How AI is Accelerating Drug Discovery

How AI is Accelerating Drug Discovery

In the future, we may see explicit and innovative use cases of AI by guiding pharmaceutical organizations in the drug discovery process.

Fremont, CA: Artificial Intelligence (AI) has transformed the healthcare sector in recent years. It has played an influential role in enhancing diagnostics equipment's capabilities, designing bots that can interact with patients recovering from surgery or mental illness, or distributing medical samples and drugs. And now it's still showing its mettle in the discovery of drugs. This is not surprising since AI inventions have been a regular dose for tech enthusiasts. Today, AI can boost drug development and medical research that could cut down drug costs in the long term—including the COVID-19 vaccine.

The COVID-19 crisis has brought potentially far-reaching, long-term negative impacts on human life. Despite stringent lockdown measures and social distancing protocols, the number of positive cases and deaths are rising alarmingly. Due to such frightening and unforeseen conditions, experts are now focused on leveraging technologies to help them find a potential cure to this epidemic. Generally, discovering a new drug to cure an illness is like finding a needle in a haystack. It is also a costly, laborious, and time-consuming task.

Moreover, using the existing traditional drug discovery pipeline will take between five to ten years from the concept stage to the market and could cost billions in the process. The next challenge is conventional protein drug discovery approaches such as high-throughput scanning, which require a considerable number of unsuccessful research and error. This takes a lot of time for researchers who are searching for new drug volunteers. Thanks to supercomputers and artificial intelligence researchers, high-performance computing can now speed up this process by screening billions of chemical compounds rapidly to invent relevant drug candidates. They also help scientists track the genetic mutation of viruses over time, information that will determine any vaccine’s value in the future.

These instances of leveraging AI for accelerated drug discovery against COVID-19 have helped to enable a faster transition to clinical drug trials on humans. This feat would have considered impossible a year ago. According to official WHO info, as of early September, 34 vaccine candidates were tested in humans, and 145 additional candidates were tested in animals. Laboratories are currently pursuing at least eight different forms of vaccines. These involve conventional ones focused on inactivated viruses, as well as new, more experimental ones involving the use of genetic material—so-called DNA and RNA vaccines—and others based on unique proteins or other biological agents.

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