Global Artificial Intelligence (AI) in Pharma Market Analysis

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

Artificial Intelligence or AI is changing the face of the pharma business and bringing possibilities in the development of medicines, formulation, and even delivery. AI is rapidly gaining popularity across the world in pharma due to the enhanced efficiency, cost-effectiveness and value it brings in the overall handling of processes and management of patient care.

AI can process big biological databases to search for the significant drug targets and estimate molecule interactions with high speed. A study revealed that using artificial intelligence in virtual screening for finding the candidate drugs for Ebola was accomplished within few days while the normal traditional method takes few months. The FDA released information on the submissions of AI/ML based products which crossed more than a hundred in 2021, suggesting that the acceptance of these technologies is on the rise.

However, there are still issues that need to be addressed, for example, personnel deficits especially for specialized personnel, data protection issues, and concerns on the bias of the data and lack of concise policies governing the use of big data. For instance, the World Health Organization has encouraged the implementation of AI in health care systems in order to improve the efficiency of diagnosing as well as acting on the diagnosis. In the future, AI is believed to be becoming pivotal for such a revolutionary approach towards medicine, which is the so-called personalized medicine, meaning that treatments are tailored to a patient’s genetic profile and would provide a better outcome. 

Market Dynamics for Artificial Intelligence (AI) in Pharma Market in Global

Market Growth Drivers

The use of AI in the context of the pharmaceutical industry is further supported by the effectiveness of the applied methods that contributes improved realization of operational activities. The breakthrough in AI, therefore, revolves around its ability to assess big data molecules to arrive at conclusive drug prospects faster than conventional drug discovery and further predict how effective such a drug will be before its development is completed. According to the Nature Reviews Drug Discovery study, applied to R&D, AI might save drug makers as much as $50 billion annually. Also, the growing interest in precision medicine and precision treatment increases the AI demand as such tools allow treating patients according to their data, which would not only enhance their results but also their satisfaction. 

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

On the other hand, there are various factors that negatively impact on the implementation of AI in the field of pharmaceuticals. The threat to privacy and data security is due to the confidential nature of health data; thereby discouraging organisations from adopting AI solutions. Nevertheless, there is still a shortage of qualified specialists who would be able to use these tools effectively. An article in Clinical Pharmacology & Therapeutics also stresses on the need and development of ethical and applicable regulatory measures when it comes to AI in drug development. These regulatory concerns resulting in unclarities along with algorithmic risks and deceptively intricate nature of incorporating AI into the processes of the industry affect the cautiousness of stakeholders and hinder the advent of the AI technologies into the pharmaceutical business ventures. 

Competitive Landscape for Artificial Intelligence (AI) in Pharma Market in Global

Key Players

• IBM Watson Health
• Google DeepMind
• Microsoft
• NVIDIA Corporation
• Atomwise, Inc.
• BenevolentAI
• BioXcel Therapeutics, Inc.
• Insilico Medicine
• Exscientia
• PathAI 

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 Pharma 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.