Artificial Intelligence in Drug Discovery Market Analysis:
The artificial intelligence in drug discovery market is evolving at very fast pace across the pharmaceutical industry and making commitments towards change in the drug discovery process and accurate predictions. Machine learning, deep learning and predictive analytics are being applied in critical steps in drug discovery process including target identification, molecule screening and drug optimization. These tools help pharmaceutical firms process big data faster, identify new drugs, estimate the efficiency and safety of the compounds, and avoid high costs and long time required for drug creation.
There is a rising need for better target treatment, and there is an upsurge in the global diseases that are chronic in nature. Of all the areas of AI in drug discovery, the most significant is the identification of targets for drugs and the selection of patients for clinical trials. The market is driving by the partnerships between the pharmaceutical companies and the AI solution providers and significant funding that is targeted at improving the AI solutions for the respective platforms. It is believed that the advancement in the technology will enhance the subsequent advancements in drug discovery in terms of productivity and new drug development.
Key Points and Statistics on the Artificial Intelligence in Drug Discovery Market:
· The global artificial intelligence in drug discovery market is projected to reach a valuation of USD 12.02 billion by 2032, growing at a CAGR of approximately 27.8% from 2024 to 2032
· In 2023, the market was valued at around USD 1.35 billion
· The market is categorized based on type, therapeutic area, technology, end-user, and region
· North America is expected to remain the largest revenue-generating region through 2032
· The Asia-Pacific region is forecasted to experience the fastest growth between 2024 and 2032
· Target identification is anticipated to lead the type segment of the market
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Increasing Incidences of Chronic Disorders Fuels the Global Artificial Intelligence (AI) in Drug Discovery Market Growth
The rise in the number of chronic diseases like cancer, diabetes, cardiovascular diseases, and neurodegenerative disorders is a major factor that is also fueling the market growth of artificial intelligence (AI) in drug discovery. A vast number of deaths have been attributed to chronic diseases, which is why healthcare systems are on the verge of collapse and why chronic diseases cannot be treated with conventional methods. This is an area where AI technologies can significantly help to overcome this challenge by speeding up drug discovery. AI Platforms could help in early identification of drug targets, faster screening of molecules and better design of clinical trials thereby helping in lowering the time and costs involved in getting new treatments to the market. This efficiency is especially valuable when it comes to managing such diseases as diabetes, which, as a rule, necessitates customized treatment plans.
As the need to develop new and better treatments for chronic diseases persist, the use of AI in pharmaceutical firms is growing. AI models can easily go through large amounts of medical data, identify previously unknown patterns and accurately forecast the patients’ reactions to the new drug candidates. These capabilities are critical to creating better treatments, enhancing the quality of life of patients, and lowering healthcare expenditures related to chronic illness. For that reason, it is believed that the integration of AI into drug discovery will stay on the rise due to the necessity to combat chronic diseases and provide more individualized, accurate, and effective treatments.
Focus on Developing Human-Aware AI Systems Creates Significant Market Opportunities
The emphasis on the creation of human-aware AI systems is generating vast market prospects in the Artificial Intelligence (AI) in Drug Discovery market. Human-aware AI systems are created to be able not only to process complicated biological information but also to take into consideration human body, actions and relations in the process of creating new drugs. These systems can assist the pharmaceutical organizations to create better and targeted therapies as it predicts how any given person might react to particular medication. This has tremendous potential for improving the concept of precision medicine, where ‘molecularly targeted treatments’ can be developed based on genetic make-up, medical history and aspects of the environment, thus improving the efficacy of treatment and reducing the effect of side effects.
Knowledge about the significance of human-aware AI in drug discovery is growing among the pharmaceutical companies, and, therefore, significant efforts are being made to enhance the effectiveness of such systems in drug development. The use of artificial intelligence in drug discovery has the potential to quicken and enhance the prediction of patient-specific interactions and thus, faster and more certain identification of potential drugs. Furthermore, human-aware AI systems can greatly enhance clinical trial designs by making corresponding participant selection and dosage recommendations closer to the target population. These are some of the optimized AI models that signify significant growth prospects within the AI-based drug discovery market and therefore propelling more advancement and changing the face of drug development and testing.
Artificial Intelligence in Drug Discovery Market Segmentation:
Artificial Intelligence in Drug Discovery Market By Type
· Target Identification
· Molecule Screening
· De Novo Drug Design and Drug Optimization
· Preclinical and Clinical Testing
Artificial Intelligence in Drug Discovery Market By Therapeutic Area:
· Oncology
· Neurodegenerative Diseases
· Cardiovascular Disease
· Metabolic Diseases
· Infectious Disease
· Others
Artificial Intelligence in Drug Discovery Market By Technology
· Machine Learning
o Deep Learning
o Supervised Learning
o Reinforcement Learning
o Unsupervised Learning
o Other Machine Learning Technologies
· Other Technologies
Artificial Intelligence in Drug Discovery Market By End-User
· Pharmaceutical and Biotechnology Companies
· Contract Research Organizations
· Academics and Research
Artificial Intelligence in Drug Discovery Market By Based on Region:
· North America
· Europe
· Asia-Pacific
· Latin America
· The Middle East & Africa
Artificial Intelligence in Drug Discovery Market Regional Overview:
North America has the highest market share of the Artificial Intelligence (AI) in Drug Discovery market, due to the concentration of key pharmaceutical and biotechnology companies and a strong technology ecosystem. The area is well endowed with research and development funding as producers strive to cut the cost and time taken in the discovery of new drugs. In addition, the need for individualized treatment and increased prevalence of chronic illnesses in North America are fuelling the application of AI solutions. The cooperation between AI solution providers and pharmaceutical firms remains robust, and the industry keeps advancing, which is vital for market expansion.
On the other hand, the Asia-Pacific region is fast becoming the most significant market for AI in drug discovery, especially with China and India. These nations are therefore risking a great deal to tap into the development of AI and biotechnology to meet the growing need for sophisticated health care. The region has a vast number of datasets, and the technology companies’ partnership with pharmaceutical producers is on the rise, so AI is actively developing there. Asian-Pacific governments are also enacting positive policies and funding schemes for the incorporation of AI in drug discovery; hence, positioning the Asia-Pacific market in the global market. Given the increasing availability of AI technology, the ability to make further breakthroughs in drug discovery remains high across the region.
Artificial Intelligence in Drug Discovery Market Companies:
Prominent players in the industry include Atomwise, Inc., Aitia (formerly GNS Healthcare), BenevolentAI, BPGbio, Inc. (acquired Berg Health), Cloud Pharmaceuticals, BioSymetrics, Inc., DeepMind (Google), Exscientia, Insilico Medicine, Inc., IBM, insitro, NVIDIA Corporation, Microsoft Corporation, Schrödinger, and Tempus, Inc.
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