Imagination is more important than knowledge.

15th March 2023

Improving The Drug Discovery And Development Process Through Big Data

Drug discovery and development is a remarkably complex process. It requires years of work, millions of dollars and exhaustive testing to see a new drug come to market. In fact, the process is so rigorous that less than 10%  of new pharmaceuticals actually reach the market. What can be done to improve these processes? Below is a brief look into how big data and artificial intelligence (AI) can be utilized to enhance the drug discovery and development process.

First, what is drug discovery and development? Consisting of numerous stages and key steps within each one, this arduous process focuses on identifying possible cures for known disease-related targets or ways to make an affliction more manageable. It relies on extensive research, accurate data and peer-reviewed trials well before it can reach approval for clinical trials. Such discovery and preclinical development is designed to strategically eliminate possibilities before an expensive late-stage investment can be made.

Progress in this field of research has been driven by several modern advancements, including in the areas of biological technology, robotics and computing power capabilities. The ability to draw on big data analysis and AI predictions is pushing its potential further. How might big data and AI software be used to enhance the process?

One way is in the contribution to the drug development community as a whole. As data is a key factor in identifying prospective applications for a drug, it can be used to analyze markets and predict outcomes using AI and machine learning technologies. Interpretation of this data also has the potential to enhance early decision-making and shorten project lead times.

Another way is by enhancing the computation-aided drug design process with emerging AI software. Already successful in generating 3D protein structure predictions involving molecular targets and similar design structures, AI-aided computational tools are accelerating many aspects of the discovery and development of new drugs. With investment into these cutting-edge digital applications, the possibilities in the pharmaceutical market are boundless.

While a lot of money goes into the production of a new drug, a lot can be gained in the rising global drug discovery market. Set to be valued at more than $71  billion by 2025, the market is ever-expanding with new or improved products. What’s more, data-driven drug development resources and methodologies could contribute to the expansion of biotech applications and further innovations within the realm of human health and wellness. For these reasons and many more like them, we’ll be seeing revolutionary approaches to drug discovery involving AI, big data analysis and beyond in the not-so-distant future.

Want to learn more? Please see the accompanying resource for further information on the drug discovery process and additional ways to improve upon it.

Presented by OmniAb – antibody discovery platform

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