AI in Drug Discovery Market: Segmentation

AI in Drug Discovery Market (Offering: Software and Services; Application: Oncology, Infectious Diseases, Neurological Disorders, Rare Diseases, Metabolic Diseases, Cardiovascular Diseases, and Others; Technology: Machine Learning and Other Technologies; Drug Type: Small Molecules and Large Molecules; and End User: pharmaceutical & biotechnology companies, contract research organizations, academics & research, and others)   

REPORT PREVIEW

As many nations fight to contain the deadly virus, rapid drug discovery for COVID-19 could be very helpful. Lockdowns and strong limits on people's freedom of movement have had a negative effect, leading to significant losses for businesses in the AI in drug discovery sector. However, it could be beneficial in many ways if the right treatment is discovered for COVID-19 sufferers. Over 17 known medications to lessen corona virus infection in cells have been identified by a University of Michigan research team using an AI-powered picture. Such strategies and tactics ultimately contribute to the expansion of the AI in drug discovery industry by revealing the effectiveness of currently available medications against COVID-19.    

With a compound annual growth rate (CAGR) of XX% from 2024 to 2033, the global artificial intelligence (AI) in drug discovery market was valued at US$ XX billion in 2023 and is projected to reach US$ XX billion by 2033. AI solutions are being adopted by the pharmaceutical and healthcare industries more frequently in an effort to reduce the considerable financial burdens and potential drawbacks that come with using traditional virtual screening (VS) approaches. Drug development and discovery have been transformed by AI, which makes it possible for scientists to more accurately forecast a drug's bioactivity. Artificial Intelligence (AI) improves the precision and speed of bioactivity predictions for a range of chemicals by utilising cutting-edge techniques like molecular docking and quantitative structure-activity relationship (QSAR) modelling. The artificial intelligence (AI) in drug discovery market is growing significantly due to this technical breakthrough, providing a more cost-effective and reliable approach to drug development.

Market Overview
Artificial intelligence (AI) is transforming drug development at many stages of the pipeline, including computational approaches like de novo design and property prediction. This is the primary driver of AI's explosive expansion in the market. Drug discovery applications and drug response analysis are greatly improved by modern AI techniques like graph neural networks, reinforcement learning, and generative models combined with structure-based techniques like molecular docking and molecular dynamics simulations. AI-based software tools and open-source databases make it easier to create drugs and address issues with molecular representation, complexity, data collecting, labelling, and label discrepancies. These data-driven approaches have enormous potential benefits for the digitisation of medical records, clinical trials, precision medicine, drug discovery, and health policy. Drug discovery has undergone a drastic transformation because to new analytical techniques and computational advancements. Recent developments have sparked a great deal of interest in the use of AI in these fields to enhance de novo molecular design, optimisation, structure-based drug design, and pre-clinical and clinical development.

•    In December 2023, Merck launched the first-ever AI solution to integrate drug discovery and synthesis. 
•    In December 2023, MilliporeSigma also launched the first-ever AI solution to integrate drug discovery and synthesis.     

The Need for AI in Drug Discovery is Driven by the Rise in Chronic Diseases

The number of individuals suffering from chronic illnesses is on the rise worldwide. The Centers for Disease Control and Prevention report that 60% of American adults have at least one chronic condition, and 40% have two or more. Additionally, the CDC states that chronic diseases such as heart disease and diabetes are the primary causes of death in the United States. These figures emphasize the growing prevalence of chronic diseases and the need to decrease the mortality rate associated with them

Artificial Intelligence (AI) based tools used in the field of drug discovery can provide valuable insights that can aid in the development of treatments for chronic illnesses. As a result, the market for AI in drug discovery is expected to experience significant growth from 2021-2031.                        

Significant Influence of Oncology on Market Expansion

The use of Artificial Intelligence (AI) in oncology is expected to provide significant growth opportunities. AI can assist in understanding the mechanism of drug resistance in cancer cells and aid in the development of new drugs and strategies for drug use. Machine learning, a type of AI technology, can accelerate current research in the field of anticancer drugs. One example of this is Paige's, an AI diagnostic technology start-up, which uses machine learning to aid pathologists in making accurate cancer diagnoses by analyzing tissue samples. These advancements are likely to drive the growth of the AI in drug discovery market

Rising Adoption of Mindful AI to Present Breakthrough Opportunities

Mindful AI, a human-centered and responsible approach to developing drugs, is quickly gaining popularity as an ideal solution in the pharmaceutical industry. Mindful AI is a method of creating AI-based technologies that take into account the intended use of the technology. By using Mindful AI, pharmaceutical companies can not only speed up drug development but also ensure that the drugs are effective for a wide range of patients. As a result, the increasing adoption of Mindful AI in the pharmaceutical industry is expected to provide significant growth opportunities, driving the overall AI in drug discovery market

Advancements in Treatment of Neurological Diseases to Open Profitable Avenues

The advancements in the treatment of neurological diseases are expected to create profitable opportunities in the AI in drug discovery market. The use of AI in treating neurological disorders could offer a wide range of growth opportunities. Pharmaceutical companies are collaborating to explore new solutions for neurological diseases. For example, PharmEnable, a U.K.-based drug discovery company, and Sosei, a Japan-based firm, are working together to use Sosei's Heprares CPCR-focused drug design platform and PharmEnable's AI technologies to discover new drug leads. These developments are expected to contribute to the substantial growth of the AI in drug discovery market

Consultant point of view  

According to analysts, the AI in drug discovery market is projected to grow at a CAGR of 36.1% during the forecast period of 2021-2031, crossing US$10.93 billion by 2031. The increasing cases of chronic diseases, particularly cardiovascular disorders and diabetes, are driving the need for AI in drug discovery platforms. In addition, the use of AI in treating neurological disorders will further increase the growth rate. Companies in the AI in drug discovery market should focus on using Mindful AI to design and develop effective drug discovery platforms, and the advancements made by AI in finding related to COVID-19 are also expected to witness significant growth

AI in Drug Discovery Market: Overview

In recent years, Artificial Intelligence (AI) has become a topic of interest among medical technology professionals, with various companies and research labs working to refine these technologies for clinical use. The first commercial examples of how AI, also known as deep learning, machine learning, or artificial neural networks, can assist clinicians are now available. These systems have the potential to transform the way clinicians work, improve productivity, and enhance the quality of treatment and patient care      

The use of Artificial Intelligence in healthcare is rapidly growing, and with its limitless potential, many major companies are investing in healthcare applications. The integration of AI and machine learning tools in drug discovery and development can improve healthcare outcomes by increasing efficiency in drug discovery, aiding in the identification of targeted molecules, reducing the time needed for drug discovery and importantly, lowering the costs of drug development for manufacturers
 

Additionally, many pharmaceutical companies and entrepreneurs globally are initiating projects and investing in the development of AI and machine learning technologies to enhance drug discovery and improve outcomes in drug development        

Report Highlights     
By Type
In the AI-driven drug discovery industry, the preclinical and clinical testing segment has the biggest market share by type. The pharmaceutical industry's continuous expansion of AI applications in pre-clinical drug development highlights the technology's crucial role in the entire drug discovery value chain. AI technologies improve each stage, from clinical development to target identification. Artificial intelligence (AI) is widely used in many areas of medicine, such as drug research and discovery, imaging, precision medicine, target-disease relationships, and clinical trials. This wide range of applications highlights AI's revolutionary potential to enhance productivity and results across the whole drug discovery and development process.
 

By Technology
With the biggest market share, the artificial intelligence (AI) sector is anticipated to expand at the quickest compound annual growth rate (CAGR) during the course of the projection period. Deep learning, supervised learning, reinforcement learning, unsupervised learning, and other AI technologies are covered in this section. Deep learning is the one with the most market share among these; its algorithms are widely used in early Alzheimer's disease detection, diabetic retinopathy detection, and breast nodule ultrasound identification. Deep learning techniques simplify intricate data processing, enabling more accurate abnormality discovery and prioritisation, thus enhancing the efficiency and accuracy of medical diagnostics and treatment planning.
With the biggest share of the market, the AI category is anticipated to develop at the quickest compound annual growth rate (CAGR) during the course of the forecast period. The rapid uptake of AI technologies by biotechnology, pharmaceutical, and contract research organisations (CROs) is the primary driver of this expansion. AI has completely changed the biotech sector by speeding up and lowering the cost of the drug discovery process. AI is currently being adopted by several companies in the sector, revolutionising the process of finding and developing new pharmaceuticals. Five of the best AI drug discovery businesses are among the industry leaders, establishing standards for using AI to improve and expedite the drug discovery process.

By Application
Market for artificial intelligence in drug discovery is divided into five main categories: immuno-oncology, cardiovascular disease, metabolic illnesses, neurodegenerative disorders, and others. The immuno-oncology sector maintains the greatest market share due to the rising need for efficient cancer treatments. Massive genomic and proteomic datasets are analysed extensively in immuno-oncology using machine learning (ML) and deep learning (DL) approaches. This methodical approach highlights AI's potential to find novel biomarkers that can be used to customise immunotherapy, improving patient outcomes and treatment efficacy.
Market for artificial intelligence in drug discovery is divided into five main categories: immuno-oncology, cardiovascular disease, metabolic illnesses, neurodegenerative disorders, and others. Neurodegenerative disorders represent the application area in this market with the quickest rate of growth. Recent developments in artificial intelligence (AI) have shown that these illnesses can be diagnosed, predicted, treated, and monitored with great potential. Artificial intelligence (AI) algorithms are capable of analysing enormous volumes of data from a variety of sources, such as clinical records, genetic data, electroencephalography (EEG) signals, driving behaviours, measurable proteins in urine, blood, and cerebrospinal fluid (CSF), and medical photographs. One of the most prevalent neurodegenerative diseases, Alzheimer's disease (AD), gradually reduces memory and cognitive function. The ability of artificial intelligence (AI) to integrate and comprehend vast datasets improves our understanding, diagnosis, and treatment of neurodegenerative illnesses.

By End User
Majority of the AI in drug discovery market is held by pharmaceutical and biotechnology companies. A growing number of biotech and pharmaceutical businesses, as well as their investors, are making investments in artificial intelligence (AI) technology in the hopes that the newest AI generation may provide new cures for a variety of illnesses, including cancer, chronic diseases, and COVID-19. By utilising AI, these businesses may speed up the pre-clinical stage of drug research, cutting expenses and improving development process effectiveness dramatically. Businesses can innovate swiftly and launch innovative, efficient therapies onto the market more quickly thanks to this smart use of AI.
Over the course of the forecast period, research institutions, academic associations, and government foundations are anticipated to witness the quickest growth in the AI drug discovery market. These organisations are making significant investments in data science, AI, and HCI fundamental and application-inspired research. Human-AI interaction, computer vision, human language technologies, and machine learning theory are important areas of focus. In a wide range of industries, artificial intelligence (AI) has shown itself to be a transformative instrument with enormous potential that may benefit economies, society, and governments equally. The strategic focus on R&D in these areas emphasises how important it is to advance AI technology in order to handle difficult problems and spur larger-scale innovation. 

AI in Drug Discovery: Market Drivers 

The global AI in drug discovery market is driven by several factors such as:

• The rise in cross-industry alliances and collaborations
• The growing importance of AI in drug discovery and development
• Increased funding for R&D activities, including AI technology in the field of drug research
• Examples of such collaborations and partnerships include:
• In July 2020, IBM made an acquisition of WDG Automation to enhance its AI-infused automation capabilities for businesses. This acquisition expands IBM's comprehensive capabilities in AI-infused automation, covering both business processes and IT operations
• Artificial intelligence (AI) drug discovery firm, Exscientia, expanded its ongoing partnership for anti-viral drugs with the U.K.'s national synchrotron facility, Diamond Light Source, and the University of Oxford, to include California-based Scripps Research's Calibr and target COVID-19 research
• In January 2021, Nucleai, a U.S-based provider of biomarker-based therapy, entered into a partnership with Debiopharm Pharma Company, a leading company in drug development. As per the terms of the agreement, Debiopharm Pharma Company will use Nucleai's AI platform for its pipeline of oncology drug candidates
• Therefore, the growth of global AI in drug development market is driven by the increase in cross-industry collaborations and partnerships

Market Dynamics
Driver
AI Enhances Drug Discovery Through Advanced Molecular Insights and Clinical Trial Optimization
By improving our understanding of molecular mechanisms, predicting dose-response relationships in pharmacokinetic/pharmacodynamic modelling, and streamlining toxicology assessments with tools like the Deeptox Algorithm for precise toxicity predictions, artificial intelligence (AI) is a key factor in the drug discovery market's advancement. AI techniques dramatically enhance critical procedures in clinical trials, including molecular effect prediction, gene target localisation, and illness identification. Moreover, AI-powered solutions facilitate risk-based monitoring and expedite medication adherence, which increase clinical trial success rates and efficiency. These features highlight AI's vital role in speeding up drug discovery procedures and propelling market expansion in the pharmaceutical industry.

Restraints
Data Challenges 
Significant data issues prevent artificial intelligence (AI) from reaching its full potential in the drug research industry. Among these difficulties include the enormous size, quick expansion, variety, and innate unpredictability of pharmaceutical data sets, which may contain millions of different molecules. Large and complicated data sets like these may be too much for traditional machine learning (ML) methods to handle efficiently. Limitations in AI applications for drug development are further exacerbated by QSAR-based models, which are dependent on short training sets and prone to inaccuracies in experimental data. Another layer of restriction that hinders the scalability and effectiveness of AI-driven techniques in furthering drug development efforts is the absence of strong experimental validations. To fully realise the promise of AI and promote expansion in the pharmaceutical sector, it is imperative to tackle these data-related challenges..
 

Opportunities
AI's Role in Drug Formulation and Manufacturing 
The pharmaceutical sector stands to gain a great deal from the application of artificial intelligence (AI) in drug design and manufacturing. Artificial Intelligence (AI) substitutes manual trial-and-error methods with computer tools that use Quantitative Structure-Property Relationship (QSPR) models to handle formulation design difficulties like stability, dissolution, and porosity. By using rule-based systems to choose excipients based on the physicochemical characteristics of drugs, decision-support tools constantly optimise procedures through feedback mechanisms. AI is being integrated into modern production systems to automate processes such as Computational Fluid Dynamics (CFD), which evaluates stress and agitation in machinery such as stirred tanks. By increasing productivity and quality of output, this automation satisfies industry expectations for sophisticated production techniques. AI has a significant impact on pharmaceutical operations, which highlights how it can spur innovation and expansion in the drug discovery sector.
•    In October 2023, Fujitsu and RIKEN developed AI drug discovery technology utilizing generative AI to predict structural changes in proteins. 

Market Segmentation: AI in Drug Discovery Market     

The global AI in drug discovery market is segmented by drug type, application, end user, offering, and technology.

• In terms of drug type, the market is divided into large molecules and small molecules 
• By application, the market is classified into oncology, infectious diseases, neurological disorders, rare diseases, metabolic diseases, cardiovascular diseases, and others
• In terms of end user, the market is segmented into pharmaceutical & biotechnology companies, contract research organizations, academics & research, and others
• By offering, the market is split into software and services
• In terms of technology, the market is segmented into machine learning and other technologies
  Each of these segments have been analyzed in detail for market trends, recent trends, and developments, drivers, restraints, opportunities, and useful insights. 

The AI in drug discovery market report provides current and expected revenue (US$ Mn) for each of these segments from 2021 to 2031, considering 2020 as the base year. The compound annual growth rate (percentage CAGR) has been provided for each segment and market from 2021 to 2031 along with market size estimations

Regional Overview: AI in Drug Discovery Market

• The global AI in drug discovery market is segmented by region, including North America, Europe, Asia Pacific, Latin America, and Middle East & Africa, which have been further divided into major countries and sub-regions
• North America is expected to hold the largest share of the global AI in drug discovery market, due to the region's advanced technology and early adoption of latest technologies. High awareness about AI in drug discovery among key players in the region is also driving the market's growth 
• The report provides the current and expected market revenue (US$ Mn) of these regional markets and their major countries from 2021 to 2031, with their CAGRs from 2021 to 2031
• The study also offers a list of recommendations, highlights, and useful insights of the global AI in drug discovery market, which can help new companies entering the market and existing companies to increase market shares and in the decision-making process

Key Insights

•    North America accounted largest market share.
•    The APAC market is projected to grow at a notable CAGR in forecast period.
•    By therapeutic area, the oncology segment accounted market share and the infectious diseases segment is projected to grow at the fastest CAGR.
•    Based on application, the drug optimization and repurposing segment has garnered a market share of and the preclinical testing segment is growing faster.

Regional Stance
Market for AI in drug discovery is expected to be dominated by North America, especially Canada. The incorporation of artificial intelligence (AI) into the medication research and development process guarantees Canada's ability to adapt to the health demands of its populace and to be ready for pandemics and other emergencies in the future. The Canadian government is fully dedicated to implementing state-of-the-art technology in order to expedite medication discovery and create efficient therapies for the country's citizens. The Canadian Association of Radiologists (CAR) has highlighted that the country's current healthcare environment is highly favourable for the adoption of AI. The integrated nature of the Canadian healthcare system makes it ideal for combining anonymised medical data from different institutions and provinces to improve and validate AI tools for patient management. AI applications range from direct patient care, improving diagnosis, prognosis, treatment selection, and enabling robotic surgeries and examinations, according to the Government of Canada Report on Integrating Robotics, Artificial Intelligence, and 3D Printing Technologies into Canada's Healthcare Systems. indirect patient care via better inventory control and hospital operations, as well as homecare using wearable technology and sensors to anticipate patients' requirements.
Market for AI in drug discovery is expected to grow at the quickest rate in the Asia-Pacific area, with India emerging as a major participant. The potential of AI to personalise treatment regimens, facilitate remote consultations, and speed up drug discovery is driving the technology's explosive growth in the Indian healthcare sector, which is expected to grow to be a sizable market in the years to come. Gen AI, or generative artificial intelligence, is essential for data analysis, side effect prediction, and medication repurposing. It increases efficiency in clinical trials by anticipating obstacles. Leading the charge in this AI revolution are India's biotech entrepreneurs, which are using Gen AI for drug development and patient-centric applications. They are also contributing to highly targeted medicines and putting India on the map of international clinical trials. AI co-pilots are being developed by businesses to increase productivity and efficiency throughout the value chain. Building a trained workforce that can adapt to these cutting-edge technologies is crucial if we are to continue this growth.

Major Players    

The AI in drug discovery market report concludes with the company profiles section, which includes key information about major players in the global AI in drug discovery market

Leading players analyzed in the report include

• Exscientia
• GNS Healthcare
• Cloud Pharmaceuticals, Inc.
• Benevolent AI
• PathAI, Inc.
• Berg Health
• Atomwise
• Insitro
• Cyclica
• IBM
• Nucleai 
• Wuxi AppTec
• BlackThorn Therapeutics
• Insilico Medicine
• Notable Labs
• Numerate  
• Standigm
• Recursion Pharmaceuticals
• BioSymetrics
• The AI in drug discovery market report includes profiles of the major players in the market based on key parameters such as company overview, financial overview, business strategies, application portfolio, business segments, and recent developments

Recent Developments

•    In January 2024, Deloitte expanded its Quartz AI Suite with Atlas AI for Drug Discovery. 
•    In May 2024, Sanofi, Formation Bio, and OpenAI announced a first-in-class AI collaboration. 
•    In March 2024, Elsevier and Iktos partnered to deliver an AI-driven synthetic chemistry platform for drug discovery. 
•    In May 2024, Oregon Therapeutics and Lantern Pharma launched a strategic AI collaboration to optimize the development of the first-in-class drug candidate XCE853, a potent inhibitor of cancer metabolism. 

AI in Drug Discovery Market – Segmentation      

UMR's study on the AI in drug discovery market includes information segmented into six categories: offering, technology, drug type, application, end user, and region. The report covers in-depth analysis of evolving industry trends and key market dynamics related to these segments of the global AI in drug discovery market