Artificial Intelligence in Drug Discovery Market is expected to register a CAGR of 32.8% over the forecast period.
The COVID-19 pandemic initially had a substantial impact on artificial intelligence in the drug discovery market. With the massive and fast-paced demand for developing novel drugs to treat the symptoms of the novel coronavirus infection and curb its infection, AI held the potential to identify some promising drug candidates, which helped optimize the ligand-based de novo drug design for COVID-19. Some companies deployed AI to accelerate the speed of the COVID-19 drug discovery research. For instance, in 2021, BenevolentAI utilized machine learning to expedite the drug discovery of COVID-19, which discovered barcitinib as a potential drug against COVID-19. In 2022, Insilico Medicine identified a novel preclinical therapeutic drug candidate, a 3CL protease inhibitor, for the treatment of COVID-19 with the use of the generative chemistry AI platform Chemistry42. AI offered better data accessibility, which has helped the researchers utilize a large amount of published data about the virus from the population, such as the infectivity rate of COVID-19.
Furthermore, AI has not only accelerated the speed of screening drug candidates but also underlined the pitfalls of the traditional drug discovery processes. The promising speed and efficacy of AI were helpful for safe, highly efficient, and accelerated drug discovery to curb the infection of COVID-19. During the pandemic and post-pandemic phases, several AI companies, startups, and organizations have received funding for COVID-19 drug discovery. For instance, in May 2022, the National Institutes of Health (NIH), known as the National Institute of Allergy and Infectious Diseases (NIAID), awarded over USD 577 million for the establishment of nine Antiviral Drug Discovery (AViDD) Centers for Pathogens of Pandemic Concern. In July 2021, Exscientia entered a collaboration of nearly USD 70 Million for the discovery and development of small molecule therapeutics against Coronavirus. Thus, the COVID-19 outbreak has positively impacted the market's growth amid the pandemic. Additionally, it is expected to aid the drug discovery process with emerging variants worldwide over the coming years, as per our analysis. The market is expected to grow further at a notable pace with its increasing use in drug discovery for COVID-19 and other related disease areas globally.
Further, the digitization of the clinical drug discovery processes is also driving the growth of the market. The use of big data and the use of AI with stage modeling, selection of leads, and optimization steps in the area of computational biology are helpful in the drug discovery process. The digital approaches have been helpful during the analysis of big data from the domains of pharmacological, chemical, biological, and clinical research. For instance, in November 2022, Monash University of Australia utilized big data, which can be repurposed for use in broader medical applications such as the repurposing of dimethyl fumarate for multiple sclerosis and thalidomide for multiple myeloma. In October 2022, Verge Genomics, a clinical-stage and tech-enabled biotechnology company that utilizes AI for drug discovery purposes announced the first dose of the drug VRG50635 for the management of amyotrophic lateral sclerosis. Such instances are likely to favor the market's growth.
In addition, several drug manufacturers have collaborated with AI companies to expedite their drug discovery programs. For instance, in January 2022, Sanofi and Exscientia signed a research collaboration and license agreement for the discovery and development program for four types of cancer (non-small cell lung cancer, triple-negative breast cancer, mesothelioma, and multiple myeloma) using the AI-driven platform of Exscientia. In November 2022, AI company, CytoReason expanded its multi-year partnership with Pfizer to utilize its AI technology for drug discovery and development.
Therefore, owing to the aforementioned factors, it is anticipated that the studied market will witness growth over the analysis period. However, the high cost and the errors associated with the management of the data and its standardization are likely to impede the market growth.
AI expedites the drug discovery of anti-cancer drugs with machine learning and deep learning algorithms. Deep learning is highly flexible in the design of de novo molecular structures of the drug candidates and the prediction of their reactions. According to a study published in the journal Nature in 2022, AI is helpful in the effective identification of novel drugs and anti-cancer targets from biological networks. The biological networks effectively preserve and evaluate the interaction between the components of the cancer cells. This includes cellular network modeling, which helps to quantify the framework that connects the network properties and cancer through AI biology analysis. This helps to discover potential novel anti-cancer drugs and targets.
In addition, some market players have utilized AI in the drug discovery process for cancer. For instance, in October 2022, Model Medicines, a pharma-tech company, launched its Oncology Program, which is focused on drug discovery and development of anti-cancer drugs that target AXL and BRD4. Further, in June 2022, Schrödinger, Inc. received clearance from the USFDA for its investigational new drug application for SGR-1505, a MALT1 inhibitor. The company uses a physics-based software platform for drug discovery purposes. With the active research and clinical studies of anti-cancer drug discoveries using AI and the key developments of market players and pharmaceutical companies, the oncology segment is expected to witness significant growth over the forecast period.
Key developments and the high concentration of market players in the United States are some of the other factors driving the growth of artificial intelligence in the drug discovery market in the region. For instance, in November 2021, Alphabet, the parent company of Google, launched its first drug discovery company, ISOMORPHIC LABORATORIES. Further, in September 2022, Microsoft signed a collaboration agreement with Novo Nordisk. Under the agreement, Microsoft would provide its AI, computational, and cloud services to the data science analysis, drug discovery, and development activities of Novo Nordisk. Also, in August 2022, Johnson & Johnson's unit, Janssen, announced a collaboration with SRI International to use SRI's SynFini AI platform for the discovery of small molecule drugs. Thus, these continuous developments in the region are anticipated to drive the growth of the market.
Therefore, owing to the increasing use of AI in drug discovery by academics, research, and healthcare institutions, the companies and their key developments are expected to boost the growth of the studied market in the North American Region.
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The COVID-19 pandemic initially had a substantial impact on artificial intelligence in the drug discovery market. With the massive and fast-paced demand for developing novel drugs to treat the symptoms of the novel coronavirus infection and curb its infection, AI held the potential to identify some promising drug candidates, which helped optimize the ligand-based de novo drug design for COVID-19. Some companies deployed AI to accelerate the speed of the COVID-19 drug discovery research. For instance, in 2021, BenevolentAI utilized machine learning to expedite the drug discovery of COVID-19, which discovered barcitinib as a potential drug against COVID-19. In 2022, Insilico Medicine identified a novel preclinical therapeutic drug candidate, a 3CL protease inhibitor, for the treatment of COVID-19 with the use of the generative chemistry AI platform Chemistry42. AI offered better data accessibility, which has helped the researchers utilize a large amount of published data about the virus from the population, such as the infectivity rate of COVID-19.
Furthermore, AI has not only accelerated the speed of screening drug candidates but also underlined the pitfalls of the traditional drug discovery processes. The promising speed and efficacy of AI were helpful for safe, highly efficient, and accelerated drug discovery to curb the infection of COVID-19. During the pandemic and post-pandemic phases, several AI companies, startups, and organizations have received funding for COVID-19 drug discovery. For instance, in May 2022, the National Institutes of Health (NIH), known as the National Institute of Allergy and Infectious Diseases (NIAID), awarded over USD 577 million for the establishment of nine Antiviral Drug Discovery (AViDD) Centers for Pathogens of Pandemic Concern. In July 2021, Exscientia entered a collaboration of nearly USD 70 Million for the discovery and development of small molecule therapeutics against Coronavirus. Thus, the COVID-19 outbreak has positively impacted the market's growth amid the pandemic. Additionally, it is expected to aid the drug discovery process with emerging variants worldwide over the coming years, as per our analysis. The market is expected to grow further at a notable pace with its increasing use in drug discovery for COVID-19 and other related disease areas globally.
Further, the digitization of the clinical drug discovery processes is also driving the growth of the market. The use of big data and the use of AI with stage modeling, selection of leads, and optimization steps in the area of computational biology are helpful in the drug discovery process. The digital approaches have been helpful during the analysis of big data from the domains of pharmacological, chemical, biological, and clinical research. For instance, in November 2022, Monash University of Australia utilized big data, which can be repurposed for use in broader medical applications such as the repurposing of dimethyl fumarate for multiple sclerosis and thalidomide for multiple myeloma. In October 2022, Verge Genomics, a clinical-stage and tech-enabled biotechnology company that utilizes AI for drug discovery purposes announced the first dose of the drug VRG50635 for the management of amyotrophic lateral sclerosis. Such instances are likely to favor the market's growth.
In addition, several drug manufacturers have collaborated with AI companies to expedite their drug discovery programs. For instance, in January 2022, Sanofi and Exscientia signed a research collaboration and license agreement for the discovery and development program for four types of cancer (non-small cell lung cancer, triple-negative breast cancer, mesothelioma, and multiple myeloma) using the AI-driven platform of Exscientia. In November 2022, AI company, CytoReason expanded its multi-year partnership with Pfizer to utilize its AI technology for drug discovery and development.
Therefore, owing to the aforementioned factors, it is anticipated that the studied market will witness growth over the analysis period. However, the high cost and the errors associated with the management of the data and its standardization are likely to impede the market growth.
Artificial Intelligence in Drug Discovery Market Trends
The Oncology Segment is Expected to Witness Significant Growth Over the Forecast Period
In oncology drug discovery, AI accelerates the discovery of anti-cancer drugs. With the incidence of cancer on the rise, the segment is expected to witness growth in the near future. According to the American Cancer Society 2022, cancer is the second-leading cause of death in the United States. It was estimated that over 609,360 deaths and 1.9 million new cancer cases are expected by the end of 2022.AI expedites the drug discovery of anti-cancer drugs with machine learning and deep learning algorithms. Deep learning is highly flexible in the design of de novo molecular structures of the drug candidates and the prediction of their reactions. According to a study published in the journal Nature in 2022, AI is helpful in the effective identification of novel drugs and anti-cancer targets from biological networks. The biological networks effectively preserve and evaluate the interaction between the components of the cancer cells. This includes cellular network modeling, which helps to quantify the framework that connects the network properties and cancer through AI biology analysis. This helps to discover potential novel anti-cancer drugs and targets.
In addition, some market players have utilized AI in the drug discovery process for cancer. For instance, in October 2022, Model Medicines, a pharma-tech company, launched its Oncology Program, which is focused on drug discovery and development of anti-cancer drugs that target AXL and BRD4. Further, in June 2022, Schrödinger, Inc. received clearance from the USFDA for its investigational new drug application for SGR-1505, a MALT1 inhibitor. The company uses a physics-based software platform for drug discovery purposes. With the active research and clinical studies of anti-cancer drug discoveries using AI and the key developments of market players and pharmaceutical companies, the oncology segment is expected to witness significant growth over the forecast period.
North America is Expected to Dominate the Artificial Intelligence in Drug Discovery Market
North America is expected to dominate the market owing to factors such as the high adoption of AI technologies in pharmaceuticals, a large patient pool, a higher prevalence of chronic and infectious diseases, advanced healthcare infrastructure, and highly active clinical research and trials of AI and drug discovery in the region. The United States has a high prevalence of metabolic and lifestyle diseases. According to the CDC, in 2022, more than 130 million adults in the United States will be living with diabetes. As per the National Institutes of Health, 1 in every seven adults in the United States is affected by chronic kidney disease. Various research and academic institutes are integrating AI into drug discovery studies, including the University of Texas MD Anderson Cancer Center, the University of Alabama in Huntsville, the University of Oxford, and the University of Dundee, among others.Key developments and the high concentration of market players in the United States are some of the other factors driving the growth of artificial intelligence in the drug discovery market in the region. For instance, in November 2021, Alphabet, the parent company of Google, launched its first drug discovery company, ISOMORPHIC LABORATORIES. Further, in September 2022, Microsoft signed a collaboration agreement with Novo Nordisk. Under the agreement, Microsoft would provide its AI, computational, and cloud services to the data science analysis, drug discovery, and development activities of Novo Nordisk. Also, in August 2022, Johnson & Johnson's unit, Janssen, announced a collaboration with SRI International to use SRI's SynFini AI platform for the discovery of small molecule drugs. Thus, these continuous developments in the region are anticipated to drive the growth of the market.
Therefore, owing to the increasing use of AI in drug discovery by academics, research, and healthcare institutions, the companies and their key developments are expected to boost the growth of the studied market in the North American Region.
Artificial Intelligence in Drug Discovery Market Competitor Analysis
The artificial intelligence in the drug discovery market is moderately consolidated in nature due to the presence of a few companies operating globally as well as regionally. The competitive landscape includes an analysis of some international as well as local companies that hold market shares and are well known, including Microsoft, IBM, Exscientia, GNS Healthcare, Alphabet, Benevolent AI, Cloud, NVIDIA Corporation, DEEP GENOMICS, Neumora, Recursion, Notable, Insilico Medicine, and PathAI.Additional benefits of purchasing the report:
- The market estimate (ME) sheet in Excel format
- 3 months of analyst support
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Table of Contents
1 INTRODUCTION
4 MARKET DYNAMICS
5 MARKET SEGMENTATION (Market Size by Value - USD million)
6 COMPETITIVE LANDSCAPE
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Microsoft
- IBM
- Exscientia
- GNS Healthcare
- Alphabet
- Benevolent AI
- Cloud
- NVIDIA Corporation
- DEEP GENOMICS
- Neumora
- Recursion
- Notable
- Insilico Medicine
- PathAI
Methodology
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