<aside> 🧬 Introducing Codon, an artificial intelligence approach to speeding up the vaccine development process by taking viral DNA and determining the optimal protein structure, target, and the type of vaccine.
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One of the world's most important inventions was the vaccine, fighting dangerous infectious diseases. Within the last couple hundred years, we've nearly eliminated smallpox, polio, measles, diphtheria, and rubella in many parts of the world. Despite all the value of vaccines, the process of developing a vaccine is extremely costly, in terms of time, capital, and resources. On average, it takes 20 years, between $521 million and $2.1 billion, and hundreds of researchers and patients before a vaccine can make it to the market. On top of this, only one in ten vaccines actually make it to market.
As we've seen over the last year and a half, the COVID-19 vaccine has been developed in record speed. The biggest contributing factor to the rapid development is the fact that scientists had been studying the SARS-CoV-02 virus for years in advance, and had identified the spike protein sequence as a target from research in 2003 when the strain first emerged. For most diseases, this research isn't readily available, and regulatory concerns greatly decelerate the vaccine development process.
STATUS QUO VACCINE DEVELOPMENT PROCESS:
There's two big factors that contribute to the length of vaccine development:
<aside> 🔑 Decreasing total vaccine development pipeline from up to 20 years → 11 years. 45% reduction in time
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Finding vaccine candidates, producing them in the laboratory, and confirming their efficacy in animal models remains a complicated undertaking. Thus, there is an urgent need for building pipelines or computational frameworks, to integrate diverse algorithms and databases using a single input and provide meaningful results for researchers working on vaccine development.
Developing an algorithm to replace the trial and error experiments can drastically reduce time and maximize results, which is why machine learning systems and computational analyses have played an important role in the vaccine quest. These tools are helping researchers understand the virus and its structure, and predict which of its components will provoke an immune response—a key step in vaccine design. They can help scientists choose the elements of potential vaccines and make sense of experimental data. They also help scientists track the virus's genetic mutations over time, information that will determine any vaccine's value in the years to come