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市場調查報告書
商品編碼
1663320
醫藥品商業化的AI:市場洞察·競爭情形·市場預測 (~2032年)Artificial Intelligence (AI) in Drug Commercialization - Market Insights, Competitive Landscape, and Market Forecast - 2032 |
預測期內,醫藥商業化人工智慧的市場規模預計將以 24.12% 的複合年增長率成長。
慢性病發病率的上升推動了對創新有效治療的需求,從而加速了人工智慧驅動的藥物商業化的需求。對真實世界證據 (RWE) 的日益重視使得製藥公司能夠將 AI 應用於個人化醫療,從而優化藥物開發和上市。此外,技術供應商和製藥公司之間加強的合作正在加速人工智慧的整合,增強數據分析能力,並簡化商業化流程。
市場動態:
根據全球癌症觀察站的最新數據,預計2022年全球將記錄2,000萬例新發癌症病例,到2045年預計將上升至3,260萬例。癌症仍然是發病率和死亡率的主要原因,促使製藥公司越來越注重開發精準抗癌藥物、免疫療法和標靶療法。人工智慧透過增強藥物發現、臨床試驗設計和患者分層,實現更快、更有效的商業化,在這項努力中發揮著至關重要的作用。人工智慧驅動的真實世界證據 (RWE) 分析可以幫助製藥公司更好地了解治療反應、預測疾病進展並改善商業化策略。此外,人工智慧生物標記分析可以幫助識別理想的患者群體,改善抗癌藥物的市場進入和採用。
除腫瘤學外,心血管疾病(CVD)也正在推動人工智慧在藥物商業化的應用。根據世界心臟聯盟(2024)的預測,2022 年全球將有約 6,000 萬人罹患心房顫動。它是最常見的心律不整之一,會增加血栓、心臟衰竭和中風的風險;患有心房顫動的人中風的可能性高出五倍。人工智慧正在透過分析大型數據集來識別潛在的候選藥物,從而改變心血管疾病藥物的發現和再利用過程,減少開發時間和成本。鑑於心血管疾病的複雜性,人工智慧將幫助製藥公司透過挖掘現有研究、患者記錄和臨床試驗數據來發現新的治療方案。
本報告提供全球醫藥品商業化的AI的市場調查,彙整市場概要,市場影響因素及市場機會分析,法律制度,市場規模的轉變·預測,各種區分·地區/各主要國家的詳細分析,競爭情形,主要企業簡介等資訊。
Artificial Intelligence (AI) in Drug Commercialization Market by Service Type (Regulatory and Legal Services, Market Access and Pricing, Marketing and Branding, and Others), Drug Type (Small Molecules and Biologics), Commercialization Stage (Pre-launch, Launch, and Post-launch), Indication (Oncology, Cardiovascular, Neurology, Infectious Disease, and Others), End-User (Pharma and Biotech Companies, Contract Research Organizations (CROs), and Others), and Geography (North America, Europe, Asia-Pacific, and Rest of the World) is expected to grow at a steady CAGR forecast till 2032 owing to the increasing prevalence of chronic diseases, the growing importance of Real-World Evidence (RWE) in driving personalized medicine, and growing collaborations among technology companies and pharmaceutical firms to advance AI-driven drug commercialization.
The artificial intelligence in drug commercialization market is estimated to grow at a CAGR of 24.12% during the forecast period from 2025 to 2032. The rising prevalence of chronic diseases is driving demand for innovative and effective treatments, fueling the need for AI-driven drug commercialization. The growing emphasis on Real-World Evidence (RWE) enables pharmaceutical companies to harness AI for personalized medicine, optimizing both drug development and market positioning. Additionally, increasing collaborations between technology providers and pharmaceutical firms are accelerating AI integration, enhancing data analytics capabilities, and streamlining commercialization processes.
Collectively, these factors are propelling the AI-driven drug commercialization market by improving decision-making, reducing costs, and expediting drug approvals, ultimately leading to more efficient and targeted healthcare solutions. As a result, the market is expected to witness significant growth during the forecast period from 2025 to 2032.
Artificial Intelligence in Drug Commercialization Market Dynamics:
According to the latest data from the Global Cancer Observatory, an estimated 20 million new cancer cases were recorded globally in 2022, with projections rising to 32.6 million cases by 2045. As cancer remains a leading cause of morbidity and mortality, pharmaceutical companies are increasingly focusing on developing precision oncology drugs, immunotherapies, and targeted treatments. Artificial Intelligence (AI) plays a pivotal role in this effort by enhancing drug discovery, clinical trial design, and patient stratification, ensuring faster and more effective commercialization. AI-driven analysis of Real-World Evidence (RWE) enables pharmaceutical firms to better understand treatment responses, predict disease progression, and refine commercialization strategies. Additionally, AI-powered biomarker analysis helps identify ideal patient populations, improving market access and adoption of cancer therapies.
Beyond oncology, cardiovascular diseases (CVDs) are also driving AI adoption in drug commercialization. According to the World Heart Federation (2024), approximately 60 million people worldwide were affected by atrial fibrillation in 2022, one of the most common forms of arrhythmia, which increases the risk of blood clots, heart failure, and stroke. Individuals with atrial fibrillation are five times more likely to suffer a stroke. AI is transforming the drug discovery and repurposing process for CVDs by analyzing large datasets to identify potential drug candidates, reducing development time and costs. Given the complexity of CVDs, AI enables pharmaceutical companies to uncover novel treatment options by mining existing research, patient records, and clinical trial data.
Moreover, AI is playing a critical role in optimizing drug pricing models by analyzing extensive datasets to identify trends and support value-based pricing structures that benefit both pharmaceutical companies and healthcare systems. By leveraging AI, companies can streamline reimbursement processes, improve patient access to innovative therapies, and enhance decision-making throughout drug commercialization. AI-driven analytics also assist firms in predicting market demand, assessing competitive landscapes, and refining launch strategies, ultimately reducing costs and expediting time-to-market for new therapies.
For instance, in January 2025, Lyfegen, a global innovator in drug market access, pricing, and rebate management, announced a transformative collaboration with EVERSANA, a leading provider of global commercial services to the life sciences industry. This partnership aims to revolutionize drug pricing and access through AI-driven insights, underscoring the technology's growing influence in the pharmaceutical landscape.
These factors collectively are expected to propel the global AI in drug commercialization market during the forecast period from 2025 to 2032 by improving efficiency, reducing costs, and enhancing patient access to innovative treatments.
However, challenges remain. Privacy and data security concerns, along with resistance to AI adoption stemming from a lack of understanding or fears of job displacement, may pose obstacles to market growth.
Artificial Intelligence in Drug Commercialization Market Segment Analysis:
Artificial Intelligence in Drug Commercialization Market by Service Type (Regulatory and Legal Services, Market Access and Pricing, Marketing and Branding, and Others), Drug Type (Small Molecules and Biologics), Commercialization Stage (Pre-launch, Launch, and Post-launch), Indication (Oncology, Cardiovascular, Neurology, Infectious Disease, and Others), End-User (Pharma and Biotech Companies, Contract Research Organizations (CROs), and Others), and Geography (North America, Europe, Asia-Pacific, and Rest of the World)
In the drug type segment of artificial intelligence (AI) in drug commercialization market, the small molecules category is expected to hold a significant share in 2024. Small molecules, characterized by their simple chemical structures and low molecular weight, have long been the backbone of pharmaceutical development, comprising the majority of approved drugs for a range of conditions, including infectious diseases, cancer, diabetes, and hypertension. Their versatility and oral bioavailability make them crucial in treating both acute and chronic diseases.
AI is playing an increasingly vital role in optimizing the commercialization of small molecule drugs by enhancing key processes:
AI-powered algorithms can analyze vast datasets to identify promising small molecule candidates with greater speed and precision than traditional methods. This significantly shortens the preclinical and clinical development phases, allowing new therapies to reach the market faster.
AI facilitates the forecasting of market demand, price optimization, and market segmentation by leveraging big data and predictive analytics. This ensures that pharmaceutical companies can better identify optimal markets for commercialization and set competitive pricing strategies.
AI-driven tools help anticipate and mitigate supply chain disruptions, ensuring that small molecule drugs are delivered to the right markets and patients efficiently.
AI enables targeted outreach to healthcare professionals and patients through data-driven marketing strategies. This personalized approach aids in raising awareness and boosting adoption rates of small molecule therapies across diverse regions.
As AI technology continues to evolve, its integration into drug commercialization processes is expected to deepen, helping pharmaceutical companies streamline operations, improve patient outcomes, and enhance market competitiveness.
Thus, these factors collectively are expected to drive growth in the small molecules segment, thereby boosting the overall artificial intelligence in drug commercialization market globally during the forecast period.
North America is expected to dominate the overall artificial intelligence in drug commercialization market:
North America is expected to hold the largest share of artificial intelligence (AI) in drug commercialization market in 2024. This dominance is attributed to the region's robust biotechnology and pharmaceutical industries, advanced healthcare infrastructure, and significant investments in AI research and development. The high prevalence of chronic diseases further drives the demand for AI-driven drug commercialization solutions.
According to GLOBOCAN (2022), North America reported approximately 2.67 million new cancer cases, with projections indicating a rise to 3.83 million by 2045. AI-powered platforms leverage genomic profiles and Real-World Evidence (RWE) from regional patient data to optimize drug discovery, pricing models, and regulatory processes. The region's strong healthcare ecosystem and ongoing collaborations between pharmaceutical companies and AI developers are accelerating commercialization timelines.
AI's integration into precision medicine is particularly impactful in oncology, enabling the identification of biomarkers, patient stratification, and the development of targeted therapies that improve treatment efficacy and accessibility. The synergy between the rising cancer burden and AI's capabilities has established a strong growth trajectory for the market.
Further reflecting this trend, in March 2024, Tonix Pharmaceuticals Holding Corp. partnered with EVERSANA(R), a leading provider of global commercialization services, to support the launch strategy and commercial planning for Tonmya(TM) (TNX-102 SL), a drug under development for fibromyalgia in the U.S. market. This collaboration highlights the increasing reliance on AI-driven strategies in pharmaceutical commercialization, enhancing efficiency, patient targeting, and overall market success.
Thus, all these factors are expected to propel the growth of the artificial intelligence in drug commercialization market in North America during the forecast period from 2025 to 2032.
Artificial Intelligence in Drug Commercialization Market Key Players:
Some of the key market players operating in the artificial intelligence in drug commercialization market include EVERSANA, Lyfegen, Syneos Health, McKinsey & Company, ICON plc., Clarivate., Thermo Fisher Scientific Inc., Viseven, ZS Associates, Cloud Pharmaceuticals Inc., and others.
Recent Developmental Activities in the Artificial Intelligence in Drug Commercialization Market:
Key Takeaways From the Artificial Intelligence in Drug Commercialization Market Report Study
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