The adoption of artificial intelligence (AI) in the pharmaceutical and biotech sectors is expanding beyond drug discovery to include research and development (R&D) support, manufacturing, commercialization, and regulatory strategies. Initially, AI was primarily used for identifying drug candidates and analyzing clinical data. Now, it is enhancing production efficiency, quality control, market entry strategies, regulatory compliance, and automating internal documentation, accelerating the trend of 'AI transformation' (AX).
According to a report by Samil PwC titled 'Innovation in Pharmaceutical Companies Based on AI,' companies that fully integrate AI across their organizations could potentially double their operating profits by 2030. Specifically, if the level of AI integration in the pharmaceutical industry increases, it is projected to generate an additional annual operating profit of approximately $254 billion by 2030. The United States is expected to lead with $155 billion, followed by emerging markets at $52 billion and Europe at $33 billion.
The role of AI in the pharmaceutical industry is most pronounced in R&D. AI enhances speed and accuracy in candidate discovery, preclinical and clinical trial design, site selection, and document automation.
For instance, global pharmaceutical giant Merck utilizes its AI-based drug development platform, AIDDISON, to screen 60 billion compounds and propose new synthesis methods to identify optimal candidates. Amgen has developed a machine learning-based clinical optimization platform, ATOMIC (Analytical Trial Optimization Module), which has more than doubled the speed of patient enrollment in clinical trials.
AI's benefits are also evident in operational areas. The pharmaceutical industry increasingly employs AI for optimizing production schedules, predictive maintenance, quality control, and demand forecasting. For example, Sanofi has introduced an AI-based decision-making app called Plai, developed in collaboration with Aily Labs, for use in R&D, clinical trials, and manufacturing.
AI's role in regulatory strategies is also growing. New models are emerging that utilize large language databases to assist with inquiries from regulatory agencies and predict the likelihood of approval for submitted documents, evolving into a 'helper for market entry and approval strategies.'
In line with this trend, global pharmaceutical companies are ramping up their AI investments. Eli Lilly announced plans in January to jointly invest up to $1 billion with NVIDIA to establish an AI innovation lab over the next five years. Novo Nordisk is collaborating with OpenAI, while Bristol Myers Squibb (BMS) is integrating Anthropic's generative AI across its operations.
Domestic pharmaceutical companies are also quickly accelerating their AI initiatives. Celltrion recently announced plans to fully integrate AI into three key areas: drug development, manufacturing, and administration. The company aims to apply AI throughout the candidate discovery and validation stages, as well as in production and administrative tasks, to enhance development speed, production efficiency, and automation.
SK Biopharm has established an AI and Digital Transformation Center and is advancing its overall digital innovation strategy, expanding the application of systems such as automated personalized news reports.
AI integration has also begun in regulatory tasks. GC Green Cross recently developed an AI-based regulatory affairs chatbot called RegulAItor. This chatbot is designed to assist regulatory affairs personnel in formulating strategies and reviewing documents by utilizing datasets from FDA guidelines and internal approval documents.
In the pharmaceutical industry, AI is not only a 'future investment' that increases the likelihood of drug success but also a 'current cost-saving measure' that reduces inefficiencies in production, quality, sales, and support functions. An industry insider stated, "We view AX not merely as a digital transformation but as a restructuring aimed at both defending profitability and pursuing growth strategies. AI is no longer just an 'experimental tool' but has become a management infrastructure that changes the profit structure and work processes themselves."
According to a report by Samil PwC titled 'Innovation in Pharmaceutical Companies Based on AI,' companies that fully integrate AI across their organizations could potentially double their operating profits by 2030. Specifically, if the level of AI integration in the pharmaceutical industry increases, it is projected to generate an additional annual operating profit of approximately $254 billion by 2030. The United States is expected to lead with $155 billion, followed by emerging markets at $52 billion and Europe at $33 billion.
The role of AI in the pharmaceutical industry is most pronounced in R&D. AI enhances speed and accuracy in candidate discovery, preclinical and clinical trial design, site selection, and document automation.
For instance, global pharmaceutical giant Merck utilizes its AI-based drug development platform, AIDDISON, to screen 60 billion compounds and propose new synthesis methods to identify optimal candidates. Amgen has developed a machine learning-based clinical optimization platform, ATOMIC (Analytical Trial Optimization Module), which has more than doubled the speed of patient enrollment in clinical trials.
AI's benefits are also evident in operational areas. The pharmaceutical industry increasingly employs AI for optimizing production schedules, predictive maintenance, quality control, and demand forecasting. For example, Sanofi has introduced an AI-based decision-making app called Plai, developed in collaboration with Aily Labs, for use in R&D, clinical trials, and manufacturing.
AI's role in regulatory strategies is also growing. New models are emerging that utilize large language databases to assist with inquiries from regulatory agencies and predict the likelihood of approval for submitted documents, evolving into a 'helper for market entry and approval strategies.'
In line with this trend, global pharmaceutical companies are ramping up their AI investments. Eli Lilly announced plans in January to jointly invest up to $1 billion with NVIDIA to establish an AI innovation lab over the next five years. Novo Nordisk is collaborating with OpenAI, while Bristol Myers Squibb (BMS) is integrating Anthropic's generative AI across its operations.
Domestic pharmaceutical companies are also quickly accelerating their AI initiatives. Celltrion recently announced plans to fully integrate AI into three key areas: drug development, manufacturing, and administration. The company aims to apply AI throughout the candidate discovery and validation stages, as well as in production and administrative tasks, to enhance development speed, production efficiency, and automation.
SK Biopharm has established an AI and Digital Transformation Center and is advancing its overall digital innovation strategy, expanding the application of systems such as automated personalized news reports.
AI integration has also begun in regulatory tasks. GC Green Cross recently developed an AI-based regulatory affairs chatbot called RegulAItor. This chatbot is designed to assist regulatory affairs personnel in formulating strategies and reviewing documents by utilizing datasets from FDA guidelines and internal approval documents.
In the pharmaceutical industry, AI is not only a 'future investment' that increases the likelihood of drug success but also a 'current cost-saving measure' that reduces inefficiencies in production, quality, sales, and support functions. An industry insider stated, "We view AX not merely as a digital transformation but as a restructuring aimed at both defending profitability and pursuing growth strategies. AI is no longer just an 'experimental tool' but has become a management infrastructure that changes the profit structure and work processes themselves."
* This article has been translated by AI.
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