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Big Data to Help with COVID-19 Vaccine Development

When the novel coronavirus appeared, no one thought it would scale up this fast. However, today we see healthcare systems worldwide losing the fight against the disease. The numbers are rising quickly, as there are more than seven million cases and 400,000 deaths related to COVID-19 around the globe.  

Scientists have realized that the vaccine might be the only cure against COVID-19. According to the statistics from April 2020, there were more than 200 clinical trials for COVID-19 vaccines or treatment in that month. And even though many people succumbed to the illness, there’s a silver lining — we can use the data to understand the virus and, hopefully, find a cure.   

Data Is Almost Equally Important as a Vaccine

Since the beginning of the pandemic, governments, healthcare sectors, and related organizations have been working on figuring out how the virus behaves. They’ve been analyzing the pathogens and how long they can last on surfaces, what affects them the most, and how they spread. This is where big data comes into the picture. It’s beneficial in analyzing, calculating, and predicting the way COVID-19 will act in the future.

But before the data is used, it needs to be scanned, verified, and properly segmented. Artificial intelligence makes this easy and relatively fast. Even governments join forces with tech companies to work on big data and AI-powered tools, such as surveillance drones and contact tracing mobile apps.

Big Data and AI for Vaccine Development

AI and big data play an essential role in current vaccine development. AI can run complex algorithms by parsing datasets. It can identify components of a vaccine by analyzing and understanding the protein structure of COVID-19. AI helps researchers gather enormous amounts of data at the fastest possible pace. 

Medical researchers can use AI and cloud computing to identify the compounds that prevent the spike protein from binding to the ACE2 receptor on human cells. AI can also monitor the safety of vaccine development. 

Project Tycho as an Example

One example of using big data for vaccine development is Project Tycho. Namely, it provides access to historical records of more than 50 diseases. The project aims to improve the standards, machine readability, and availability of global health data. 

Project Tycho works with national and global health institutes and research facilities to make data more accessible and easier to use for global health improvement. It also works on overcoming the challenges that come with collecting big data, such as limited access. 

Project Tycho uses FAIR Guiding Principles for scientific data management through these three main activities: 

  • Standardizing data about diseases and determinants 
  • Creating machine-interpretable metadata
  • Making data widely available

Conclusion

In these times of uncertainty, hope lies in artificial intelligence and big data. Combined, they can help scientists observe large medical datasets faster than ever before while creating predictions about the movement and behavior of the virus. Insightful datasets are crucial for vaccine development because the analysis of diseases similar to COVID-19 can lead to better outcomes more quickly.

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