Artificial intelligence can help improve pharmacovigilance in three key ways: 1) AI can automate repetitive manual tasks like data entry of adverse event reports to improve efficiency. 2) Machine learning algorithms can be trained on large databases of adverse drug reaction reports to help identify new safety signals. 3) AI tools show promise in extracting clinically relevant information from individual case safety reports without human review, reducing the time spent on case processing. However, challenges remain around data quality, costs, and ensuring AI augmentation rather than replacement of human experts.

1. Artificial Intelligence in
Pharmacovigilance
Dr Lokendra Sharma
Principal Nodal Officer New Govt Medical College Alwar
HOD,Department of Pharmacology
RUHS-CMS,Jaipur

2. What Is Pharmacovigilance?
• Pharmacovigilance Is The Study Of Two Primary
Outcomes In The Pharmaceutical Industry: Safety And
Efficacy.
• Essentially, it asks does a drug work and is it safe?

3. Aims Of AI in Pharmacovigilance

5. AGENDA
• Pharmacovigilance Automation Scope
• Prioritization Approach
• Machine Learning strategies in Production
• Implementing Intelligent Automation (ex.
Attribute Identification)
• Training data for Machine Learning(ML)
Algorithms
• Current State and Future Development

7. AI Definition Contd…
• Computer science defines AI research as the theory
and development of computer systems able to
perform tasks normally requiring human
intelligence,
• Eg visual perception, speech recognition, decision-
making, and translation between languages.
• AI also involves the study of "intelligent agents", that
is, any device that perceives its environment and
takes actions that maximize its chance of
successfully achieving its goals.
• AI is said to be the pillar of the next Industrial
Revolution.

9. Scope for AI is in Every step of PV

11. ADR reports are numerically increasing day by day as a result of a number of
factors including : increased number of products,more robust ADR reporting
systems etc.A Adverse event reporting System
This presents a major challenge of processing this ever increasing data.And this is where
AI can help tremendously.of adverse event reports)

12. Automation promises to be a game-changer in pharmacovigilance, decreasing the
cost of case processing and improving data quality.
Repetitive and routine manual tasks such as adverse event case intake and data
entry can be automated and tackled by AI in a sophisticated and seamless way.

17. Training Data
Requirements
• Good training quality
reduces the number of
training datasets needed
• Reduces the number of
model interations needed
• Pharmacovigilance: data
cleaning and annotation
is particularly needed
when:
• Limited in quantity
• Rich in non-essential data
elements
• Such as
• Signal detection
and evaluation
• PV agreements
• Aggregate reports
• Literature reports

18. What about
ICSR
Training
Data?
• There are categories in AI in
ICSR (Individual Case Safety
Report)processing:
• Adverse event database:
training data of varying
quality but in abundance
• ICSR data can be used
directly for ML algorithm
training
• There are two types of ICSR
data: structured and
unstructured, and insertion
of this data is done to
facilitate AI in decision
making.

19. VigiBase
• A PV database that records
the information in a
structured and ordered
form to allow easy analysis
of recorded data.
• This system is related to
medical and drug
classification
• Over 20 million reports of
adverse drug effect were
recorded by VigiBase (as of
May 2019
VigiBase Training Session at
RUHS-CMS

20. VigiAccess
•It is a publicly
accessible web
application to
browse and access
the data of adverse
drug effects easily
through VigiBase.
VigiAccess Training
Session at RUHS-CMS

21. VigiLyze •It is an online
resource that
provides a clear and
quick review of
VigiBase which can
be explored online
for further analysis
VigiLyze Training Session at
RUHS-CMS

22. VigiFlow
• It is a web-based ICSR
management system for
international drug
monitoring by:
• Collection
• Processing
• Sharing of data to
facilitate effective data
analysis, which is
supported by WHO Drug
and MedDRA
VigiFlow Training Session at
RUHS-CMS

23. VigiGrade
• To measure the
completeness score of
clinically relevant
information in ordered
format on the individual
case report.
• This is mainly used as a part
of communication with
countries on data quality
VigiGrade Training Session at
RUHS-CMS

24. VigiMatch •It is an algorithm to
detect the similar
individual case report
by the use of
probabilistic pattern
matching
VigiMatch Training Session at
RUHS-CMS

25. VigiRank • It is a novel method to
detect the statistical signals
which is not just for
disproportionate reporting
patterns but also for the
completeness, recency, and
geographic spread of
individual case reporting
VigiRank Training Session at
RUHS-CMS

26. Benefits of
Artificial
Intelligence in
Pharmacovigilanc
e
• The most important
benefits of AI are reduced
cycle times.
• Due to this method, the
processing is spontaneous
• Improve the quality and
accuracy of the
information
• AI can handle or manage
diverse types of incoming
data formats

27. Benefits of
Artificial
Intelligence in
Pharmacovigilanc
e
•It can be used for the
identification of ADRs
• AI is useful to reduce
the burden and time of
case processing
• AI tools extract the
information from the
adverse drug event
form and evaluate the
case validity without
the workforce.

28. Potential
challenges
• Costs issues
• Ethical issues
• Reluctance among medical
practitioners to adopt AI
• Fear of replacing humans
• Data Privacy and security
• Mobile health applications and
devices that use AI
• Lack of interoperability
between AI solutions
• Data exchange

29. Potential
challenges
• Need for continuous training by
data from clinical studies
• Incentives for sharing data on the
system for further development and
improvement of the system.
Nevertheless,
• All the parties in the healthcare
system, the physicians, the
pharmaceutical companies and the
patients, have greater incentives to
compile and exchange information
• State and federal regulations
• Rapid process of software updates
commonly used to improve existing
products and services

30. Future
Indian
Scenario
• Collaboration between medical
and technical institutions
• Government funding – more
intelligent and result oriented
• Current status of medical
records
• Laboratories and clinics need to
collaborate to accelerate the
implementation of electronic
health records
• Data need to be captured in real-
time, and institutions should
promote their transformation
into intelligible processes

31. • AI is designed to be self
evolving and someday ,in
not too distant future
• AI will match and then
exceed Human intelligence
and may even integrate
with human biology
and create what some
scientists refer to as Trans-
Humans.
• Possibilities are immense
and what we are
witnessing right now is just
the tip of the iceberg.

32. Paper less
activity for
HCQ
Pharmacovigi
lance with AI
integration to
manage ADR
data

33. GMHAT:Training in
Medical Education;Feb 2019
GMHAT is a computer
assisted clinical
interview to be used in
routine clinical
practice to detect and
manage mental
disorders.With AI
integration it can
better predict mental
health status.

34. Research Projects
[15]& GMHAT
1. Mental health assessment by medical
students of Batch 2016
using GMHAT.
2. Mental health assessment by medical
undergraduate of Batch 2017
students using GMHAT.
3.Assessment of Mental health of
participants by MBBS Batch 2018 by
using
GMHAT.
4. To assess and compare the effect of
traditional teaching with Integrated
teaching in MBBS students with the
help of GMHAT this also
included in teaching timetable.
5. Use GMHAT By Postgraduate students
in there training & thesis work on Cancer,
HIV, TB, Diabetes and Osteoarthritis
patients.

35. Mental Health
Disorders Project
with Jointly SMS
Medical College
Jaipur and
University of
Manchester (UK)

36. Role of
Telegram/
Whats app
in GMHAT
Training
i. Cloud-based
instant messaging
ii. Available for
Android, iOS,
Windows Phone,
Windows, macOS
and GNU/Linux

37. Covid and Psychosocial Issues related Awareness
Initiative with potential role of AI in identifying early
signs of psychological stress; May 23,2020
Online Activities in Present situation by different college for Psychosocial support
https://www.youtube.com/channel/UCzW3nd0RQZ6sU-bzKb2eEdQ?view_as=subscriber

38. May 2, 2022
Unveiling of the RUHS CMS
Pharmacovigilance poster with Honorable
VC Sir Dr Sudhir Bhandari. (VC, RUHS &
Principal SMS Medical College).
May 10, 2022
Unveiling of the RUHS CMS
Pharmacovigilance poster for Lupus
awareness on Lupus Day.
Our On Campus Activities and events to enhance Medical Education

39. May 6,2022
CPR Training for MBBS students at RUHS-CMS,Jaipur(How
CPR Training saves lives) and Introduction to world’s First AI-
Controlled CPR System developed by University of Minnesota
and Georgia Institute of Technology

40. •
MAY 1, 2022
Awareness for vaccination and
Management of 4th Covid wave in
collaboration with Dr Tarun Lal
along with discussion about how AI
has been used by companies to
determine vaccine targets

42. AWARENESS FOR MATERIOVIGILANCE
PROGRAM OF INDIA BY AMC SMS ,JAIPUR.
FEB 23,2022

43. Thank You
Organ Donation Drive in SMSMC Jaipur
Covid War Room Team