Artificial Intelligence (AI) Assisted Drug Discovery
There are many difficulties in the drug development process. In recent years, much attention has been focused on artificial intelligence (AI) that is emerging as a time-saving and labor-saving technology for drug design. As an expert in the field of drug design and synthesis, Creative Biolabs has been equipped to provide high-quality, short-period AI-based drug design services to customers all over the world.
Introduction of AI
AI, also known as machine intelligence. With the advancement of technology, AI has undergone revolutionary changes. Technologies such as SIRI and face recognition are all representative products of AI. It is particularly important to note that AI provides opportunities for the discovery and development of innovative drugs.
Due to the long development cycle and low success rate, the discovery and design of new drugs are an extremely long, expensive, and challenging process. AI-assisted drug discovery is the most promising way to solve this dilemma. By embedding data in high-dimensional space and extracting key relationships, AI provides innovative solutions for all stages of early drug discovery. The effective combination of AI and new experimental technology is expected to hunt new drugs faster, cheaper, and more effectively. More importantly, recent breakthroughs in AI have proven its potential in the pharmaceutical industry.
Why is AI used in Drug Discovery?
Identifying drugs that are beneficial for the body is the main purpose of research drug discovery. Most of these drugs are artificially mixed with small molecules. In order to discover these molecules, researchers need to study the molecular library to identify target molecules that have the potential to become drugs. Since the specific chemical structure that is biologically suitable as an effective drug is not clear, it is an expensive and time-consuming method to refine potential compounds into drug candidates. Based on the above facts, AI systems have emerged as a novel strategy for accelerating drug development and reducing the cost of finding new drugs due to their unparalleled data processing potential.
Fig.1 AI in drug development. (Mak, 2019)
AI in Drug Design
At present, a large number of AI-assisted drug discovery technologies have been used, including virtual screening, de novo drug design, prediction of physicochemical and pharmacokinetic properties, drug reuse and related aspects. In addition, AI also plays a major role in planning chemical synthesis, cell image processing, physical biological activity and toxicity prediction, and operating robotic systems for organic synthesis.
Fig.2 The applications of AI in drug discovery. (Pei, 2021)
AI virtual screening
AI can be used for the virtual screening of target molecules. Modeling based on sequence recognition algorithms, deep learning images, and millions of manually sorted active compound data, AI can identify the most potent compounds and determine their locations.
AI compound design
This strategy is developed on the premise of known active compounds to design high-quality derivatives or analogs. In this process, matching characteristics and conducting synthetic feasibility analysis can play a key role in finding high-quality lead compounds.
AI synthesis path design
Currently, some platforms can design synthetic routes for specific compounds. This process uses AI technology to generate a model to quickly recommend the synthesis path with the lowest cost and the highest success rate.
AI in predicting the structure of target molecular
The 3D structure of structural target proteins is essential for structure-based drug discovery. Traditional methods usually take several years to resolve the target molecular structure, while AI-based structure prediction only takes a few hours, making this process more time-saving and accurate.
The applications of AI to promote the drug identification process and the discovery of suitable molecules from the database have shown great potential in drug discovery. In addition, AI has great significance in different fields such as medical care, anti-aging, and cancer. We have established an advanced platform for drug screening and design. Our scientists have an in-depth understanding of the role of AI in drug synthesis and design. If you have difficulties with drug development, please contact us for help.
Mak, K. K.; Pichika, M. R. Artificial intelligence in drug development: present status and future prospects. Drug discovery today. 2019, 24(3): 773-780.
Pei, J.; Zhavoronkov, A. Artificial intelligence for Drug Discovery and Development. Frontiers Media SA. 2021.