의약품 상업화 분야 AI 시장 규모는 예측 기간 동안 연평균 24.12%의 CAGR로 성장할 것으로 예상됩니다.
만성질환의 유병률 증가는 혁신적이고 효과적인 치료법에 대한 수요를 촉진하고, AI 기반 의약품 상용화의 필요성을 가속화시키고 있습니다. 리얼월드에비던스(RWE)에 대한 관심이 높아지면서 제약사들은 AI를 맞춤형 의료에 활용하여 의약품 개발 및 시장 개척을 최적화할 수 있게 되었습니다. 또한, 기술 제공업체와 제약사 간의 협업이 증가함에 따라 AI의 통합이 가속화되고 데이터 분석 능력이 강화되어 제품화 프로세스가 간소화되고 있습니다.
시장 역학:
Global Cancer Observatory의 최신 데이터에 따르면, 2022년에는 전 세계적으로 약 2,000만 건의 신규 암 사례가 기록될 것으로 예상되며, 2045년에는 3,260만 건으로 증가할 것으로 예측됩니다. 암은 여전히 주요 사망률과 이환율의 주요 원인이기 때문에 제약사들은 정밀 암 치료제, 면역치료제, 표적 치료제 개발에 점점 더 많은 노력을 기울이고 있으며, AI는 신약개발, 임상시험 설계, 환자 분류를 강화하고 보다 신속하고 효과적인 제품화를 실현함으로써 이러한 노력에 매우 중요한 역할을 하고 있습니다. AI를 활용한 RWE(Real World Evidence) 분석을 통해 제약사들은 치료 반응에 대한 이해를 높이고, 질병 진행을 예측하며, 상업화 전략을 정교화할 수 있습니다. 또한, AI 기반 바이오마커 분석은 이상적인 환자 집단을 찾아내어 암 치료제의 시장 진입과 채택을 개선하는 데 도움이 됩니다.
암 분야 외에도 심혈관질환(CVD)도 의약품 상용화에 AI의 도입을 촉진하고 있으며, 세계심장연맹(World Heart Federation, 2024년)에 따르면 2022년에는 전 세계적으로 약 6,000만 명이 심방세동으로 고통받고 있습니다. 심방세동은 가장 흔한 부정맥 중 하나로 혈전, 심부전, 뇌졸중의 위험을 증가시키며, 심방세동 환자는 뇌졸중 발생 가능성이 5배 더 높은 것으로 알려져 있습니다. CVD의 복잡성을 고려할 때, AI는 기존 연구, 환자 기록, 임상시험 데이터를 마이닝함으로써 제약회사가 새로운 치료 옵션을 발견할 수 있게 해줄 것입니다.
세계의 의약품 상업화 분야 인공지능(AI) 시장을 조사했으며, 시장 개요, 시장 영향요인 및 시장 기회 분석, 법·규제 환경, 시장 규모 추정과 예측, 각종 부문별·지역별·주요 국가별 상세 분석, 경쟁 구도, 주요 기업 개요 등의 정보를 정리하여 전해드립니다.
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.
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