by Qualer

AI and Biotech Trends

Overview

 The cost of discovering and making pharmaceuticals can be staggering. A cool few billion dollars and a decade might yield a successful new drug. Or it might not. And given the current COVID-19 crisis, researchers are racing to speed up this process while lowering costs. What to do?

 Drug Discovery Challenges

Given the great expense and time investments needed for safe, functional pharmaceutical products, there is a lot on the line for each one brought to market. And not every contender ever makes it that far.

 In fact, nine out of ten drugs never make it to market. Many do not even get past the clinical trial stage. So, the great development “funnel” winnows out a lot of prospects. That is a formidable amount of money and time spent on something that will not go on to aid humanity.

 It is of utmost importance to find promising drug targets that are safe enough to make it to clinical trial stages and beyond. This arduous process involves understanding molecular structure of various compounds and how they would interact in the body to activate or inhibit processes.

 Recently, artificial intelligence (AI) has been used more frequently to help and identify drug targets. This vastly reduces the time and cost of potential pharmaceutical rollouts. The reason this option may dominate the scene within a decade or so is because machines can filter through the drug design process much faster than humans can. Machine learning results in finding more new compounds that could be used toward drug development.

 Tailoring Existing Pharmaceuticals for New Treatments

 The COVID-19 pandemic has made finding new drugs, vaccines, and uses for existing treatments of paramount importance.

 Taking an existing, safe drug and finding a new use for it would take an enormous amount of time to study if done by traditional methods. Now, with AI and machine learning, this process is much faster. It is an attractive method for finding new treatments partly because of existing drugs’ rigorous testing that brought them to market to begin with.

 Given that time is of the essence in a pandemic, and we face many more challenges both in infectious and chronic diseases, it only makes sense that pharmaceuticals and biotech companies should rely more on AI and machine learning headed into the future.

 Beyond the science fiction tropes of the evil AI computer that takes over and runs amok, we live in an era in which the reality of science and AI could mean a great new landscape for improving life as we know it.

 Given the advanced needs of this new paradigm, research facilities will need to keep on top of their regulatory documents and validation more than ever, and have such information at their fingertips in real time. Qualer can help with that.

 Qualer stands ready to build a bridge to this new era in pharmaceuticals and technology.

 

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 Sources: 

Tech Xplore: Using artificial intelligence to find new uses for existing medications

https://techxplore.com/news/2021-01-artificial-intelligence-medications.html?utm_source=nwletter&utm_medium=email&utm_campaign=daily-nwletter

 Technology Networks: The Changing Landscape of Target-Based Drug Discovery https://www.technologynetworks.com/drug-discovery/articles/the-changing-landscape-of-target-based-drug-discovery-342886

 

Topics: biotechnology, AI

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