The global artificial intelligence for drug discovery and development market size was valued at USD 710 million in 2021 and is estimated to reach an expected value of USD 8520 million by 2030, registering a CAGR of 31.8% during the forecast period (2022 – 2030).AI is the science and engineering adopted to generate intelligent machines, particularly intelligent computer programs. Artificial intelligence (AI) refers to a smart system that connects various human intelligence-based functions, such as reasoning, learning, and problem-solving abilities, to multiple fields, including biology, computer science, psychology, mathematics, linguistics, and engineering. AI is useful in the healthcare sector for managing medications, creating treatment programs, finding new drugs, and more.
Discovering new drugs and developing them involves several steps and phases that cost a lot of money. Additionally, getting the drug approved for use in the market and undergoing clinical trials may be challenging. The main factor driving this industry is an increase in the number of partnerships between AI providers and pharmaceutical and biotech firms. A significant factor affecting the market growth is how much time and money artificial intelligence saves during medication discovery and development. The demand for cloud-based software that helps researchers swiftly and accurately create pharmaceuticals is anticipated to fuel market expansion. Additionally, the life science research and development industry is becoming more innovative, efficient in terms of time and money, and cost-effective with the integration of artificial intelligence (AI) and machine learning technologies.
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Growing Number of Cross Industry Collaborations and Partnerships
Artificial intelligence is among the crucial technologies, with pharmaceutical and healthcare being the most affected industries. Many healthcare industries looking for new technologies collaborated with IT industries that offer artificial intelligence for drug discovery. IT companies use their technology to accelerate drug discovery and design by using a proprietary AI-driven process to deliver novel molecules tailored to a drug target's characteristics. For instance, in June 2018, GlaxoSmithKline (GSK) is set to apply artificial intelligence (AI) technology to improve its drug discovery efforts through collaboration with Cloud Pharmaceuticals.
Moreover, in 2018, Pfizer and IBM announced a partnership to accelerate drug discovery in immuno-oncology. There is a healthy spread of such partnerships covering several research areas, such as identifying novel small molecules, discovering new treatment methods, monitoring health data through wearable technologies, etc. These developments are forecasted to contribute to advancing healthcare services, efficiency in clinical trials, and others. For instance, increasing investment by major players in biopharma companies and a rise in public and private partnerships for R&D activities with IT industries are the factors that are expected to boost the growth of the market.
Reduced Cost and Time Utilized in the Drug Discovery& Development Process.
Major Pharma and biotech companies are adopting digital transformation. They use advanced artificial intelligence in drug discovery, R&D, clinical trials, preclinical trials, sales & marketing, regulatory compliance, supply chain analytics, and pharmacy vigilance to achieve operational excellence and better outcomes. Artificial intelligence is attracting attention as an advanced technology that can intensely reduce the high cost and time required for new drug discovery. According to Biomedical Journal, in 2016, traditional drug discovery involves an average of more than ten years, and $2.6 billion are required to develop one new drug. For instance, artificial intelligence is mainly used in the early stage of drug discovery and search for candidate compounds in the pharmaceutical industry; however, AI will be used for various purposes to drastically reduce the cost and time for new drug discovery, therefore, reduction in the time factor, which helps to boost the market growth.
Shortage of Data Sets in the Field of Drug Discovery
Advancements in artificial intelligence are modernizing several aspects of drug discovery. Avoiding past problems in drug development like analysis of large datasets, protracted screening of compounds while reducing standard error, requiring large amounts of R&D cost of over $2.5 billion, and longer time of more than a decade are now possible using artificial intelligence methods. Artificial intelligence requires a large amount of specific data sets to complete its procedure for drug discovery. Datasets are integral to machine learning, but finding a suitable dataset for machine learning and data science projects is sometimes quite challenging. Some organizations, researchers, and individuals who have shared their work and professionals can use their datasets to build their projects. However, these data sets are not enough for drug discovery as it needs more specific data sets to build a primary model for drug discovery. Thus, insufficient data in drug discovery impedes the market growth.
Increase in Awareness Related to Artificial Intelligence
The pharmaceutical sector is struggling to reduce the high rates of drug development attrition. Pharmaceutical industries are collaborating with AI industries to overcome challenges. Artificial intelligence improves the efficiency of the drug development process. Artificial intelligence has been recognized to have enormous applications in drug discovery as it helps to analyze outbreaks, develop cures for diseases, and predict which animal viruses tend to mutate. Artificial intelligence has improved research and development in drug discovery, allowing researchers to discover drugs for diseases.
In addition, big data can improve different components such as clinical trial design, drug discovery, and detection of adverse drug reactions. Hence, artificial intelligence can be a better solution to enhance and accelerate drug development.
The global artificial intelligence for drug discovery and development market is segmented by type, indication, end user, and region.
By type, the global artificial intelligence for drug discovery and development market is divided into target identification, molecules screening, de novo drug design &drug optimization, and preclinical &clinical testing. The preclinical and clinical testing segment was the highest contributor to the market and is estimated to grow at a CAGR of 32.6% during the forecast period. In the past few years, the number of artificial intelligence companies focused on discovering new drugs using innovative approaches to preclinical& clinical testing has increased rapidly. Animal models often resist predicting the human physiology response accurately. A lack of good preclinical modeling is a significant reason for low R&D returns. Although a body of research focuses on finding better predictive preclinical technologies, such as organs-on-a-chip or 3D cell cultures, AI algorithms might help identify which animal models could be more accurate for certain diseases. A new statistical technique called 'Found in Translation' uses ML (machine learning) algorithms to identify matches in gene expression profiles between mice and humans and better predict cross-species differences.
The molecules screening segment is the second largest. The market is expanding primarily due to an increase in the number of leadership development agreements between pharmaceutical companies and AI providers. For instance, in 2019, Atomwise Inc. collaborated with Enamine Ltd., the world's largest chemical supplier, to launch a 10 billion compound AI-powered virtual drug screening initiative. Through this project, safer small molecule medications to treat pediatric tumors are expected to be discovered significantly more frequently. Furthermore, in 2019, Janssen Pharmaceutical initiated a collaboration agreement to use Iktos' artificial intelligence (AI) technology to accelerate small molecule drug discovery. Under the collaboration, Janssen will implement Iktos' virtual design technology for several of its projects.
Based on indication, the global artificial intelligence for drug discovery and development market is classified into oncology, infectious disease, neurology, and others. The oncology segment was the highest contributor to the market and is estimated to grow at a CAGR of 32.8% during the forecast period. Oncology is the study of cancer. It includes medical oncology (use of chemotherapy, hormone therapy, and cancer treatment), radiation oncology (use of radiation therapy to treat cancer), and surgical oncology (use of surgery and other cancer treatment procedures). It is anticipated that this segment will show significant market growth during the forecast period as a result of the rising adoption of AI to find drugs for treating several kinds of cancer, broad categories of promising drugs in the pipeline, a higher number of unmet needs for treating cancer, and rising collaboration rates between industry players.
By end user, the global artificial intelligence for drug discovery and development market is segmented into pharmaceutical & biotechnology companies and CROs. The pharmaceutical and biotechnology companies segment was the highest contributor to the market and is estimated to grow at a CAGR of 31.5% during the forecast period. Pharmaceutical &biotechnology companies use various AI systems for genome editing, chemical genomics, combinational drug screening, lead optimization, ADMET studies, and in clinical& preclinical trial studies. AI systems in the drug discovery industry reduce manual work, provide accurate results and increase the speed of the drug discovery process. Such factors drive segment growth.
Region-wise, the global artificial intelligence for drug discovery and development market is analyzed across Europe, Asia-Pacific, North America, and LAMEA.
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North America dominated the global artificial intelligence for drug discovery and development and is estimated to grow at a CAGR of 30.8%. The surge in demand for precision medicine developed healthcare infrastructure and a large number of Cross-industry collaborations are mainly driving the market growth in North America. In addition, an upsurge in adopting advanced drug discovery technologies and a higher number of R&D activities fuels the market growth in North America. An increase in collaborations among the companies is expected to boost the market growth in the North American market. In addition, increasing government initiatives to reduce overall healthcare costs and enhance the quality of healthcare services are further influencing the market growth in North America.
Europe is the second largest region. It is anticipated to reach a predicted value of USD 3200 million by 2030, registering a CAGR of 32.4%. An increase in the number of acquisitions of small startup artificial intelligence companies in the region due to the advancement of algorithms is expected to drive market growth in Europe. For instance, Google acquired a UK-based artificial intelligence startup called DeepMind in 2014. An increase in investment for advancement in artificial intelligence in Europe is expected to boost the market growth. In addition, the government is providing significant support for advancing the use of artificial intelligence in drug discovery further supports market growth.
Moreover, various pharmaceutical companies and AI companies in Europe are collaborating to further support Europe's market growth. For instance, in April 2019, UK-based company Benevolent teamed with AstraZeneca to use artificial intelligence and machine learning to discover and develop new treatments for chronic kidney disease (CKD) and idiopathic pulmonary fibrosis (IPF). Moreover, in January 2020, Bayer entered into a collaboration agreement with artificial intelligence drug discovery company Exscientiato to identify and optimize novel lead structures for potential drug candidates in treating cardiovascular and oncological diseases.
Asia-Pacific is the third largest. The market growth in Asia-Pacific is attributed to the change in several government initiatives to improve the healthcare sector and the increase in investments in foreign companies, primarily U.S-based companies, which is expected to drive the market growth. For instance, Data analytics startup Elucidate, an India and U.S.-based data science startup, has raised $1.7 million in seed funding led by Hyperplane Venture Capital; the company is mainly focused on developing tools and software solutions for drug discovery. Moreover, the rise in significant R&D investments, improvement of healthcare infrastructure, and the presence of artificial intelligence provider companies such as iCarbon X, WuXi NextCODE, Huawei, Tencent, Elucidate Corporation, and others further drives the market growth in Asia-Pacific. Furthermore, many companies are IT companies collaborating with pharmaceutical companies in the Asia-Pacific region, which is projected to fuel the market growth, owing to significant advantages of using artificial intelligence, such as enhanced clinical trials and improved efficiency in drug discovery. For instance, in October 2019, Insilico signed a $200 million artificial intelligence drug discovery partnership with China's CTFH (Chia Tai Fengtai Pharmaceutical), mainly focused on targets in triple-negative breast cancer. An increase in investment for advancement in artificial intelligence is expected to drive the growth of the Asia-Pacific artificial intelligence in drug discovery.
List of key artificial intelligence for drug discovery and development market companies profiled