able to define
normality and diseases.
In other words, digital twin is a dynamic representation of a particular device fed with
data from embedded sensors as well as software. It provides accurate real-time status of physical
device. When adding the power of computational technologies like artificial intelligence,
identification of the potential issues before they arise, allow to repair or replace critical elements
(El Saddik, 2018). For an instance, smart analysis of the data transmitted from sensors during
fight is able to provide 15 to 30 days advanced notice regarding potential failures.
Benefits of digital twins: Healthcare is embracing digital twin technology. The target of
the trend is delivering the data driven personalized medicine. These are developed on computer

5DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
based named as Silico models with fed individuals as well as population data. The digital
representations of human physiology are important in terms of new drugs as well as devices. The
industry leaders in healthcare as well as FDA authorities have suggested that digital twins assist
in accelerating medical innovation as well as regulatory approval (David, Lobov & Lanz, 2018).
Digital twins are implemented optimizing aerosol deposition of medication. It helps to identify
the requirements of maintenance before these arise.
The use cases for digital twin technology is varied as well as combined with the sensors,
cognitive, data for making digital simulation, analytics and assets where a course overlay with
digital information onto the physical world. It requires to be leveraged for designing of the
products as well as service purposes. These can remove silos, inefficiencies and errors as well as
huge resource in order to work with the models. Datta (2016) stated that the approaches to
healthcare are developed on dynamic as well as high-resolution digital models. These are based
on medicine and developed the fact. It is closer to the process of engineering artifacts and
attempts are usually undertaken developing the models of heart. The idea of digital twins
provides viable conceptual models on the key concepts in the healthcare practice. The
approaches of digital twin on healthcare have the possibility in increasing resolution as well as
comprehensiveness at which a person can define diseases as well as normality. Hence, high
resolution models of the process need to be operated in scenario.
Tarassenko and Topol (2018) mentioned that digital twins have scope to play two
different roles in healthcare such as designing hospital and management along with patient care.
The models are useful to plan the beds, schedules of the employees along with operating rooms
in order to maximize the care to patients. On the other hand, digital twins of hospitals allows the
managers trying out the solutions to the issues like implementation of the best performing

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solutions. On the other side, the software can make a turn of a 2D scan from an individual human
as well as blood flow in the heart (Datta, 2016). In addition, the user can manipulate the process,
sticking in the pacemakers as well as reversing its chambers. It is able to bridge the gap between
real with a virtual system. As smart machines are considered better compared to humans
accurately as well as constantly capturing and making communication with data. The technology
is able in picking up inefficiencies as well as issues faster that helps in saving time and money.
Components of digital twin of a device: In order to predict when a device requires
maintenance, it is required for the data from the device. Artificial intelligence can assist in
identifying the patterns in data. However, telling the patterns is considered meaningful. It is also
important to focus on understanding the technology for the process. AI augments have human
capabilities (Landolfi et al., 2018). Thus, when developing the predictive models, it becomes
important pairing the data scientists with the engineers and deep domain knowledge.
Digital twins of the devices are not useful when the device is in use. As the digital twins
are already developed at the time of developing products, they enable the process of rapid
prototyping of new or enhanced technology. Use of digital twins in developing the vehicles can
endure more conditions (Varghese et al., 2018). The teams in formula one create digital twins of
the cars that allow rapid design, test as well as manufacture enhanced parts for upcoming races.
Challenges for using digital twin: The first step of implementing digital twin idea needs
3D models. The CAD trends survey by the business advantages shows that there are two third of
the users surveyed out 610 still rate 2D drafting, which is highly significant (Torkamani et al.,
2017). On the other hand, for successful deployment of a digital twin concept, the key is helping
as well as supporting small suppliers in the process of adopting digital approach. The digital

7DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
manufacturing as well as Design Innovation Institute is giving efforts in the direction through the
US funded research and development organization (Kricka, 2018). It has currently issued a
project for demonstrating technology for the digital twins from supply chain participants.
Methods/ Approaches
In order to conduct a research on digital twin in the health care industry, positivism
philosophy is useful. On the other hand, descriptive research design and deductive research
approach helps in conducting the research in proper way. Secondary data collection technique is
used in order to collect data on the use of digital twins (Reid & Rhodes, 2016). Qualitative data
analysis technique can be appropriate to analyze the data gathered for the research.
On the other hand, for the disruptive business outcomes, the leaders of industry need to
follow the approaches like following the business goals, integration with a single digital twin and
incorporating compound digital twins.
Figure 1: Approaches of Digital twins
(Source: Al-Ali, Gupta & Nabulsi, 2018, p.5001)

8DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
Focus on business goals: The range of benefits from streamlining operations of the
industry to the process of identification of the risks related to the devices breakdown to
developing equipment faster. However, leaders need to list down the business goas that are the
objective of digital integration strategy (Paritala et al., 2017). The technology leaders will
comprehend the devices and materials that are best suited with digital twins.
Integration with a single digital twin: Planning to adopt digital twin fir the industry is
related to several IoT connected devices and need multiple endpoints (Anderl et al., 2018). For
an example, manufacturer and an organization have planned for digital twin for the equipment; it
is required to observe the points like sensors as well as actuators will assist in collecting
information regarding the equipment in real time. An application will assist tracking the status of
the equipment with the help of smart phone (Tao et al., 2018). In addition, proper technologies
will be helpful to check for compliance with the data, which is collected and shared.
Incorporating compound digital twins: Integrating compound digital twins are related to
the complex IoT connected things that should leverage advanced technologies like artificial
intelligence that can help in providing products that can be connected with the sensors and will
be fitted for complicated digital twins. Adoption of digital twins for the industry is non-
negotiable for most of the organizations for innumerable advantages that are offered by digital
twins (Bolton et al., 2018). It includes optimized asset management and takes preventive
equipment maintenance along with end-to-end visibility of the products in real time. Hence, not
creation of the future ready strategy for digital twins in order to integrate the components of
digital twins will make irrelevant in the market.
Conclusion and implications

9DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
The concept of digital twins gives a concrete ideas about the instruments in order to
analyze the conceptual as well as ethical aspects of future healthcare as well as human
improvement. On the other hand, digital twins are one of the emerging fields in medicine, which
has possibility to become the main playfield where improvement as well as therapy can be
explored. On the other hand, a comparison between digital twins in the whole populations allows
getting sharper concept on therapy versus improvement. It has the potential to impact on identity
of a person and can be assigned to the specific patterns in the data.
The paradigm of engineering inherent a digital twins that is based on health care and will
raise on social and ethical issues for therapy as well as improvement of the patients. On the other
hand, digital twins can be challenging for equality and even without the application of
improvement technologies. On the other hand, personal digital twins are considered as
asymptotically scenario of data intense.
Scope for future research
Digital twin is one of the virtualized dynamic representation of the industrial procedures,
product or services in the form of model that utilizes the combination of data as well as
intelligence in order to predict, optimize and profile the performance of the industrial asset
through situations. It is an integral part of the industrial internet of things because of allowing the
automated controlling as well as monitoring the industrial assets along with procedures. There is
a future scope on digital twins in the health care industry, with more specific data are restricted
to a specific individual or a group of people and belongs to a specific region or segment. In
addition, providing a specific view regarding the group can be more focused in future study of
digital twins.

10DIGITAL TWIN IN THE HEALTH CARE INDUSTRY
References
Al-Ali, A. R., Gupta, R., & Nabulsi, A. A. (2018, April). Cyber physical systems role in
manufacturing technologies. In AIP Conference Proceedings (Vol. 1957, No. 1, p.
050007). AIP Publishing.
Anderl, R., Haag, S., Schützer, K., & Zancul, E. (2018). Digital twin technology–An approach
for Industrie 4.0 vertical and horizontal lifecycle integration. it-Information
Technology, 60(3), 125-132.
Bolton, R. N., McColl-Kennedy, J. R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., & Zaki,
M. (2018). Customer experience challenges: bringing together digital, physical and social
realms. Journal of Service Management, 29(5), 776-808.
Bruynseels, K., Santoni de Sio, F., & van den Hoven, J. (2018). Digital twins in health care:
Ethical implications of an emerging engineering paradigm. Frontiers in genetics, 9, 31.
Datta, S. P. A. (2016). Emergence of Digital Twins. arXiv preprint arXiv:1610.06467.
David, J., Lobov, A., & Lanz, M. (2018, July). Leveraging Digital Twins for Assisted Learning
of Flexible Manufacturing Systems. In 2018 IEEE 16th International Conference on
Industrial Informatics (INDIN) (pp. 529-535). IEEE.
El Saddik, A. (2018). Digital Twins: The Convergence of Multimedia Technologies. IEEE
MultiMedia, 25(2), 87-92.
Gaggioli, A. (2018). Digital Twins: An Emerging Paradigm in Cyberpsychology
Research?. Cyberpsychology, Behavior, and Social Networking, 21(7), 468-469.

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Kricka, L. J. (2018). History of disruptions in laboratory medicine: what have we learned from
predictions?. Clinical Chemistry and Laboratory Medicine (CCLM).
Landolfi, G., Menato, S., Sorlini, M., Valdata, A., Rovere, D., Fornasiero, R., & Pedrazzoli, P.
(2018). Intelligent value chain management framework for customized assistive
healthcare devices. Procedia CIRP, 67, 583-588.
Paritala, P. K., Yarlagadda, T., Sreeram, R., & Yarlagadda, P. K. (2017, March). Impact of
digital manufacturing on health care industry. Global Science and Technology Forum
(GSTF).
Reid, J. B., & Rhodes, D. H. (2016, March). Digital System Models: An investigation of the non-
technical challenges and research needs. In Conference on Systems Engineering
Research. Huntsville, AL.
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., ... & Nee, A. Y. C. (2018). Digital twin-
driven product design framework. International Journal of Production Research, 1-19.
Tarassenko, L., & Topol, E. J. (2018). Monitoring Jet Engines and the Health of People. JAMA.
Torkamani, A., Andersen, K. G., Steinhubl, S. R., & Topol, E. J. (2017). High-definition
medicine. Cell, 170(5), 828-843.
Varghese, B., Villari, M., Rana, O., James, P., Shah, T., Fazio, M., & Ranjan, R. (2018).
Realizing Edge Marketplaces: Challenges and Opportunities. IEEE Cloud
Computing, 5(6), 9-20.