SaMD or Software as a Medical Device can be described as a software constructed to be used in medical devices. These softwares can be run on different operating systems and virtual platforms. 1. The basic programming model of a SaMD is given below. 2. Different softwares are used for medical purposes, and they include the following: To continue Reading : https://bit.ly/31ItRVc Contact Us: Website : https://bit.ly/2BvO06b Email us: sales.cro@pepgra.com Whatsapp: +91 9884350006

1. Copyright © 2020 pepgra. All rights reserved 1
Challenges and Opportunities in Software Driven Medical Sciences
Dr. Nancy Agens, Head,
Technical Operations, Pepgra
Sales.cro@pepgra.com
I. INTRODUCTION
SaMD or Software as a Medical Device
can be described as a software constructed
to be used in medical devices. These
softwares can be run on different operating
systems and virtual platforms. Examples
of SaMD include:
 standalone softwares running on
general computers, smartphones
and tablets.
 SaMD that can detect interrupted
breathing during sleep by using a
microphone of a smart device.
 SaMD that can analyze the heart
beat rate.
A software can behave as SaMD when it is
run on a medical hardware device, but
does not serve any intended purpose for
the hardware. However, if the software
controls the hardware device or drives it,
then it cannot be called SaMD.
Softwares, when used as medical devices
have several challenges, the major ones
being clinical evaluation, scientific
validity and clinical validation. All these
three must be performed with accuracy as
they are crucial for a successful launch of
SaMD in the clinical market.
 Clinical evaluation of SaMD is
described as a set of ongoing
activities which are conducted to
assess and analyze the SaMD's
safety, performance and
effectiveness.
 Scientific validity/ Valid Clinical
Association of SaMD refers to the
extent of clinical acceptance of the
SaMD's output in terms of concept,
conclusion and measurements. It
ensures that the output of SaMD
corresponds accurately to the
healthcare situations and conditions
in the real world.
 Clinical validation can be described
as the relationship between
verification and validation results
of the algorithm used and the
clincial condition in question.
Clinical validity is determined by
the manufacturer of the SaMD
while developing it before
distribution (pre-market) and when
it is in use after distribution (post-
market).
The basic programming model of a SaMD
is given below.
Different softwares are used for medical
purposes, and they include the following:
1. Advanced analytics - described as a
device which can use big and large
complex data sets from a variety of
sources by identifying and analyzing the
data, and uses this data for medical
devices.
2. Artificial intelligence - described as a
device which mimics human learning and
reasoning. Machine learning, neural
networks and natural language processing
are all different types of AI.
3. Cloud - described as a device which has
an internet based computing system, whcih
provides with computer processing
resources and data. Several resources such
as servers, computer networks and storage
devices can share the pool of data from the
cloud system.
4. Cybersecurity - described as a device
which prevents unauthorized access,
misuse, modification, or denial of use of
any information that can be transferred to
an external recipient from a medical
device.
5. Interoperability - a device that
exchanges and uses information with

2. Copyright © 2020 pepgra. All rights reserved 2
another medical/non-medical product via
an electronic interface.
6. Medical Device Data System (MDDS) -
a software (or hardware) used to transfer
and store data, convert formats of data and
display data of the medical device without
the alteration of parameters of any other
connected medical device.
Figure 1: SaMD Basic Programming Model
Premarket notification is a key element for
the regulation of medical devices. There
are diverse medical products in the market
such as glassware and reagents of
laboratories, spectacles, lenses, etc, which
are not true medical devices. The system
of identifying and classifying generic
devices is crucial for a successful
regulation of such products. To define
safety and effectiveness of all types of
medical devices, the factors taken into
consideration are:
 patient population in question
 labelling and advertising of the
ways to use a medical devise
 balance between benefits and risks
to health when using a medical
device
 reliability of the medical device
The International Medical Device
Regulator’s Forum (IMDRF) seeks to
demonstrate safety, effectiveness and
performance of SaMD. It suggests that a
software used in medical sciences is

3. Copyright © 2020 pepgra. All rights reserved 3
unique with respect to its connectivity. The
manufacturers of softwares related to
medical devices are encouraged to use this
feature of uniqueness to modify the
softwares to suit the real-world
performances.
It is important to ensure safety in the new
technologies used for medical devices, and
the way it is done is illustrated below:
Figure 2: Good quality systems ensure safety of patients
Several opportunities associated with
software driven medical sciences are
discussed below.
 Techniques of advanced analytics
can be used to analyze datasets
which normally cannot be analyzed
by humans. These include big and
complex data sets that can only be
analyzed by specialized softwares.
 Advanced analytics can discover
new patterns in data.
 A patient's melanoma can be
analyzed by an imaging system
through comparison with a
repository of past melanoma data
such as images, diagnosis and
treatment plans.
 A personalised 3D model of the
coronary arteries can be created
from a standard CT by a software,
and the model can predict the
impact of blockages on flow of
blood through the arteries.
 Algorithms used in imaging
systems of artificial intelligence

4. Copyright © 2020 pepgra. All rights reserved 4
can provide diagnostic information
on skin cancer.
 AI used in a smart ECG device can
estimate the probable occurrence of
acute cardiac ischemia (ACI)
 A mobile colposcope can use
images stored in cloud and retrieve
it for use in the doctor's chamber
later on.
 Cardiovascular images acquired
from magnetic resonance scanners
can be analyzed by a software
through a cloud-based picture
archiving and communication
system.
 Data of patients from a pulse
oximeter can be used by a designed
infusion pump to change the
settings of another infusion pump
as per requirement.
 A software can be used to adjust
the pressure, flow settings and
volume of air of a ventilator, and
also to collect output data about a
patient's carbon dioxide level.
 Patient data from several devices
can be received by a centralized
patient monitoring system.
 medical data can be electronically
displayed
Given below is the total product life cycle
of a medical device – the science cycle and
the regulatory cycle:
Figure 3a: Science cycle

5. Copyright © 2020 pepgra. All rights reserved 5
Figure 3b: Regulatory Cycle
REFERENCES
1. https://www.fda.gov/medical-devices/digital-
health/digital-health-criteria
2. http://www.imdrf.org/docs/imdrf/final/technical/imd
rf-tech-170921-samd-n41-clinical-evaluation_1.pdf
3. https://www.ncbi.nlm.nih.gov/books/NBK209791/p
df/Bookshelf_NBK209791.pdf
4. Kramer DB, Tan YT, Sato C, Kesselheim AS.
Ensuring medical device effectiveness and safety: a
cross--national comparison of approaches to
regulation. Food Drug Law J. 2014;69(1):1-23, i.
PMID: 24772683; PMCID: PMC4091615.