How AI Can, Cannot Help in Search for Coronavirus Vaccine

The use of artificial intelligence (AI) in the development of coronavirus vaccines, which started barely three months after the virus was first identified in China, has revolutionized the way vaccines are developed.

According to the World Health Organization, in September 34 different vaccines were being tested in humans and an additional 145 vaccine candidates had tests being conducted in the lab or on animals. These are surprising numbers, especially considering that it takes years, sometimes decades, to develop a vaccine. Up until the COVID-19 outbreak, the mumps vaccine was the fastest-produced vaccine with a four-year record of development, from sample collection to its marketed form.

Currently, laboratories are looking into eight different types of coronavirus vaccine. These include experimental ones that involve the use of genetic material, i.e., RNA and DNA vaccines, and traditional ones created by using inactivated viruses as well as others that are based on biological agents or special proteins.

Computational analyses and machine-learning systems have played a crucial role in the quest for a SARS-CoV-2 vaccine. These tools help researchers understand the makeup of a virus and other vital information while also predicting the virus’s components that will give rise to an immune response. These systems also help researchers understand experimental data and track the genetic mutations of a virus over time. This information helps determine the value of the vaccine in the years to come.

Researchers are looking forward to a time when computational techniques, through the use of AI, could help solve vaccine challenges such as discovering an effective HIV vaccine. However, despite its advantages, AI cannot speed up or replace the most important and time-consuming part of vaccine development, i.e., animal and human trials. This requires significant human effort, with thousands of participants, health-care workers and scientists all documenting their experiences with different vaccines in the present time.

Unlike in the past, developing vaccines in today’s day and age is largely an information-intensive venture. The use of AI helps makes this process easier as machine-learning tools can make crucial predictions, based on training data sets that are collected from pathogens. While AI is helpful, it cannot replace the time-consuming processes that go into vaccine development.

Additionally, AI can’t predict the outcome of human trials. However, it can certainly make it easier to understand the data collected from these experiments by more quicky and efficiently analyzing all the parameters and locating patterns. As a growing number of potential vaccines advance to the second and third phases of clinical trials, thousands of participants will be involved, and AI systems will be crucial in helping analyze immunological and clinical data.

AzurRx BioPharma Inc. (NASDAQ: AZRX) is an interesting biopharmaceutical company you should watch. The company focuses on leveraging recombinant proteins to develop therapies for gastrointestinal diseases.

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