Artificial Intelligence (AI) in Drug Discovery: A Peek Inside the Approaching future of Drug Research and Discovery

Several industries have improved and advanced using AI technology, including the healthcare sector. As per healthcare experts of BIS Research, the global AI-enabled drug discovery and clinical trials market is projected to witness high growth and touch $4238.7 Million by 2029, with a growth rate (CAGR) of 24.88%.

In this article, we’ll discuss how AI technology is used for drug discovery, its benefits and challenges, and the current situation of the AI-based drug discovery market.

What is Artificial Intelligence and How it Helps in Drug Discovery?

Artificial intelligence refers to making machines capable of working and thinking like humans with continuously advancing themselves with the provided data. The traditional way of drug research and discovery was cost-intensive and time-consuming, with several resource consumption and manual intervention. Identifying the accurately targeted material like RNA, DNA, or protein through the traditional method was like locating a needle in a haystack.

In the drug research and discovery process, a high quantity of internal information is generated and collected from several external pathways, phenotype expression, proteomic databases, and sequence expression.

Using artificial intelligence (AI), the collected data from different sources can easily be processed via advanced AI and get the required insights, patterns, and information for drug discovery. Also, AI can help to check different targets with less manual intervention in a much more accurate and faster manner.

Benefits of Adopting Artificial Intelligence for Drug Discovery

• AI technology is not dependable on treatments that are predetermined for drug research and discovery. Therefore, existing knowledge and subjective preference are not an obstacle in the drug development method using AI technology.
• AI technology uses advanced computing and biology to develop high algorithms for drug research and discovery. Due to the continuous rise in processing strength and reducing processing cost, artificial intelligence has the higher capabilities to raise the drug development standards.
• AI technology has better predictive power for determining the meaningful interaction taking place in a drug screen. Thus, the chances of false positives are reduced by accurately designing the parameters in specific drug discovery questions.
• Most importantly, artificial intelligence has the capability of moving drug screening from a traditional manner to virtual labs. It can help in getting the drug results at a greater speed by shortlisting the promising targets without any extensive experiments and manpower.

Market Overview of Global AI-Enabled Drug Discovery and Clinical Trials

In the last few decades, there has been a continuous increase in the data of the healthcare sector, which has resulted in the high need for advanced technology.

As per NEJM Catalyst, approximately 30% of global data is being generated by the healthcare sector alone. Furthermore, every single patient generated nearly 80 megabytes (MG) of data on an annual basis.

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Today, several technologies like artificial intelligence (AI), machine learning (ML), supervised learning, and deep learning are helping in better research for the healthcare sector.

In the area of healthcare research, especially for drug discovery and clinical trials, artificial intelligence processes several benefits like the generation of 3D models for depicting drug and ligand interactions, data gathering and analysis, designs of clinical studies, evidence from the real world, and optimizing clinical trials.

Due to several untapped opportunities, for instance, expansion in developing countries like Latin America, China, and Japan, the future of the global market for AI-enabled drug discovery and clinical trials market is promising. Furthermore, Saudi Arabia and the Middle East are investing high amounts in the healthcare sector and resulting in higher expansion chances in the regions.

Challenges of Artificial Intelligence in Drug Research and Discovery

AI has great potential to change the situation of drug research and discovery, but it has also got several challenges. The most common challenges faced by AI in drug discovery are lack of accurate data, absence of interoperability, and dimensionality.

The lack of proper data is one of the most recurring problems faced by nearly every sector adopting artificial intelligence. For AI technology, data is the most important thing for performing better and developing them with time. So, if required data is absent, machines will never be able to make themselves advance with time and hence result in failure.

Conclusion

The older method of drug discovery is a time taking process and requires several studies to understand and know the possible side effects of the drugs. However, with the adoption of artificial technology, the healthcare sector can have positive impacts and will be able to perform drug discovery seamlessly. In the upcoming years, artificial intelligence is going to bring revolution in the drug discovery process and will be responsible for reinventing the healthcare and pharmaceutical sector.

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