Pune, Nov. 28, 2022 (GLOBE NEWSWIRE) -- The Global Artificial Intelligence (AI) in Drug Discovery Market reach USD 1.01 Billion in 2022 and is expected to exhibit a CAGR of 28.34% over the forecast period 2023 to 2032, according to a recent global market study by Quince Market Insights.
Computer-assisted drug development is made possible by artificial intelligence (AI). This development is being facilitated by the extensive use of machine learning, particularly deep learning, in a variety of scientific domains as well as improvements in computing hardware and software. Machine intelligence is used to distinguish artificial intelligence from natural intelligence generated by animals like humans (AI). AI is the study of "intelligent agents," or systems, that are able to comprehend their environment and take choices that increase their chances of success. The many applications of AI technology are based on varied objectives and the use of certain methods.
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A branch of computer science called artificial intelligence focuses on modelling intelligent behaviour. It enables machines to think and do various tasks, such as those performed by people and animals, while learning from their errors. Usually, an algorithm used in artificial intelligence enables computers to carry out tasks accurately and with few mistakes. It uses deep learning and machine learning techniques to personify information while carrying out a range of tasks.
The ability of artificial intelligence to identify diseases, provide treatments for them, and predict which animal viruses will emerge has significant implications for drug research. Artificial intelligence has been found to enhance research and development (R&D) in the discovery of medications, aiding scientists in the identification of remedies for chronic diseases. Discovering a biological target, such as an enzyme, protein, gene, or receptor, is the first step in the process of developing a medication. This process is used in medicine, pharmacology, and biotechnology. In the past, drugs were discovered by locating the active component in conventional therapies. Thus, the process of discovering new drugs and their therapeutic uses begins with drug discovery. Bioavailability, efficacy, potency, and safety are required for new drugs.
The supercomputer built by International Business Machines (IBM) named Watson is an illustration of an AI-based tool (IBM, New York, USA). Its goal was to support the study of a patient's medical information and its comparison with a sizable database, leading to recommendations for cancer treatment strategies. This method could enable quick illness detection. It is simple to imagine AI being involved in the development of a pharmaceutical product from the bench to the bedside given that AI can help with rational drug design, decision-making, determining the best therapy for a patient, including personalised medicines, and managing clinical data for future drug development.
The healthcare sector has made extensive use of artificial intelligence, notably in the search for novel drugs. This aids in the quicker identification, production, detection, and screening of tiny molecules as well as the identification of medicinal targets. The market is expected to grow exponentially throughout the projected period as a result of the benefits of using these contemporary methods rather than outdated ones. Additionally, a surge in industrial alliances and partnerships is the main factor driving the market. Additionally, artificial intelligence reduces the time and money needed for medication development, which helps the market expand. However, in the field of drug discovery, a lack of knowledgeable people and data sources is restricting industry growth.
Impact of COVID-19
The COVID-19 pandemic is anticipated to have a substantial positive impact on the artificial intelligence for drug research and development industry, resulting to a rise in the use of AI to find and create new drugs for COVID-19 therapy. Repurpose, as an example, in June 2020. AI and Scripps Research collaborated to develop COVID-19 medications, placing a focus on medicinal repurposing. Theoretically, AI-based drug screening methods will assist in elucidating important components of the virus (such as protein structure) in order to ascertain how the virus's functions might speed up vaccination technologies and play a significant part in medication formulation to battle COVID-19.
Furthermore, by quickly identifying drugs with COVID-19 effectiveness, artificial intelligence can quicken the drug research and development process. By repurposing existing pharmaceuticals to treat a variety of illnesses, this fills the gap between the quantity of repurposed medications, clinical testing, and the final drug approval process.
Finding a good therapy for COVID-19 individuals, however, may prove advantageous in a number of ways. A group of researchers from the University of Michigan found over 17 active drugs to reduce coronavirus infection in cells using an AI-powered image. Such technologies and methods help determine how well current pharmaceuticals work against COVID-19, which helps the market for artificial intelligence in drug discovery grow.
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Market Segmentation
Artificial Intelligence (AI) in Drug Discovery, By Component
Software
The whole AI industry must include platforms based on machine learning and deep learning technologies. The artificial intelligence in drug discovery market is dominated by the software sector. Google AI and Microsoft Azure are two of the most well-known AI platforms available today. But an increasing number of modest businesses are developing AI platforms, driving the industry for artificial intelligence in drug research ahead at an exponential rate.
Service
The services area includes AI integration, deployment, and upgrading. In addition to providing a platform, numerous companies, such as BenevolentAI and DeepMatter, frequently communicate with pharmaceutical companies (such as AstraZeneca) to offer their services to enhance drug development outcomes.
Artificial Intelligence (AI) in Drug Discovery, By Technology: -
- Machine learning
With lots of high-quality data and machine learning (ML) methods, decision-making on certain subjects may be improved. It is the study of computer algorithms that, given enough time and data, may learn and grow on their own. Considered to be a component of artificial intelligence. In many fields where, conventional algorithms are difficult to develop or are not feasible, such as medicine, email filtering, speech recognition, and computer vision, machine learning algorithms are applied. Utilizing ML can improve data-driven decision making, which might speed up and lower failure rates in the drug research and development process. The share of this group is anticipated to be higher.
- Deep Learning
Models that use deep learning (DL) to explain geometric alterations over several layers. Deep learning technology uses neural "networks," which are logical structures similar to the brain, to recognise and distinguish patterns such as speech, picture, and video. The field of drug development has seen tremendous promise from deep learning. It is anticipated that the market for AI drug discovery would have the quickest growth throughout the assessment period.
Artificial Intelligence (AI) in Drug Discovery, By Application: -
Another significant use of AI integration in drug research is the treatment of neurodegenerative illnesses. There is presently no cure for the severe neurological condition known as amyotrophic lateral sclerosis (ALS). An AI and machine learning start-up called BenevolentAI is currently looking at possible treatments for amyotrophic lateral sclerosis (ALS). Neurodegenerative diseases are the market's fastest-growing application segment. The category has grown quickly due to AI's ability to create therapies for complex conditions and market participants' focus on providing AI-based platforms for neurological diseases.
According to predictions, the market for artificial intelligence in drug development would be dominated by the immuno-oncology sector. Precision medicine can now discriminate between different genetic variations thanks to AI technologies. By researching and identifying genetic variations, oncologists can more effectively treat their patients. The use of AI in the creation of cancer drugs holds great potential, and an increasing number of businesses are starting to do so. For instance, Novartis is working with Microsoft's AI platform to develop new medications for the fatal illness.
A notable example of emerging cancer breakthroughs is Paige's, a company that develops AI diagnosis technologies. The business helps pathologists identify cancer accurately using images of tissue samples by applying machine learning. Such improvements are anticipated to accelerate the expansion of AI in pharmaceutical
Artificial Intelligence (AI) in Drug Discovery, By End User: -
The biggest winners will be the pharmaceutical and biotechnology industries from AI integration in drug research. Pharma innovators may significantly increase the effectiveness and speed of their drug discovery process by implementing AI. The drug and biotechnology industries, contract research organisations, research centres, university and government organisations, and research centres make up the market for AI in drug disclosure. Pharmaceutical and biotechnology companies are anticipated to hold the largest market share in the market for artificial intelligence in drug discovery throughout the assessment period.
It is anticipated that the contract research organisation sector would be the second-largest in the market for artificial intelligence in drug discovery. It is anticipated that integrating AI would drastically reduce the costs associated with drug discovery and development, helping both service providers and creators.
Artificial Intelligence (AI) in Drug Discovery, By Region
The greatest revenue share in the worldwide Al in drug discovery market is predicted to come from North America. This can be linked to the vast patient population suffering from a variety of illnesses, such as cancer and neurological problems, which in turn raises the need for different medications with low side effects. Additionally, the region's strong emphasis on clinical research and the presence of important companies from the pharmaceutical and technology industries are promoting the expansion of the North American market for al in-drug discovery.
The rising incidence of various ailments in the area is one of the major determinants of the growth of the North American Al drug discovery market. For instance, the dramatic rise in cancer prevalence in the United States is one of the primary causes of the increasing demand for pharmaceuticals. An estimated 1.9 million additional instances of cancer will be identified in the United States in 2021, according to figures published by the American Cancer Society.
A total of 1,708,921 new cases of cancer were recorded in 2018, according to the Centers for Disease Control and Prevention (2021).
For instance, the American Cancer Society predicts that in 2022, there will be 287,850 new instances of invasive breast cancer in women in the United States. Therefore, it is anticipated that the country's rising prevalence of cancer, including breast cancer along with other forms of cancer, would further increase the need for Al in the development of new drugs. The National Cancer Institute (NCI), The Cancer Moonshoot, and the Department of Energy (DOE) are supporting two major partnerships to take advantage of the same by identifying and interpreting the characteristics of target molecules that promote cancer development, and the second initiative is the RAS initiative to study the interaction of the KRAS protein with other molecules.
Recent Developments in the Global Artificial Intelligence (AI) in Drug Discovery Market
- In January 2022, Sanofi and Exscientia, a start-up that utilises artificial intelligence to find novel medication ideas, engaged into a research partnership that may be valued up to US$5.2 billion to Exscientia.
- Insilico Medicine announced the beginning of the first Phase I clinical trial of a medicine created from scratch utilising Al in December 2021. Al is used in biology for target identification and in chemistry for drug creation on its end-to-end platform. Idiopathic pulmonary fibrosis is being treated with the medication developed for Al, a small molecule inhibitor.
- In November 2021, Alphabet Inc. announced the founding of a new business, Isomorphic Laboratories, which would utilise aluminium in the search for novel drugs.
- 2021 November A physics-ML model generation system called NVIDIA Modulus was created to assist a variety of sectors with high demands for AI and physics but low AI expertise.
- Genesis Therapeutics (US) and Genentech (US) entered into a multi-target drug development partnership in October 2020. The collaboration will make use of Genesis' graphical machine learning capabilities to find therapeutic candidates for a variety of illnesses.
- Sep 13, 2021 RXN for Chemistry was developed by IBM Research. IBM Research and Arctoris study how automation and artificial intelligence may speed up closed-loop chemical discovery.
- Chief.AI, a machine learning platform that is operational, announced the introduction of a continuous artificial intelligence platform for drug development in July 2021.
- Chief.AI, the working stage of artificial intelligence, has said that it would only provide a larger compensation when the expenses of the Artificial Intelligence Stage for the enhancement of medicines are incurred in July 2021. This stage minimises the need for interventions by giving small and medium-sized businesses appropriate access to cutting-edge technology. the hit-or-miss nature of medical advancements and precisely and swiftly identifying game-changing medications.
- MegaMoIBART, a novel drug development paradigm centred on "response prediction, molecular optimization, and de novo drug discovery," was revealed by NVIDIA and AstraZeneca in April 2021.
- Iktos (France) and Pfizer (USA) worked together in March 2021 to apply Iktos' de novo AI-driven design tools to a number of Pfizer small molecule initiatives.
What Does This Report Provide?
This report provides a detailed understanding of the global Artificial Intelligence (AI) in Drug Discovery market from qualitative and quantitative perspectives during the forecast period. The major market drivers, challenges, and opportunities for the global Artificial Intelligence (AI) in Drug Discovery market have been covered in the report.
Major Companies: In this report, the major companies studied are IBM Corporation (US), Microsoft (US), Google (US), NVIDIA Corporation (US), Atomwise, Inc. (US), Deep Genomics (Canada), Cloud Pharmaceuticals (US), Insilico Medicine (US), Benevolent AI (UK), Exscientia (UK), Cyclica (Canada), BIOAGE (US), Numerate (US), Numedii (US), Envisagenics (US), twoXAR (US), OWKIN, Inc. (US), XtalPi (US), Verge Genomics (US), and Berg LLC (US)
Market Segmentation:
Objectives of this Report:
- On a regional and worldwide scale, estimate the market size for Artificial Intelligence (AI) in Drug Discovery market.
- To provide a competitive scenario for the Artificial Intelligence (AI) in Drug Discovery market with major developments observed by the key companies in the historic years.
- To evaluate key factors governing the dynamics of Artificial Intelligence (AI) in Drug Discovery market with their potential growth during the forecast period.
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Quince Market Insights
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