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The well-behaved dog in the frame is named Rosie
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An eight-year-old female mud
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A few years ago Paul rescued her from an animal shelter in Australia
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Since then
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Rosie is Paul's best partner
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Best Mate
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A year ago
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Rosie was given a death sentence by the vet
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Diagnosed with cancer
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Having surgery
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Undergoing chemotherapy
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Also undergoing immunotherapy
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All efforts proved futile
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The vet said
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Rosie has only a few months left
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This Australian dog owner, determined to save Rosie
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He came up with a crazy idea
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Open ChatGPT
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Ask what options there are
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This is Rosie after treatment
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An Australian dog owner with no medical background
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What makes it possible in just a few months
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to complete what would normally take ten years of medical research
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to design an mRNA cancer vaccine for dogs
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What kind of god-tier interaction did he have with AI behind the scenes
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this crazy lab-rat plan
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Could it unlock another option for humans
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a new heavyweight in defeating cancer
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Please sit back, everyone
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This episode we go straight to real people and true stories
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Australian pet owner AI dog-rescue story
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A real case that breaks medical norms
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While we are at it
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When AI becomes a research assistant
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Future humans
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And is there really a chance to avoid the term terminal illness
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Say goodbye
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The story's starting point
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Starting from a few years ago in Sydney, Australia
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About four years ago
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Rosie was four years old then
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He noticed lumps on both of her hind legs
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For a full year
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The vets assured him
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it is just a common rash
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Do not worry
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But those tumors kept growing bigger
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By the time Rosie was five
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A thorough checkup yielded a confirmed diagnosis
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Mast Cell Tumor
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Mast Cell Tumor
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Common in dogs
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But also one of the hardest malignant skin cancers to treat
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Pet owners watching
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You will understand
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Pets are family to us
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And Rosie is Paul's constant best mate
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Best Mate
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Paul wouldn't give up
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So he set off on a long cancer-fighting journey with Rosie
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Conventional cancer treatments
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There are only three options
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Surgery, chemotherapy, immunotherapy
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Paul spent money like water
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Tried everything
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Countless surgeries
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Chemotherapy wore Rosie down
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Even immunotherapy
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But it all failed
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The vet told Paul something no owner wants to hear
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Also the hardest thing to hear
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Sorry
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Its cancer has already spread
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Currently in an incurable stage
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We can at most give it a few more months of life
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Rosie was officially abandoned by conventional medicine
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If an ordinary person reached this point
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They may have to accept
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But in his despair, Paul suddenly hit upon an idea
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Since conventional medicine isn\\
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Why not try it
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It was 2025
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The whole city was talking about how AI could do anything
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Paul stared at the computer
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He thought
If that is the case
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Could the AI guru save Rosie\\
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Then he opened ChatGPT
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At first he was just like us
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to ChatGPT
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to understand the complex veterinary information
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and explore what other treatment options exist
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But
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Nobody expected
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As Paul dug deeper into the leads ChatGPT gave him
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Even started contacting Australia\\
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In his mind
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he began to believe he could personally develop a new antidote for Rosie
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This move
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In the eyes of many doctors at the time
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Unthinkable
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An amateur
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A layperson trying to rely on an online chatbot to save a terminal cancer dog that even top vets say is incurable
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In doctors\\
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Isn\\
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Many would even think
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Is this owner so desperate they\\
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Crazy, right
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But in Paul\\
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He completely ignored what others thought
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In his mind at the time
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Only one simplest, most direct idea
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I don\\
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With this stubborn determination to see it through
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The whole thing suddenly took an unbelievable turn
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A medical miracle that even OpenAI CEO Sam Altman would post praising
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has officially begun
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Someone who has never even looked at a DNA sequence
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a regular pet owner with no bioinformatics training
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Where did the courage come from
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That he could help Rosie
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to develop a new cancer drug
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In fact, the moment Paul opened ChatGPT
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He had unknowingly stepped out of
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the bounds of traditional medicine
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Initially, he just wanted to use AI as a medical dictionary
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to help translate terms
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Paul at that moment on DNA and RNA
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I have no idea what cancer vaccine this is
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Who knows ChatGPT in conversation
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Paved a way out for Paul
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He tells Paul about modern technology
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It can truly be tailored for Rosie
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Her personalized mRNA cancer vaccine
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The premise is actually simple
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Paul only needs to fetch Rosie's tumor gene data
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ChatGPT as an AI can help decode the vaccine formula
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This sounds like a science fiction suggestion
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It even woke a father who had hit a dead end
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Traditional medical logic is like dining at a tea restaurant
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All Meal A, Meal B, and Meal C
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Big pharma develops a chemotherapy drug
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Used by tens of thousands of cancer patients at once
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But cancer cells are the universe's most cunning chameleons
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Every tumor mutation in every dog and person
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Each one is actually unique
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Conventional drugs can't treat Rosie
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Because all of Meal A, Meal B, and Meal C
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None of them suit it
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If that is the case the only way out is
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To make Rosie a globally unique one
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The one of a kind that belongs to her
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a dog's personalized mRNA
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cancer vaccine
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Neighbors, we've endured COVID-19
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Believe in the term mRNA vaccine
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won't be unfamiliar anymore
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But we are here
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Quick recap of what it actually is
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How it differs from traditional vaccines
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It is not a live attenuated virus
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Injected into the body
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In essence
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It is the feature data of the top fugitive
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Sent into your body
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Once the vaccine enters the body
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Your immune forces will act with precision
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Like a wanted notice
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Immediately follow
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The features on the list
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All forces mobilized
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Closing in on you completely
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The enemy you want to wipe out: COVID-19
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Either way
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Cancer cells as well
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But for this warrant to exist
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Clever you should have thought of
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Before the warrant is issued
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First you need to know what the top fugitive looks like
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What it actually looks like
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So
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Paul without a second thought
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follows ChatGPT's instructions
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Immediately contact Australia's top research institutions
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Genomics Institute at the University of New South Wales
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Spending a few thousand AUD
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The request is simple
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Rose's tumor tissue
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Then perform whole genome sequencing
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Genome Sequencing
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Read every DNA code inside
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The associate professor Martin Smith who led the center at that time
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When I received Paul's email
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At first, my mind was full of questions
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The professor wants
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Hey
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You are a layperson
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Do you have any idea how huge the genome data is
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Once you have it
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how to deal with it
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But Paul was sure then and told the professor
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Don't worry
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data analysis work
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I can handle it
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The data the research center handed to Paul
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Not a miracle drug
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But instead several huge digital files
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When Paul opened these files
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They are strings springing out of ATCG
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An endless sea of characters
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How many letters are here in total
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The answer is about 150 billion
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Just how big is 150 billion
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If we print it as a book
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It could fill the whole university library
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Paul faces
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these completely irregular ones
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a scrambled alphabet salad
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to find the one letter copied wrong
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causing Rosie to form a tumor
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People like us reach this point
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Facing this mountain of data
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Willpower may be almost gone
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But the turning point is
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Paul is not just an ordinary IT guy
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His real identity
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is actually an IT guy who specializes in machine learning
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What he is best at
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Of course not a surgeon
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He deals with data every day
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So in his eyes
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Big data problems are well within his reach
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Since the human eye can't read all 150 billion letters
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Then hand it to the fastest AI
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Paul enters round-the-clock seclusion
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Every day he faces a glowing screen
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Treating ChatGPT as his superbrain
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Give this data, like a stack of scriptures, to AI for sorting and analysis
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AI suddenly becomes Paul's best medical assistant
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Help him precisely search through the massive data
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Rosy cancer cell neoantigens
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Neoantigens
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What are neoantigens
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Normal cells are ordinary, law-abiding citizens
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And cancer cells are fugitives hidden among ordinary citizens
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This so-called neoantigen
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is actually the fugitive's unique feature
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If AI can pinpoint it precisely within 150 billion letters
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Find the fugitive features
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The vaccine can become a precise arrest warrant
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Teach your immune system to use these features to catch them
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That is how it works
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It would normally take a long time to organize
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Through day and night interactions between Paul and ChatGPT
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The data mountain starts to be dismantled layer by layer
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That 150-billion-letter celestial manuscript begins filtering, slimming down
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Finally zeroes in on a specific gene mutation
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This gene is called the CKIT gene
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That moment
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Paul knew the first battle had been won
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He finally, in the vast sea of data
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He precisely grabbed the tail of this formidable foe, the cancer cell
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But the letters of the gene mutation
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Only the fugitive's textual description
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This is like what is written on the wanted notice
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A mole on the suspect's face
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But the problem is
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Where is the mole located?
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Left side, right side
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Or is it on the nose?
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If there is no 3D location
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Rosie's immune system can't make sense of it
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nor can they act on it
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So
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The tricky problem Paul must solve next
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is how to turn this string of text into a concise form
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a string of text becomes a precise 3D location-based wanted notice
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At this point, Google's turn
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another AI marvel that turns data into 3D structures
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AlphaFold takes the stage
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After locking onto the CKIT gene
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Paul, though, has the fugitive's flat data
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But he knows a string of flat gene letters alone
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cannot be directly turned into an injectable drug
284
00:10:46,840 --> 00:10:51,079
Because the next hurdle is predicting the 3D structure of proteins
285
00:10:51,399 --> 00:10:53,199
In the microscopic world
286
00:10:53,199 --> 00:10:54,560
Structure equals function
287
00:10:54,600 --> 00:10:56,359
DNA is only a flat blueprint
288
00:10:56,439 --> 00:10:59,119
The real culprit is the 3D protein
289
00:10:59,680 --> 00:11:01,760
You have to design a bespoke vaccine
290
00:11:01,800 --> 00:11:04,359
With the features of this top fugitive
291
00:11:04,680 --> 00:11:06,920
which is the cancer cell's new antigen
292
00:11:07,119 --> 00:11:09,159
which are a bunch of mutated proteins
293
00:11:09,159 --> 00:11:12,279
Then you must know in 3D space
294
00:11:12,359 --> 00:11:14,680
what these mutated proteins actually look like
295
00:11:14,760 --> 00:11:16,039
In other words
296
00:11:16,039 --> 00:11:19,359
you must precisely pinpoint the spot the cancer cell exposes
297
00:11:20,239 --> 00:11:20,920
where exactly it sits
298
00:11:21,760 --> 00:11:26,520
Pharma companies used to spend years and money researching a protein structure
299
00:11:26,680 --> 00:11:28,079
But Rosie could not wait
300
00:11:28,359 --> 00:11:31,479
So Paul deploys Google's AI marvel AlphaFold
301
00:11:32,880 --> 00:11:34,920
Many people may not have heard of AlphaFold
302
00:11:35,359 --> 00:11:36,239
To put it simply
303
00:11:36,239 --> 00:11:39,279
It is the world's most powerful 3D protein modeling tool
304
00:11:39,800 --> 00:11:41,319
Things that used to take years
305
00:11:41,319 --> 00:11:42,560
Why it can be so fast now
306
00:11:43,199 --> 00:11:44,760
Because Google made a decision
307
00:11:44,760 --> 00:11:48,760
They made AlphaFold freely available to the public
308
00:11:49,000 --> 00:11:52,600
Today, almost all top biology labs worldwide
309
00:11:52,760 --> 00:11:55,079
use this AI tool every day
310
00:11:55,479 --> 00:11:57,840
with this protein 3D modeling tool
311
00:11:57,840 --> 00:12:00,079
The whole process is divided into three parts
312
00:12:00,640 --> 00:12:01,399
Step one
313
00:12:01,399 --> 00:12:05,520
Paul must first navigate the 150-billion-letter data mountain
314
00:12:05,760 --> 00:12:10,840
Precisely filter the seven strongest, easiest-to-recognize new antigens
315
00:12:10,840 --> 00:12:12,760
In the wording of a wanted notice
316
00:12:12,760 --> 00:12:14,640
He successfully locked onto the suspect
317
00:12:15,680 --> 00:12:16,319
Step two
318
00:12:16,319 --> 00:12:20,000
He inputs the 2D data of these seven features into AlphaFold
319
00:12:20,279 --> 00:12:21,560
AI runs a computation
320
00:12:21,560 --> 00:12:25,680
and produced precise 3D models for all seven features
321
00:12:26,279 --> 00:12:26,960
Step three
322
00:12:26,960 --> 00:12:30,760
Paul then has ChatGPT perform cross checks
323
00:12:30,920 --> 00:12:33,720
Cross-check each of the seven 3D models individually
324
00:12:34,079 --> 00:12:35,880
Finally confirm these seven markers
325
00:12:35,880 --> 00:12:39,880
the seven core, inescapable features of this cancer cell
326
00:12:40,600 --> 00:12:42,840
But reality is not that glamorous
327
00:12:42,920 --> 00:12:45,920
Do not think Paul is hiding at home fighting alone
328
00:12:46,439 --> 00:12:49,399
In fact the whole process is a tight cross-disciplinary collaboration
329
00:12:49,760 --> 00:12:52,199
During the months designing the vaccine
330
00:12:52,199 --> 00:12:56,199
Paul has been working with Martin Smith, UNSW gene sequencing expert
331
00:12:56,199 --> 00:12:56,699
Paul has been working with Martin Smith, UNSW gene sequencing expert
332
00:12:56,840 --> 00:13:00,399
and Professor Paul Thorderson, director of the RNA Institute
333
00:13:00,399 --> 00:13:01,840
Maintaining close communication and collaboration
334
00:13:02,399 --> 00:13:06,159
Top scientists, an AI brain, and a father who will not give up
335
00:13:06,680 --> 00:13:10,039
This tailor-made cancer cell that outsiders once fantasized about
336
00:13:11,399 --> 00:13:13,439
Step by step, it becomes reality
337
00:13:13,960 --> 00:13:15,399
After months of effort
338
00:13:15,439 --> 00:13:17,119
Vaccine design finally complete
339
00:13:17,399 --> 00:13:18,640
As soon as the design is finished
340
00:13:18,640 --> 00:13:21,720
he immediately goes to the director of the RNA Institute
341
00:13:21,800 --> 00:13:22,479
Professor Thordarson
342
00:13:23,039 --> 00:13:25,359
Professor Thordarson was initially somewhat skeptical
343
00:13:25,720 --> 00:13:27,840
Because moving from development to production takes time
344
00:13:28,279 --> 00:13:30,239
He worries Rosie will not be able to hold out that long
345
00:13:30,640 --> 00:13:33,439
But after his team
346
00:13:33,439 --> 00:13:36,119
the professor felt this non-scientist-made design
347
00:13:36,279 --> 00:13:37,640
was quite stunning
348
00:13:38,000 --> 00:13:40,640
on top of that, his institute had never worked on a cancer vaccine
349
00:13:41,119 --> 00:13:42,319
so they all clicked right away
350
00:13:43,079 --> 00:13:46,279
but just as Paul thought he had beaten all defenses
351
00:13:46,319 --> 00:13:49,399
as he prepared a decisive shot to save the day
352
00:13:49,520 --> 00:13:51,479
the referee suddenly rushed out to blow the whistle
353
00:13:51,760 --> 00:13:53,479
and intercepted him forcefully
354
00:13:54,039 --> 00:13:55,479
This referee is not from science
355
00:13:55,880 --> 00:13:56,920
nor from AI
356
00:13:57,239 --> 00:13:59,640
but from the oldest invention of our human society
357
00:13:59,640 --> 00:14:01,479
the trickiest invention
358
00:14:01,600 --> 00:14:02,800
bureaucratic admin hell
359
00:14:03,279 --> 00:14:03,960
in Australia
360
00:14:04,039 --> 00:14:06,399
you write a software patch to upgrade the phone
361
00:14:06,399 --> 00:14:07,159
nothing at all
362
00:14:07,359 --> 00:14:12,640
but if you want to inject a string of newly designed chemical molecules into a living dog
363
00:14:13,479 --> 00:14:15,319
the laws and paperwork involved
364
00:14:15,399 --> 00:14:16,319
thicker than a dictionary
365
00:14:16,680 --> 00:14:21,560
Paul must apply to the university and government ethics boards for animal ethics approval
366
00:14:22,000 --> 00:14:26,520
the whole plan becomes a two-front battle against time
367
00:14:26,560 --> 00:14:29,319
on one side, top labs are fully ramped up
368
00:14:29,319 --> 00:14:33,439
This is the precise manufacturing process that turns digital formulas into real weapons
369
00:14:33,479 --> 00:14:34,640
The scientists spent two months
370
00:14:35,119 --> 00:14:38,119
On the other hand, Paul bears the bureaucratic paperwork alone
371
00:14:38,600 --> 00:14:42,239
During these months, this IT guy would come home after work every day
372
00:14:42,239 --> 00:14:43,920
just sitting in front of the computer
373
00:14:43,920 --> 00:14:46,399
filling those endless government filings
374
00:14:46,680 --> 00:14:47,800
He even laughs at himself
375
00:14:47,920 --> 00:14:49,800
to deal with this stack of ethics approvals
376
00:14:49,800 --> 00:14:51,319
He spends several hours a day filling them out
377
00:14:51,359 --> 00:14:53,159
It dragged on for a full three months
378
00:14:53,560 --> 00:14:55,920
The workload was more than the vaccine design itself
379
00:14:56,319 --> 00:14:56,920
In the end
380
00:14:56,920 --> 00:14:58,159
the approvals and the vaccine
381
00:14:59,279 --> 00:15:01,720
But fate played a joke on him again
382
00:15:02,000 --> 00:15:04,079
as Paul held the syringe and medicine
383
00:15:04,079 --> 00:15:06,279
as he was in high spirits preparing to save Rosie
384
00:15:07,000 --> 00:15:10,560
The research center told him, Sorry Sir
385
00:15:10,560 --> 00:15:12,039
We are the research center
386
00:15:12,039 --> 00:15:13,720
Only responsible for R&D and manufacturing
387
00:15:13,720 --> 00:15:15,239
Not authorized to vaccinate your dog
388
00:15:16,079 --> 00:15:16,439
Next
389
00:15:16,439 --> 00:15:19,439
Paul rushed to the regular vet Rosie usually goes to
390
00:15:19,720 --> 00:15:20,640
The vet took one look
391
00:15:20,640 --> 00:15:22,159
and immediately shook his head in alarm
392
00:15:22,159 --> 00:15:25,479
saying this is an untested experimental drug
393
00:15:25,479 --> 00:15:27,159
Who would take responsibility
394
00:15:28,159 --> 00:15:29,880
Months of hard work
395
00:15:29,880 --> 00:15:31,359
The high-tech solution worked
396
00:15:31,359 --> 00:15:32,880
Survived the bureaucratic paperwork
397
00:15:32,920 --> 00:15:33,600
Finally
398
00:15:33,600 --> 00:15:37,159
it was stuck at this spot where no one dares to inject
399
00:15:37,159 --> 00:15:38,039
No way
400
00:15:38,840 --> 00:15:39,399
At this point
401
00:15:39,399 --> 00:15:42,600
Rosie's leg tumor had started to worsen
402
00:15:42,600 --> 00:15:43,720
and it even bleeds
403
00:15:43,720 --> 00:15:45,600
life was clearly counting down to the end
404
00:15:46,039 --> 00:15:52,319
these breakthroughs created by IT guys, AI tools, and a top-tier science team across disciplines
405
00:15:52,920 --> 00:15:56,479
Finally, can they be injected into Rosie's body
406
00:16:01,279 --> 00:16:03,000
Watching anxiously as the vaccine is prepared
407
00:16:03,000 --> 00:16:04,399
But Rosie can't get the shot
408
00:16:04,720 --> 00:16:05,239
Fortunately
409
00:16:05,239 --> 00:16:08,319
Paul via his contact in the U.S.
410
00:16:08,319 --> 00:16:09,760
found The University of Queensland
411
00:16:09,760 --> 00:16:13,479
Professor Rachel Alvina, Vice Dean of the Veterinary Science Institute
412
00:16:13,960 --> 00:16:16,680
Professor Rachel is an expert in animal immunotherapy
413
00:16:16,720 --> 00:16:19,680
She said if Paul can bring Rosie to Brisbane
414
00:16:19,680 --> 00:16:20,800
she can give Rosie the shot
415
00:16:21,159 --> 00:16:21,640
That moment
416
00:16:21,640 --> 00:16:23,720
Rosie's leg tumor had grown very large
417
00:16:23,720 --> 00:16:25,319
Bleeding
418
00:16:25,319 --> 00:16:26,880
The situation was dire
419
00:16:27,159 --> 00:16:28,760
So Paul didn't hesitate
420
00:16:28,760 --> 00:16:32,039
and drove with Rosie all the way from Sydney to Brisbane
421
00:16:32,359 --> 00:16:33,840
And at this moment
422
00:16:33,840 --> 00:16:37,840
Paul also pulled off a bold two-pronged strategy
423
00:16:38,119 --> 00:16:41,000
Apart from his homemade mRNA vaccine
424
00:16:41,159 --> 00:16:43,520
He, through Professor Rachel,
425
00:16:43,520 --> 00:16:48,239
another Nobel Prize–winning immunotherapy drug
426
00:16:48,239 --> 00:16:49,279
immune checkpoint inhibitor
427
00:16:49,279 --> 00:16:51,760
immune checkpoint inhibitor
428
00:16:52,079 --> 00:16:52,800
Ladies and gentlemen
429
00:16:53,319 --> 00:16:55,720
This tactical logic is actually very clever
430
00:16:56,079 --> 00:16:56,920
To understand
431
00:16:56,920 --> 00:16:59,439
cancer cells can run rampant inside our bodies
432
00:16:59,640 --> 00:17:01,880
There are actually two major rogue defenses behind it
433
00:17:02,359 --> 00:17:04,279
The first line of defense is invisibility
434
00:17:04,840 --> 00:17:08,199
Because cancer cells are also our own cells
435
00:17:08,359 --> 00:17:10,880
it can often fool our own immune army
436
00:17:10,880 --> 00:17:12,239
when it is one of us
437
00:17:12,239 --> 00:17:13,039
go straight through
438
00:17:13,520 --> 00:17:15,199
The second line of defense is hypnosis
439
00:17:15,359 --> 00:17:18,119
Even if immune cells approach it they plan to destroy it
440
00:17:18,119 --> 00:17:19,359
they plan to destroy it
441
00:17:20,079 --> 00:17:22,359
cancer cells release hypnotic codes
442
00:17:22,479 --> 00:17:25,399
making cancer cells suddenly unable to see it
443
00:17:25,479 --> 00:17:28,399
That is why conventional treatments often fail
444
00:17:28,800 --> 00:17:30,640
But this time Paul combination therapy
445
00:17:30,640 --> 00:17:34,039
to wipe out both lines of defense in one go
446
00:17:34,199 --> 00:17:36,439
they use immune checkpoint inhibitors
447
00:17:36,680 --> 00:17:38,560
to disrupt the second line of defense
448
00:17:38,560 --> 00:17:39,359
breaks the hypnosis
449
00:17:39,800 --> 00:17:42,359
then follows up with his own AI vaccine
450
00:17:42,479 --> 00:17:44,399
break through the first line of defense
451
00:17:44,640 --> 00:17:48,279
directly insert a warrant listing the 3D features to identify it
452
00:17:50,640 --> 00:17:52,399
one to awaken the army
453
00:17:52,399 --> 00:17:54,520
one to lead the army to find targets
454
00:17:54,960 --> 00:17:56,960
at the University of Queensland Hospital
455
00:17:56,960 --> 00:17:59,960
Professor Rachel Alvina will deploy this perfect combination
456
00:17:59,960 --> 00:18:03,479
injected at multiple sites around Rosie tumor tissue
457
00:18:04,079 --> 00:18:04,880
At this point
458
00:18:04,880 --> 00:18:06,279
Some viewers may recall
459
00:18:06,600 --> 00:18:07,720
Hey
Bonnie
460
00:18:07,720 --> 00:18:10,520
In Chapter 1 you said Paul was already with Rosie
461
00:18:10,520 --> 00:18:12,000
Had immunotherapy already?
462
00:18:12,319 --> 00:18:14,000
but there was no result
463
00:18:14,000 --> 00:18:14,479
That is right
464
00:18:14,479 --> 00:18:17,000
The literature does not detail the failure specifics
465
00:18:17,279 --> 00:18:19,439
But based on current medical logic
466
00:18:19,520 --> 00:18:22,159
We can reasonably infer its cause
467
00:18:22,159 --> 00:18:25,039
The standard immunotherapy Paul gave Rosie at the time
468
00:18:25,159 --> 00:18:28,960
likely it was simply using this checkpoint inhibitor
469
00:18:29,279 --> 00:18:32,720
These inhibitors did wake up the immune army
470
00:18:32,880 --> 00:18:35,359
But the problem is there was no warrant on hand
471
00:18:35,520 --> 00:18:37,119
Not knowing what the enemy looks like
472
00:18:37,119 --> 00:18:38,119
rush out
473
00:18:38,119 --> 00:18:38,880
a sea of people
474
00:18:38,880 --> 00:18:42,680
the immune army still cannot tell which cancer cells to target
475
00:18:42,680 --> 00:18:44,720
ultimately they returned empty handed
476
00:18:45,239 --> 00:18:45,600
Okay
477
00:18:45,600 --> 00:18:46,840
Back to Rosie
478
00:18:47,199 --> 00:18:48,239
The first few days after the shot
479
00:18:48,800 --> 00:18:50,359
Rosie more tired than before
480
00:18:50,920 --> 00:18:52,479
One day after returning to Sydney
481
00:18:52,479 --> 00:18:54,560
Paul suddenly finds a lump on Rosie leg
482
00:18:54,560 --> 00:18:56,479
those large tumors suddenly began
483
00:18:56,479 --> 00:18:57,039
to swell violently
484
00:18:57,439 --> 00:18:58,319
This situation
485
00:18:58,319 --> 00:19:00,279
for an ordinary person it might make the legs go weak
486
00:19:00,600 --> 00:19:02,359
But his rational thinking
487
00:19:02,399 --> 00:19:03,840
he feels hopeful
488
00:19:03,880 --> 00:19:06,000
He calmly analyzes that this swelling
489
00:19:06,000 --> 00:19:08,279
may be the immune system got the wake up call
490
00:19:08,640 --> 00:19:10,600
begins a frantic siege on cancer cells
491
00:19:10,600 --> 00:19:12,079
causing local inflammation
492
00:19:12,239 --> 00:19:14,359
This is actually a very good signal
493
00:19:14,359 --> 00:19:14,680
This is actually a very good signal
494
00:19:14,680 --> 00:19:15,319
Sure enough
495
00:19:15,319 --> 00:19:16,199
Not surprisingly
496
00:19:16,359 --> 00:19:17,479
A few days later
497
00:19:17,479 --> 00:19:17,979
A miracle happens
498
00:19:18,239 --> 00:19:19,760
Those swollen tumors
499
00:19:19,840 --> 00:19:21,840
suddenly, like burst balloons
500
00:19:22,479 --> 00:19:23,039
rapidly shrink
501
00:19:23,479 --> 00:19:25,399
Paul describes himself in the interview
502
00:19:25,399 --> 00:19:26,039
he says
503
00:19:26,039 --> 00:19:27,640
In those few short days
504
00:19:27,640 --> 00:19:29,439
I really felt like I was seeing those tumors with my own eyes
505
00:19:29,479 --> 00:19:30,520
as if melting away
506
00:19:30,520 --> 00:19:31,600
watching her feet
507
00:19:31,760 --> 00:19:33,600
I actually started seeing her ankles
508
00:19:33,600 --> 00:19:34,159
I actually started seeing her ankles
509
00:19:34,159 --> 00:19:34,880
Holy crap
510
00:19:34,880 --> 00:19:35,720
it's working
511
00:19:35,880 --> 00:19:37,600
Paul said he was so excited at the time that he shouted
512
00:19:37,960 --> 00:19:38,680
went through so many rounds of chemotherapy
513
00:19:38,680 --> 00:19:40,760
the late-stage malignant tumor stayed stubbornly unchanged despite so many rounds of chemotherapy and surgeries
514
00:19:42,680 --> 00:19:46,880
Under a two-pronged attack of AI vaccines and checkpoint inhibitors
515
00:19:46,880 --> 00:19:49,560
It could be seen with the naked eye as it rapidly shrank away
516
00:19:50,000 --> 00:19:51,439
Even more amazing
517
00:19:51,439 --> 00:19:53,680
Rosie's spirits recovered
518
00:19:53,680 --> 00:19:55,640
Back to the happy dog she used to be
519
00:20:01,319 --> 00:20:03,680
Of course Paul breathed a sigh of relief seeing Rosie
520
00:20:03,680 --> 00:20:06,640
But medicine is always rigorous
521
00:20:06,640 --> 00:20:10,800
Professor Paul Thordarson and Paul later spoke to the public with great candor
522
00:20:10,800 --> 00:20:14,359
While there was improvement, it's not a perfect cure
523
00:20:14,840 --> 00:20:18,520
In medicine this is called a partial response
524
00:20:18,600 --> 00:20:21,800
Most of Rosie's tumors have melted away
525
00:20:21,800 --> 00:20:25,600
But some cancer cells remained resistant to treatment
526
00:20:25,600 --> 00:20:26,680
Even to this day
527
00:20:26,680 --> 00:20:29,039
Paul still uses the data at his disposal
528
00:20:29,039 --> 00:20:32,000
to develop the next generation of booster shots for Rosie
529
00:20:32,119 --> 00:20:32,960
booster shots
530
00:20:33,039 --> 00:20:36,039
to tackle those residual drug-resistant cancer cells
531
00:20:36,600 --> 00:20:39,279
Cancer is a long war
532
00:20:39,279 --> 00:20:40,600
You may not win in a single shot
533
00:20:41,279 --> 00:20:42,960
But at least it shows that
534
00:20:42,960 --> 00:20:46,159
Paul has found a way forward we might not have known before
535
00:20:46,680 --> 00:20:50,840
The battlefield where Silicon Valley and biotech giants are now pouring money is right here
536
00:20:51,159 --> 00:20:53,800
When bioscience becomes information science
537
00:20:53,800 --> 00:20:56,439
Unknown mysteries that would have taken years to solve
538
00:20:56,439 --> 00:20:58,760
compressed by AI into days of data sorting
539
00:20:59,119 --> 00:21:02,760
Many people now worry AI will take away their jobs
540
00:21:02,760 --> 00:21:05,000
But when we look at Paul
541
00:21:05,000 --> 00:21:10,159
Is technology creating new possibilities between doctors and patients?
542
00:21:10,960 --> 00:21:11,520
The future
543
00:21:11,520 --> 00:21:14,800
Will what Paul did become a new kind of job?
544
00:21:15,680 --> 00:21:18,760
The eventual elimination of humans won't come from AI
545
00:21:18,760 --> 00:21:20,199
Weaving miracles
546
00:21:20,199 --> 00:21:21,680
nor is it cold, impersonal technology
547
00:21:21,960 --> 00:21:26,199
But it's those who know how to use AI to protect the ones they love
548
00:21:26,760 --> 00:21:28,680
This episode ends here
549
00:21:28,680 --> 00:21:29,640
Everyone
550
00:21:29,640 --> 00:21:34,720
What new opportunities do you think AI will create in medicine or other fields in the future?
551
00:21:35,199 --> 00:21:37,640
If you like this content remember to support YOLO in your own way
552
00:21:39,520 --> 00:21:40,359
See you next time, bye
41289
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