Global Artificial Intelligence (AI) in Drugs Discovery Market Analysis

The Global Artificial Intelligence (AI) in Drugs Discovery Market Analysis size stood at around xx Bn in 2023 and is projected to reach US $xx Bn by 2033, exhibiting a CAGR of xx% during the forecast period.

The Global Artificial Intelligence (AI) in Drugs Discovery Market Analysis Executive Summary

AI in drug discovery presents the utilization of superior computing methodologies in the improvement of the drug discovery process and time effectiveness. Conventional drug discovery is a slow and an expensive process, it can take several years and billions of funds. Advanced tools of artificial intelligence like machine learning and natural language processing are changing this landscape through enhancing identification of targets, and/or properties of drugs, and/or designs of molecules. For example, it can mine large databases to find potential drugs and also predict how molecules would behave, thus lessening the use of large amounts of lab tests.

Currently, the utilization of AI in drug discovery is rapidly growing across the world; major investments are being made in this field. Based on the FDA, there were more than one hundred drug applications that included elements of AI/ML last year, proving their increased use. Furthermore, according to a report by Nature Medicine, while AI is still theoretical in many areas, new drugs developed by machine intelligence have gone into clinical trials. As the technology of AI advances further, it is believed to cut down the time for drug discovery and may result in the identification of new treatments for diseases that currently cannot be treated, thus improving the world’s health care systems.

Market Dynamics for Artificial Intelligence (AI) in Drugs Discovery Market in  Global

Market Growth Drivers

The integration of AI in drug discovery is importantly boosted by the capacity of AI in compressing the drug development cycle. AI technologies also can perform screenings and determine the efficacy of the drugs with a relative quicker and more efficient way as compared to traditional methods. For example, AI can make the expense of creating a new medicine less on average since the cost of launching a new drug is about $2. 6 Bn, by the enhancement of the medicinal discovery value chain. In addition, the FDA received over 100 submissions related to AI/ML in 2021 and thus, these technologies are being acceptance and integrated by more and more pharmaceutical companies to foster new innovation and new cooperation between the different stakeholders.

Opportunity

AI has already started promising brighter future in drug discovery and there is much more to discover in approaching technology and applications. AI will enhance identification and validation of targets in drug development cutting the costs and time in the first stages of the process. It will also increase the level of personalized medicine by identifying patients for therapies depending on their genetic make-up. Some of these firms are Atomwise and BenevolentAI that are embracing AI with conventional drug making procedures. Even governmental agencies have begun to update regulations on artificial intelligence being approved by the FDA and making it possible for the discovery of drugs to be a quicker a more efficient process.

Market Restraints

Despite the envisaged benefits of utilizing AI in drug discovery, there are a number of Barriers to its use. One of them is the scarcity of qualified personnel to apply and analyze the outcomes from the incorporation of AI practices. Further, AI produces uncertain results mainly because of the unexplained and opaque working of the models. This may result in rejection from the traditional researchers since they may not trust the AI systems more than the conventional methods that they have been trained on. Therefore, these factors can cause the slow implementation of AI in drug discovery, thus restraining the innovation created by the practice in the pharmaceutical field.

Competitive Landscape for Artificial Intelligence (AI) in Drugs Discovery Market in  Global

Key Players

• Atomwise
• BenevolentAI
• Exscientia
• Insilico Medicine
• Schrödinger
• Cyclica
• IBM Watson Health
• GNS Healthcare
• BERG Health
• Numerate

Recent Developments

December 2023, Merck launched the first AI solution integrating drug discovery and synthesis. This innovative tool combines generative AI, machine learning, and computer-aided drug design to screen over 60 Bn chemical targets, enhancing the success and efficiency of new drug development

Mergers and Acquisitions

January 2024, Vision Sensing Acquisition Corp. (VSAC) announced a merger with Mediforum Co., Ltd., a Korean biotechnology company specializing in ethical drugs and diagnostic reagents

Healthcare Policies and Regulatory Landscape for Artificial Intelligence (AI) in Drugs Discovery Market in  Global

Policy changes and Reimbursement scenario

The roles of the most recent healthcare policies and regulations for the implementation of artificial intelligence in drug discovery for the pharmaceutical sector have somewhat improved and are continuing to advance. More regulatory authorities are paying attention to the accreditation of AI applications that have regulatory oversight. For example, drugs and health IT agencies such as the FDA has started establishing guidelines for the use of AI and machine learning in drug development, especially in areas of transparency of such algorithms. Such modifications’ purpose involves implementing improvements in one’s research and development processes to innovate, protect patients, and maintain the confidentiality of patient information.

As for re-imbursements there is an increasing awareness of the necessity to cover AI-based drug discovery processes among insurance policies. With the advent of value-driven healthcare, the policies are being written that would allow utilization of the AI technologies that may advance the delivery of the new generations of the therapies.