Software Driven Medical Challenges and Opportunities in Software Driven Medical Sciences | Pepgra

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CHALLENGES AND
OPPORTUNITIES IN
SOFTWARE DRIVEN
MEDICAL SCIENCES
An Academic presentation by Dr. Nancy Agens,
Head, Technical Operations, Pepgra Group
www.pepgra.com Email sales.cro_at_pepgra.com
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Today's Discussion
OUTLINE OF TOPICS
Introduction
Challenges of Medical Device Software
Different Softwares used for Medical Purposes
Premarket Notification
International Medical Device Regulators Forum
Opportunities Associated with Software Driven
Medical Sciences
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Introduction
SaMD or Software as a Medical Device can be
described as a software constructed to be used in
medical devices.
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.
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Challenges of Medical Device Software
Softwares, when used as medical devices have
several challenges, the major ones being clinical
evaluation, scientific validity and clinical
validation.
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.
Clinical validation can be described as the
relationship between verification and validation
results of the algorithm used and the clincial
condition in question.
Contd..
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Figure 1 SaMD Basic
Programming Model
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Different Softwares used for Medical Purposes 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
Artificial Intelligence described as a device
which mimics human learning and reasoning. 3.
CLOUD
Described as a device which has an internet based
computing system, whcih provides with computer
processing resources and data.
Contd..
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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
another medical/non-medical product via an
electronic interface.
6. MEDICAL DEVICE DATA SYSTEM (MDDS)
A software used to transfer and store data,
convert formats of data and display data of the
medical device without the connection of any
other medical device.
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Premarket Notification
Premarket notification is a key element for the
regulation of medical devices.
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
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International Medical Device Regulators Forum
The International Medical Device Regulators
Forum (IMDRF) seeks to demonstrate safety,
effectiveness and performance of SaMD.
It suggests that a software used in medical
sciences is 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
Contd..
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Figure 2 Good Quality
Systems Ensure Safety
of Patients
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Opportunities Associated with Software
Driven Medical Sciences
Techniques of advanced analytics can be used to
analyze datasets which normally cannot be
analyzed by humans.
Advanced analytics can discover new patterns in
data.
AI used in a smart ECG device can estimate the
probable occurrence of acute cardiac ischemia
(ACI)
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.
Contd..
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Figure 3a Science Cycle
Contd..
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Figure 3b
Regulatory Cycle
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