Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • About
Liwaiwai Liwaiwai
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
    • Architecture
    • Design
    • Software
    • Hybrid Cloud
    • Data
  • About
  • Machine Learning

Potential COVID-19 Vaccines Get A Boost From Machine Learning

  • July 29, 2020
  • relay

After what has started to feel like a boundless eternity of wearing masks, bathing in hand sanitizer, and dodging people in the grocery store, many of us have been left thinking: what would a COVID-19 vaccine look like?

Different approaches to the challenge have looked at targeting the so-called “spike proteins” that cover the virus and help it invade human cells.

Whole virus, DNA, and RNA vaccine platforms have been explored using a range of techniques, all in the hopes of creating immunity and changing the unpredictable trajectory of the novel virus.

Recently, a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) took a new approach to getting us closer to a solution: a combinatorial machine learning system that selects peptides (short strings of amino acids) that are predicted to provide high population coverage for a vaccine.

The design system, called “OptiVax,” introduces methods for designing new peptide vaccines, evaluating existing vaccines, and augmenting existing vaccine designs. In this system, peptides are scored through machine learning by their ability to be displayed to elicit an immune response, and are then selected to maximize population coverage of who could benefit from the vaccine.

“We evaluated a common vaccine design based on the spike protein for COVID-19 that is currently in multiple clinical trials,” says Ge Liu and Brandon Carter, CSAIL PhD students and lead authors on a new paper about OptiVax. “Based on our analysis, we developed an augmentation to improve its population coverage by adding peptides. If this works in animal models, the design could move to human clinical trials.”



OptiVax 



In building out their system, the team first adjusted their predictive models and used multiple models to design a vaccine.

Read More  New System Cleans Messy Data Tables Automatically

Taking into consideration the vast differences in our individual DNA, the researchers paid close attention to the genetic makeup of different populations, to maximize the likelihood that people with uncommon genes would still be covered by the vaccine.

Armed with this, they created OptiVax. 

OptiVax works by identifying all possible peptide fragments from a set of viral or tumor proteins that would be good candidates for a vaccine.

Then, peptides are scored for selection on multiple criteria, including their observed mutation rate across nearly 5,000 geographically sampled genomes. Because these peptide fragments stem from the virus, administering them in a vaccine can lead to immunity.

OptiVax then designs a vaccine from these candidates to maximize population coverage in different geographical regions, and from the number of peptides displayed per individual to improve the chances the person will become immune.


The team then used “EvalVax,” a complementary system they designed that predicts coverage for vaccines, to evaluate 29 different vaccine designs by others. They found that many of them were not predicted to provide high population coverage.

“One of the challenges here was assembling good data on how people differ in their genetic makeup, in key genes that control the response to a vaccine or viral infection,” says MIT professor David Gifford. “And then, we had to solve a difficult optimization problem to design a vaccine with good population coverage.”

Future work 


Once animal testing of their vaccine design is done, the team says they can then evaluate if a clinical trial is warranted.  This, they note, will also depend upon the efficacy of the first set of vaccines already being clinically tested.

One of the wild cards of COVID-19 is the inability to predict how different individuals will respond — from minor symptoms to fatal cases.

Read More  How To Handle Imbalanced Data In Machine Learning Classification

With that in mind, the researchers are working with a team at the National Institute of Health (NIH) to see if their methods can be used for risk prediction using data from COVID-19 patients.

The team notes that their framework could be used to design vaccines for a wide range of infectious diseases, and hope to apply it to other viral infections in the future.

Liu, Carter, and Gifford wrote the paper alongside CSAIL postdoc Siddhartha Jain, Trenton Bricken of Duke University, Mathias Viard and Mary Carrington of Basic Science Program, Frederick National Laboratory for Cancer Research and the Ragon Institute of MGH, MIT, and Harvard.

relay

Related Topics
  • Computer Science and Artificial Intelligence Laboratory
  • COVID-19
  • CSAIL
  • EvalVax
  • MIT
  • OptiVax
  • Vaccine
You May Also Like
View Post
  • Artificial Intelligence
  • Data
  • Data Science
  • Machine Learning
  • Technology

Google Data Cloud & AI Summit : In Less Than 12 Hours From Now

  • March 29, 2023
View Post
  • Artificial Intelligence
  • Machine Learning
  • Technology

ChatGPT 4.0 Finally Gets A Joke

  • March 27, 2023
View Post
  • Artificial Intelligence
  • Machine Learning
  • Technology

Mr. Cooper Is Improving The Home-buyer Experience With AI And ML

  • March 24, 2023
View Post
  • Artificial Intelligence
  • Machine Learning
  • Technology

GPT-4 : The Latest Milestone From OpenAI

  • March 24, 2023
View Post
  • Engineering
  • Machine Learning

Peacock: Tackling ML Challenges By Accelerating Skills

  • March 23, 2023
View Post
  • Data
  • Machine Learning
  • Platforms

Coop Reduces Food Waste By Forecasting With Google’s AI And Data Cloud

  • March 23, 2023
View Post
  • Artificial Intelligence
  • Machine Learning
  • Robotics

Gods In The Machine? The Rise Of Artificial Intelligence May Result In New Religions

  • March 23, 2023
View Post
  • Artificial Intelligence
  • Machine Learning

6 ways Google AI Is Helping You Sleep Better

  • March 21, 2023

Leave a Reply

Your email address will not be published. Required fields are marked *

Stay Connected!
LATEST
  • 1
    Bard And ChatGPT — A Head To Head Comparison
    • March 31, 2023
  • 2
    Modernize Your Apps And Accelerate Business Growth With AI
    • March 31, 2023
  • 3
    Why Your Open Source Project Needs A Content Strategy
    • March 31, 2023
  • 4
    From Raw Data To Actionable Insights: The Power Of Data Aggregation
    • March 30, 2023
  • 5
    Effective Strategies To Closing The Data-Value Gap
    • March 30, 2023
  • 6
    Unlocking The Secrets Of ChatGPT: Tips And Tricks For Optimizing Your AI Prompts
    • March 29, 2023
  • 7
    Try Bard And Share Your Feedback
    • March 29, 2023
  • 8
    Google Data Cloud & AI Summit : In Less Than 12 Hours From Now
    • March 29, 2023
  • 9
    Talking Cars: The Role Of Conversational AI In Shaping The Future Of Automobiles
    • March 28, 2023
  • 10
    Document AI Introduces Powerful New Custom Document Classifier To Automate Document Processing
    • March 28, 2023

about
About
Hello World!

We are liwaiwai.com. Created by programmers for programmers.

Our site aims to provide materials, guides, programming how-tos, and resources relating to artificial intelligence, machine learning and the likes.

We would like to hear from you.

If you have any questions, enquiries or would like to sponsor content, kindly reach out to us at:

[email protected]

Live long & prosper!
Most Popular
  • 1
    Introducing GPT-4 in Azure OpenAI Service
    • March 21, 2023
  • 2
    How AI Can Improve Digital Security
    • March 27, 2023
  • 3
    ChatGPT 4.0 Finally Gets A Joke
    • March 27, 2023
  • 4
    Mr. Cooper Is Improving The Home-buyer Experience With AI And ML
    • March 24, 2023
  • 5
    My First Pull Request At Age 14
    • March 24, 2023
  • /
  • Artificial Intelligence
  • Machine Learning
  • Robotics
  • Engineering
  • About

Input your search keywords and press Enter.