Inteligencia artificial (IA) global en el mercado de descubrimiento de fármacos: tendencias de la industria y pronóstico hasta 2031

Análisis y tamaño del mercado de inteligencia artificial (IA) en el descubrimiento de fármacos

La inteligencia artificial (IA) en el mercado de descubrimiento de fármacos continúa su crecimiento exponencial, aprovechando los últimos métodos y tecnologías para revolucionar la investigación farmacéutica. A través de algoritmos avanzados y análisis de datos, la IA acelera los procesos de identificación y optimización de fármacos, reduciendo significativamente el tiempo y los costos. Su aplicación en el modelado predictivo, el cribado virtual y la identificación de objetivos mejora la eficiencia del desarrollo de fármacos, lo que promete avances en la lucha contra las enfermedades.                               

El tamaño del mercado global de inteligencia artificial (IA) en el descubrimiento de fármacos se valoró en USD 932,24 millones en 2023 y se proyecta que alcance los USD 1.409,14 millones para 2031, con una CAGR del 5,30% durante el período de pronóstico de 2024 a 2031. Esto indica que el valor del mercado. Además de los conocimientos sobre escenarios de mercado como el valor de mercado, la tasa de crecimiento, la segmentación, la cobertura geográfica y los principales actores, los informes de mercado seleccionados por Data Bridge Market Research también incluyen un análisis profundo de expertos, epidemiología de pacientes, análisis de cartera, análisis de precios y marco regulatorio.

Alcance del informe y segmentación del mercado

Definición de mercado

La inteligencia artificial (IA) en el descubrimiento de fármacos aprovecha algoritmos avanzados para analizar grandes conjuntos de datos, predecir interacciones moleculares y diseñar nuevos compuestos con potencial terapéutico. A través del aprendizaje automático y las técnicas de minería de datos, la IA acelera el proceso de desarrollo de fármacos, optimizando la selección de moléculas y reduciendo los costos. Mejora la identificación de objetivos, la optimización de los fármacos y la predicción de la toxicidad, revolucionando la investigación farmacéutica y agilizando la entrega de medicamentos que salvan vidas.            

Inteligencia artificial (IA) en la dinámica del mercado de descubrimiento de fármacos

Conductores

• Proceso acelerado de descubrimiento de fármacos

AI expedites the drug discovery process by analyzing vast datasets, predicting molecular interactions, and identifying potential drug candidates more rapidly than traditional methods.  For instance, Atomwise, using AI-powered virtual screening, identified a drug candidate for Ebola in just a few days, a process that typically takes months using traditional methods. This acceleration allows for quicker identification and development of promising compounds, potentially saving lives in urgent medical situations.

• Rise in Incidence of Chronic Diseases Propels Need

The surge in chronic diseases worldwide, exemplified by CDC data showing six in 10 U.S. adults affected, underscores the urgency for effective treatments. AI in drug discovery emerges as a promising solution to mitigate this health crisis. Through analyzing vast datasets, AI platforms offer insights into developing drugs targeting conditions such as heart disease and diabetes, addressing the pressing need for innovative therapies to reduce mortality rates.  

Opportunities

• Rising Collaboration and Data Sharing among Researchers

AI fosters collaboration among researchers and facilitates data sharing across institutions and companies, enabling access to diverse datasets and enhancing the collective knowledge base for drug discovery. For instance, platforms such as OpenAI's Drug Discovery, which harness AI to analyze molecular structures and predict drug properties, encourage collaborative efforts by providing a shared space for researchers to access and contribute to a vast pool of data, accelerating the pace of discovery and innovation in the pharmaceutical industry.

• Growing Demand for Personalized Medicine

AI facilitates personalized medicine by analyzing patient data, including genomics, proteomics, and clinical records, to identify biomarkers indicative of disease susceptibility and treatment response. For instance, AI-driven analysis of tumor genomic profiles can predict patient responses to specific cancer therapies, enabling tailored treatment strategies that maximize efficacy and minimize adverse effects, ultimately improving patient outcomes in oncology and beyond. 

Restraints/Challenges

• Integration with Traditional Methods Hinder Workflow

Integrating AI with traditional drug discovery methods faces hurdles in standardization, compatibility, and workflow optimization. Harmonizing AI algorithms with established experimental and computational techniques necessitates meticulous planning to ensure seamless integration, minimizing disruptions to existing workflows.   

• Data Privacy and Accessibility Limit Development

Access to proprietary data in drug discovery is restricted due to privacy, intellectual property, and regulatory constraints. This limits the availability of data for AI models, hindering their development and validation. Privacy concerns, especially regarding patient data, necessitate careful handling and compliance with regulations, further complicating data accessibility for AI-driven drug discovery initiatives.   

This market report provides details of new recent developments, trade regulations, import-export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on the market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Recent Development

• In July 2021, Chief.AI introduced a pay-as-you-go AI platform for drug discovery, democratizing access to advanced AI technologies. This empowers small and medium enterprises to pinpoint breakthrough therapeutics swiftly and precisely, addressing the unpredictability of traditional drug discovery
• In January 2021, Nucleai and Debiopharm Pharma formed a collaborative agreement, permitting the latter to utilize Nucleai's AI platform for oncology drug candidates. This underscores AI's growing significance in refining drug development processes, particularly in biomarker-based therapies
• In September 2020 witnessed Atomwise securing USD 123 million in Series B financing, led by Sanabil and B Capital Group Investments. This substantial investment aims to expand Atomwise's market presence, initiate its drug discovery pipeline, and forge new partnerships with pharmaceutical firms, emphasizing AI's pivotal role in advancing artificial intelligence in drug discovery and development
• In July 2020, IBM strategically acquired WDG Automation, enriching its AI-infused automation capabilities for enterprises. This strategic move enhances IBM's capacity to deliver comprehensive AI solutions, spanning from business processes to IT operations, thereby fortifying its overall portfolio

Artificial Intelligence (AI) in Drug Discovery Market Scope

The market is segmented on the basis of application, technology, drug type, offering, indication, and end use. The growth amongst these segments will help you analyze meagre growth segments in the industries and provide the users with a valuable market overview and market insights to help them make strategic decisions for identifying core market applications.

Application

• Novel Drug Candidates
• Drug Optimization and Repurposing Preclinical Testing and Approval
• Drug Monitoring
• Finding New Diseases Associated Targets and Pathways
• Understanding Disease Mechanisms
• Aggregating and Synthesizing Information
• Formation and Qualification of Hypotheses
• De Novo Drug Design
• Finding Drug Targets of an Old Drug
• Others

Technology

• Machine Learning
  • Supervised Learning
  • Reinforcement Learning
  • Unsupervised Learning
  • Other Machine Learning Technologies
• Deep Learning
• Natural Language Processing
• Others

Drug Type

• Small Molecule
• Large Molecule

Offering

• Software
• Services

Indication

• Immuno-Oncology
• Neurodegenerative Diseases
• Cardiovascular Diseases
• Metabolic Diseases
• Others

End Use

• Contract Research Organizations (CROs)
• Pharmaceutical and Biotechnology Companies
• Research Centers and Academic Institutes
• Others

Artificial Intelligence (AI) in Drug Discovery Market Regional Analysis/Insights

The market is analysed and market size insights and trends are provided by country, application, technology, drug type, offering, indication, and end use as referenced above.

The countries covered in the market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

North America is expected to dominate the artificial intelligence (AI) in drug discovery market, driven by substantial research investments and widespread AI adoption in medicine development. Key players such as IBM, Google, and Microsoft strengthen the region's influence and technological advancement, catalyzing market growth significantly.

Asia-Pacific is expected to witness rapid growth in the artificial intelligence (AI) in drug discovery market due to heightened investments in research and development initiatives. The region's evolving healthcare infrastructure further accelerates market expansion, underscoring its growing influence in shaping AI applications for drug discovery.

The country section of the report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points like down-stream and upstream value chain analysis, technical trends and porter's five forces analysis, case studies are some of the pointers used to forecast the market scenario for individual countries. Also, the presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.   

Healthcare Infrastructure growth Installed base and New Technology Penetration

El mercado también le ofrece un análisis detallado del mercado para cada país: crecimiento del gasto sanitario en equipos de capital, base instalada de diferentes tipos de productos para el mercado, impacto de la tecnología mediante curvas de línea de vida y cambios en los escenarios regulatorios de la atención sanitaria y su impacto en el mercado. Los datos están disponibles para el período histórico 2016-2021.

Análisis de la cuota de mercado de la inteligencia artificial (IA) y el panorama competitivo en el descubrimiento de fármacos

El panorama competitivo del mercado proporciona detalles por competidor. Los detalles incluidos son una descripción general de la empresa, las finanzas de la empresa, los ingresos generados, el potencial de mercado, la inversión en investigación y desarrollo, las nuevas iniciativas de mercado, la presencia global, los sitios e instalaciones de producción, las capacidades de producción, las fortalezas y debilidades de la empresa, el lanzamiento de productos, la amplitud y variedad de productos, y el dominio de las aplicaciones. Los puntos de datos anteriores proporcionados solo están relacionados con el enfoque de las empresas en relación con el mercado.

Algunos de los principales actores que operan en el mercado son:

• NVIDIA Corporation (Estados Unidos)
• IBM Corp. (Estados Unidos)
• Atomwise Inc. (Estados Unidos)
• Microsoft (Estados Unidos)
• IA benévola (Reino Unido)
• Aria Pharmaceuticals, Inc. (Estados Unidos)
• GENÓMICA PROFUNDA (Canadá)
• Exscientia (Reino Unido)
• Medicina Insilico (Hong Kong)
• Cyclica (Canadá)
• NuMedii, Inc. (Estados Unidos)
• Envisagenics (Estados Unidos)
• Owkin Inc. (Estados Unidos)
• BERG LLC (Estados Unidos)
• Schrödinger, Inc. (Estados Unidos)
• XtalPi Inc. (China)
• BIOAGE Inc. (Estados Unidos)

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