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"REVOLUTIONIZING PHARMA WITH AI:
HARNESSING ADVANCED TECHNOLOGIES FOR
INNOVATION"
PANKAJ G. & TANUJA T.
AGENDA
o INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND DATA SCIENCE
o THE AI RESURGENCE
o BUILDING BLOCKS
o APPLICATIONS OF AI
o WHAT IS MACHINE LEARNING?
o QUALITY OF DATA
o FROM VISION TO REALITY
INTRODUCTION TO AI AND
DATA SCIENCE
"Data is the new oil. Learn how to extract value from it."
o AI is the ability of machines to mimic human intelligence, enabling
them to perform tasks that typically require human intelligence,
such as learning, reasoning, and problem-solving.
o Data Science, on the other hand, involves the extraction of
meaningful insights from large and complex datasets. It combines
various disciplines such as statistics, machine learning, and data
visualization to uncover patterns, trends, and relationships within
the data.
o AI and DS are two closely related fields that are often used together.
AI provides intelligence, while DS provides data. The combination of
AI and DS is essential for many of the cutting-edge technologies
that we use today.
THE AI RESURGENCE: WHY
NOW?
"The AI resurgence is not just about technology. It's also about the way we think about the world and our place in it."
o 1997: A major milestone (Deep Blue, a chess-playing computer developed by IBM, defeats Garry Kasparov, the
world chess champion.)
o Impact - Helped to legitimize AI as a field of research
o It has only recently become popular:
o Advances in technology
o Increased accessibility
o Growing awareness
o Computing Power
BUILDING BLOCKS
"AI is not about replacing human intelligence, but amplifying and augmenting it to achieve greater heights."
Data
Algorithms
Computing Power
Machine Learning
Deep Learning
Computer Vision
Natural Language Processing
Neural Network
Robotics
Ethical considerations
APPLICATIONS OF AI
AI is a journey, not a destination
o Virtual Assistants (Amazon Alexa, Apple Siri, Google
Assistant)
o Recommendation Systems (Netflix, Amazon, Spotify)
o Autonomous Vehicles (Tesla, Waymo, Uber)
o Image and Speech Recognition (Facial recognition,
speech-to-text)
o Chatbots (Customer service chatbots)
o Fraud Detection (Financial fraud detection)
o Medical Diagnosis (Cancer detection in medical imaging)
o Language Translation (Google Translate, DeepL)
o Personalized Marketing (Targeted marketing campaigns)
WHAT IS MACHINE
LEARNING?
"AI is not a substitute for human intelligence; it is an amplifier of it. Let's amplify our potential with." - Jane Smith
o An application of Artificial Intelligence that provides systems
the ability to automatically learn and improve from experience
without being explicitly programme.
o Machine learning algorithms can learn from data in a variety
of ways. Some algorithms use statistical methods to find
patterns in data. Other algorithms use neural networks, which
are inspired by the way that the human brain works.
o Now a days this terminology is also applied in ICH guideline
(ICH Q 14)
QUALITY OF DATA
“The quality of your data is the quality of your decisions."
o If you feed a computer program a list of numbers
that are all wrong, the program will not be able to
produce the correct sum or average.
o If you feed a machine learning model a set of blurry
or distorted images, the model will not be able to
learn to identify objects in images.
o If you feed a spam filter a list of emails that are all
spam, the filter will not be able to learn to distinguish
between spam and non-spam emails.
FROM VISION TO REALITY
"Intelligence is the ability to adapt to change. Let's adapt, evolve, and thrive in biopharma with the power of AI."
Readiness Checklist for AI Implementation:
Define the goal (Problem statement)
Data Infrastructure
Data Accessibility and Integration
Database design:
Centralized Data Storage,
Data Integrity and Transparency,
Efficient Audits and Inspections,
Enhanced Decision-Making,
Improved Compliance,
Data Security and Confidentiality
Skilled Workforce
Proof-of-Concept and Pilot Projects
Risk Assessment and Mitigation
THANK YOU
"AI is a mirror reflecting our choices; it can be a tool for progress or a catalyst for
challenges, depending on how we choose to shape its future."
pankajgawate@gmail.com
tanujatanushree301@gmail.com

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Revolutionizing pharma with Artificial Intelligence

  • 1. "REVOLUTIONIZING PHARMA WITH AI: HARNESSING ADVANCED TECHNOLOGIES FOR INNOVATION" PANKAJ G. & TANUJA T.
  • 2. AGENDA o INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND DATA SCIENCE o THE AI RESURGENCE o BUILDING BLOCKS o APPLICATIONS OF AI o WHAT IS MACHINE LEARNING? o QUALITY OF DATA o FROM VISION TO REALITY
  • 3. INTRODUCTION TO AI AND DATA SCIENCE "Data is the new oil. Learn how to extract value from it."
  • 4. o AI is the ability of machines to mimic human intelligence, enabling them to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. o Data Science, on the other hand, involves the extraction of meaningful insights from large and complex datasets. It combines various disciplines such as statistics, machine learning, and data visualization to uncover patterns, trends, and relationships within the data. o AI and DS are two closely related fields that are often used together. AI provides intelligence, while DS provides data. The combination of AI and DS is essential for many of the cutting-edge technologies that we use today.
  • 5. THE AI RESURGENCE: WHY NOW? "The AI resurgence is not just about technology. It's also about the way we think about the world and our place in it."
  • 6. o 1997: A major milestone (Deep Blue, a chess-playing computer developed by IBM, defeats Garry Kasparov, the world chess champion.) o Impact - Helped to legitimize AI as a field of research o It has only recently become popular: o Advances in technology o Increased accessibility o Growing awareness o Computing Power
  • 7. BUILDING BLOCKS "AI is not about replacing human intelligence, but amplifying and augmenting it to achieve greater heights."
  • 8. Data Algorithms Computing Power Machine Learning Deep Learning Computer Vision Natural Language Processing Neural Network Robotics Ethical considerations
  • 9. APPLICATIONS OF AI AI is a journey, not a destination
  • 10. o Virtual Assistants (Amazon Alexa, Apple Siri, Google Assistant) o Recommendation Systems (Netflix, Amazon, Spotify) o Autonomous Vehicles (Tesla, Waymo, Uber) o Image and Speech Recognition (Facial recognition, speech-to-text) o Chatbots (Customer service chatbots) o Fraud Detection (Financial fraud detection) o Medical Diagnosis (Cancer detection in medical imaging) o Language Translation (Google Translate, DeepL) o Personalized Marketing (Targeted marketing campaigns)
  • 11. WHAT IS MACHINE LEARNING? "AI is not a substitute for human intelligence; it is an amplifier of it. Let's amplify our potential with." - Jane Smith
  • 12. o An application of Artificial Intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programme. o Machine learning algorithms can learn from data in a variety of ways. Some algorithms use statistical methods to find patterns in data. Other algorithms use neural networks, which are inspired by the way that the human brain works. o Now a days this terminology is also applied in ICH guideline (ICH Q 14)
  • 13. QUALITY OF DATA “The quality of your data is the quality of your decisions."
  • 14. o If you feed a computer program a list of numbers that are all wrong, the program will not be able to produce the correct sum or average. o If you feed a machine learning model a set of blurry or distorted images, the model will not be able to learn to identify objects in images. o If you feed a spam filter a list of emails that are all spam, the filter will not be able to learn to distinguish between spam and non-spam emails.
  • 15. FROM VISION TO REALITY "Intelligence is the ability to adapt to change. Let's adapt, evolve, and thrive in biopharma with the power of AI."
  • 16. Readiness Checklist for AI Implementation: Define the goal (Problem statement) Data Infrastructure Data Accessibility and Integration Database design: Centralized Data Storage, Data Integrity and Transparency, Efficient Audits and Inspections, Enhanced Decision-Making, Improved Compliance, Data Security and Confidentiality Skilled Workforce Proof-of-Concept and Pilot Projects Risk Assessment and Mitigation
  • 17. THANK YOU "AI is a mirror reflecting our choices; it can be a tool for progress or a catalyst for challenges, depending on how we choose to shape its future." pankajgawate@gmail.com tanujatanushree301@gmail.com