Artificial Intelligence (AI) in Drug Discovery Market Size, Share & COVID-19 Impact Analysis, By Drug Type (Small Molecule and Large Molecule), By Offering (Software and Services), By Technology (Machine Learning, Natural Language Processing, and Others), By Application (Endocrinology, Cardiology, Oncology, Neurology, and Others), By End-user (Pharmaceutical & Biotechnological Companies, Academic & Research Institutes, and Others), and Regional Forecast, 2023-2030

The global artificial intelligence (AI) in drug discovery market size was valued at USD 3.00 billion in 2022 and is projected to grow from USD 3.54 billion in 2023 to USD 7.94 billion by 2030, exhibiting a CAGR of 12.2% from 2023-2030. North America dominated the global market with a share of 69.33% in 2022.

Artificial intelligence plays a vital role in the drug discovery process, which is augmenting the growth of the pharmaceutical sector. The drug discovery and development process is time-consuming and expensive. However, with the help of artificial intelligence, this can be addressed. Artificial intelligence recognizes hit and lead compounds and provides a quicker validation of the drug target and optimization of the drug structure design. Pharmaceutical companies are rapidly introducing systems focusing on artificial intelligence to exploit data on genes, variants, receptor targets, disease events, and clinical studies to establish associations between drugs and disease.

The increasing patient population with chronic diseases is surging the demand for effective medical interventions. This has influenced the manufacturers' focus on introducing novel treatment approaches at lower manufacturing costs. Integration of cloud-based services and applications is expected to create new and ample opportunities for the growth of this market. Growing collaborations and partnerships to reduce the time and cost of the drug discovery process are anticipated to drive the adoption of these products and services during the forecast period.

• For example, in January 2022, Sanofi signed a deal to use U.K. start-up Exscientia’s artificial intelligence platform to conduct research studies for metabolic-disease therapies. Most sizable biopharma players have similar collaborations, which is likely to expedite market growth.

COVID-19 IMPACT

Surge in Adoption of Artificial Intelligence During the Pandemic Impacted Market Positively

The COVID-19 outbreak had a positive impact on the global artificial intelligence in drug discovery market growth in 2020. The pharmaceutical industry was focused on introducing and developing both preventive and therapeutic interventions to address the emergence of COVID-19. Several pharmaceutical companies incorporated artificial intelligence tools as a means to identify more precise targeted treatments to fight the COVID-19 pandemic. These artificial intelligence-based tools helped in testing the affinity between the drugs/peptides and the target sequence of infected patients to design better vaccines or drugs against COVID-19. Researchers across the world proposed several vaccines/drugs for COVID-19 utilizing artificial intelligence-based approaches.

• For instance, in April 2022, artificial intelligence was successfully employed by Pfizer to run vaccine trials and accelerate distribution. Pfizer used artificial intelligence to ensure that the COVID-19 vaccine matches the individual’s needs. Pfizer initiated automating its research and development activities by incorporating artificial intelligence into its working system even before the pandemic.

This positive impact was observed on the revenues of companies offering these platforms and services to the pharmaceutical industry.

• Schrödinger, Inc., witnessed a year-on-year growth of 85.6% in 2020 in its software segment sales, which provides a physics-based platform to biopharmaceutical companies to reduce time in developing novel therapies.


• This growth continued in 2021 with a year-on-year growth of 82.1% in its software segment. For the financial year 2022, the revenue generated from the software business segment exhibited similar growth to the pre-pandemic year.

The use of artificial intelligence in the pharmaceutical industry is expected to boost in the post-pandemic era as market players are adopting artificial intelligence-based tools and services in their drug development processes in order to reduce manufacturing costs within a short period. The growing collaborations between market players to introduce potential cures or treatment approaches for various diseases are anticipated to drive market growth during the forecast period.

Artificial Intelligence in Drug Discovery Market Trends

Artificial Intelligence-Enabled Biology Modeling and Target Discovery to Drive Market Growth

The pharmaceutical sector operates at research, clinical, and business levels. These operating segments are being redefined by the introduction of artificial intelligence and data technologies, novel computational tools, and infrastructural solutions.

In drug discovery research, identifying novel drug targets is a critical step for developing novel first-in-class therapeutic drugs. Traditionally, this step in drug discovery is carried out by using a ligand molecule that influences specific proteins to create suitable pockets for target identification. Novel computational approaches based on AI technologies identify new druggable protein pockets at scale and sometimes provide proteome-wide virtual screens.

The market players driven by artificial intelligence are offering target-discovery-as-a-service to other organizations. These services are focused on validating, designing and discovering novel targets. The market players are actively making strategic alliances to rejoice the leverages offered by these platforms and services together.

• For instance, in November 2022, Insilico Medicine signed a USD 1.2 billion deal with Sanofi to discover up to six new targets leveraging Insilico Medicine’s Pharma.AI platform.

Artificial Intelligence in Drug Discovery Market Growth Factors

Increasing Patient Population with Chronic Diseases to Drive the Adoption Rate of Artificial Intelligence (AI) in Drug Discovery

The emergence of epidemics and pandemics, such as influenza and COVID-19, and the prevalence of severe chronic diseases, such as cancer and heart disease, surges the ongoing need to discover novel drugs. The increasing prevalence of chronic diseases is boosting the already growing demand for AI-powered solutions in the drug discovery market. Chronic disease imposes a considerable economic burden on health services and is a major public health problem globally. According to the United Nations Chronicles, the global chronic disease burden is expected to increase to 56% by 2030. The highest increase is expected in the African, Asian, and Eastern Mediterranean regions.

In order to cater to this growing demand for novel and effective treatment, industry players are making strategic collaborations to accelerate the drug discovery and development process by incorporating artificial intelligence benefits.

• In July 2023, BioNTech acquired InstaDeep Ltd., a leading company in the field of artificial intelligence and machine learning. The acquisition was aimed to strengthen BioNTech’s capabilities in AI-driven drug discovery and the development process of next-generation immunotherapies and vaccines to address diseases with high unmet medical needs. Such strategic collaborations are expected to drive the adoption rate of artificial intelligence offerings, subsequently driving market growth.

Benefits Offered by Artificial Intelligence in Drug Discovery Process to Propel Market Growth

Drug discovery is a multi-stage process that includes target identification, high throughput screening, validation, safety and efficacy protocols, animal studies, clinical trials, and regulatory approval. The process is expensive and time-consuming, with a high risk of failure at every step.

• Development of a new drug takes approximately 14.6 years and costs about USD 2.6 billion on average, as per a study published by the Tufts Centers in 2019.

Integration of artificial intelligence-based methods at several stages in this process, such as identifying novel targets, evaluating drug-target interactions, examining disease mechanisms, and improving the molecule's compound design and optimization, reduces the manufacturing cost. Artificial intelligence solves key industry challenges and significantly speeds up the discovery process to support companies in reclaiming a sizable amount of their costs. These benefits offered by artificial intelligence in reducing the time and cost required for drug discovery and development are expected to drive market growth.

RESTRAINING FACTORS

Lack of Standardization in Data Quality May Hinder the Implementation of Artificial Intelligence in Drug Discovery Process

Despite the high number of successes, pharmaceutical companies need to address certain challenges to leverage the benefits of artificial intelligence (AI) in drug discovery process. For instance, smaller and more complex data sets serve as an impediment to the implementation of artificial intelligence-based tools. Pharma data sets are usually smaller, with fewer patients and fewer observations per patient, which makes achieving meaningful insights more challenging as most artificial intelligence algorithms need big datasets to learn.

Moreover, due to the large number of diseases and illnesses and the relatively small number of incidences of each, creating large data for each type of medical condition is very challenging.

Similarly, there are fewer data sets and far more features for each dataset, which are in multiple formats. AI systems for drug development need the ability to support varied and complex data, such as digital imaging and communication for medicine (DICOM). This lack of availability of quality data in a standard format may serve as an impediment to implementing artificial intelligence tools in the drug discovery process. Hence restricting the market growth.

Artificial Intelligence in Drug Discovery Market Segmentation Analysis

By Drug Type Analysis

Comparatively Low Cost of Small Molecule Drug Discovery to Boost Small Molecule Segment Growth

By drug type, the market is segmented into small molecule and large molecule.

The small molecule segment held a dominant artificial intelligence (AI) in drug discovery market share in 2022. The segment’s growth is attributed to the availability of a large number of clinical data for these molecules. The implementation of artificial intelligence to analyze these data sets accelerates the drug development process and shortens the drug approval process. These molecules have predictable properties, which makes the drug discovery process cost-effective. Moreover, a large number of companies focusing on small molecule drug discovery processes are surging the demand for effective implementation of artificial intelligence solutions.

• According to a research paper published by the Medicine in Drug Discovery Journal in March 2021, small molecules constitute more than 90% of the current global pharmaceutical market. Similarly, according to the U.S. FDA data, out of 293 chemical entities approved during 2017-2022, 182 were small molecules. This dominance is attributed to the benefits offered by these molecules in terms of manufacturing process and cost, which are expected to augment the segment’s growth.

Large molecule comparatively held a lower share of the global market in 2022. The number of laboratories focusing on the research and development of large molecules is limited due to the complexity involved in the process. This limits the availability of sufficient data for the effective implementation of artificial intelligence solutions and is one of the crucial factors responsible for the lower share of the market. However, increasing investment by market players for large molecule drug discovery and development to offer better therapeutic effects at affordable prices is expected to surge the demand for artificial intelligence solutions during the forecast period.

• For instance, in November 2022, the Serum Institute of Life Sciences increased its investment in Biocon Biologics by converting a USD 150 million loan into equity. Growing investment in the development of these molecules is likely to propel the segment’s growth during the forecast period.

By Offering Analysis

Introduction of Novel Platforms to Drive Software Segment Growth

By offering, the market is segmented into software and services.

The software segment dominated the market in 2022, owing to the continuous introduction of novel solutions with advanced features by market players.

• For example, in February 2023, BenchSci launched ASCEND. This artificial intelligence software aims to expedite the preclinical phase of drug development by extracting biological insights underlying disease.

Increasing investment by market players to introduce novel solutions to reduce steps of the drug discovery process and expedite the candidate's development process is likely to drive the segment’s growth.

The services segment is projected to grow at a comparatively lower CAGR during the forecast period. There is a lack of skilled professionals trained to offer and install artificial intelligence solutions, which increases the overall expenditure. Moreover, some companies offer services to process certain steps of drug discovery and not the whole process. These factors are contributing to the slower growth of the segment.

By Technology Analysis

Growing Preference Toward Machine Learning Led to Segment’s Dominance

Based on technology, the market is segmented into machine learning, natural language processing, and others.

The growing preference for machine learning led to its market dominance during the forecast period. Machine learning creates predictive models that have gained significant importance in the steps prior to preclinical studies. Machine learning (ML) approaches provide a set of tools that improve discovery and decision-making for well-specified questions with abundant and high-quality data.

• According to a research article published by the Cell Reports Methods in February 2023, machine learning has found many applications in drug development, including FDA approval predictions, clinical trial design, drug repurposing, and even the generation of new therapeutic targets.

The natural language processing segment held a considerable market share in 2022. The technology can extract structured information from text-based documents. The benefits offered by this technology in deriving concrete insights from a vast amount of information are contributing to the segment’s growth. Other technologies include machine vision, automation and robotics, among others. The segment is expected to grow at a comparatively lower CAGR during the forecast period. These technologies are still at a very nascent stage of development and require a large set of data to process and provide desirable outcomes. For instance, natural language processing extracts valuable insights from large volumes of unstructured data, such as scientific literature, clinical trial reports, and patient records.

By Application Analysis

Increasing Clinical Trials for Oncology is Driving Oncology Segment Growth

Based on application, the market is segmented into endocrinology, cardiology, oncology, neurology, and others.

The oncology segment dominated the global market in 2022. The segment’s growth is attributed to the increasing prevalence of cancer and the growing need to introduce effective therapeutic measures to address it. This has increased the investment and clinical trials in this therapeutic area. Moreover, there are a large number of artificial intelligence-based algorithms that provide powerful tools in artificial intelligence-assisted anti-cancer drug design. These factors are cumulatively contributing to the segment’s growth.

The neurology segment held a notable market share in 2022. The segment encompasses neurodegenerative diseases, neuropathic pain, and psychiatric conditions. The growing investment in neurology drug discovery by market players is expected to surge the demand for artificial intelligence integration, leading to segment growth.

• For instance, in June 2022, Biogen invested more than USD 700 million in Alectos’ preclinical oral Parkinson’s disease candidate AL01811.

The cardiology segment held a comparatively lower share, followed by endocrinology. The limited pipeline of candidates under clinical trials for these therapeutic areas is contributing to its slower growth during the forecast period. Limited data sets available and investment for other diseases are responsible for the slower growth of other segments during the forecast period.

By End-user Analysis

Growing Collaborations led to the Dominance of Pharmaceutical & Biotechnological Companies Segment

By end-user, the market is segmented into pharmaceutical & biotechnological companies, academic & research institutes, and others.

The pharmaceutical & biotechnological companies segment held a dominant share in 2022. The segment’s growth is attributed to the growing focus of the pharmaceutical industry toward the integration of artificial intelligence offerings in their drug discovery programs through strategic alliances, which is driving the demand for these solutions. For instance, Exscientia partnered with a German biomedical company, Evotec, to develop a novel cancer treatment in 2021. The A2a receptor antagonist candidate drug was discovered within eight months of the project launch. Such collaboration reduces the manufacturing cost and also minimizes the duration required for the completion of a program, subsequently augmenting the segment’s growth.

The academic & research institutes segment is anticipated to hold the second most dominant share during the forecast period. Increasing funding for research projects at the academic and research institute level to conduct pilot studies is expected to drive the segment’s growth during the forecast period. The others segment includes contract drug manufacturers, hospitals, and clinics where integration of these solutions may be difficult due to cost constraints, hence limiting the segment’s growth.

REGIONAL INSIGHTS

Geographically, the global artificial intelligence in drug discovery market is segmented into North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa.

North America market size was valued at USD 2.08 billion in 2022 and is expected to emerge as a leading region in the global market during the forecast period. The growth in this region is attributed to the strong presence of pharmaceutical companies and their strategic alliances with companies offering artificial intelligence solutions. The growing need to control drug discovery and development costs is surging the demand for artificial intelligence solutions across the region. Moreover, the increasing prevalence of chronic disease coupled with the growing investment in drug discovery processes is subsequently driving market growth across the region. According to an article published by Cushman & Wakefield in January 2023, drug discovery and biotechnology accounted for 72% of 2022 Funding in the U.S. This is expected to drive market growth across the region.

Europe market for artificial intelligence in drug discovery held the second-largest share in 2022. The growing focus of manufacturers on introducing novel treatment interventions at affordable costs by reducing the manufacturing process is surging the need for artificial intelligence integration. The growing adoption of artificial intelligence in drug discovery and development across the region is contributing to market growth.

Asia Pacific market for artificial intelligence in drug discovery is expected to grow with the highest CAGR during the forecast period. The growing prevalence of chronic diseases and the strong presence of drug manufacturers in this region are some of the factors contributing to the region’s growth during the forecast period.

The Middle East & Africa and Latin America are expected to witness comparatively slower growth during the forecast period due to limited healthcare expenditure and lack of presence of manufacturers in these regions.

List of Key Companies in Artificial Intelligence in Drug Discovery Market

Strategic Alliances Initiated by Key Players to Strengthen their Market Position Drive Market Growth

In terms of the competitive landscape, the market is highly competitive, with strong offerings by several market players. Key players, such as Microsoft, Exscientia, Benevolent AI, and others, are focusing on making strategic alliances with pharmaceutical companies to accelerate the development of pipeline candidates. For instance, in September 2023, Exscientia entered into a multi-year collaboration with Merck KGaA. In this collaboration, Merck KGaA will utilize Exscientia’s artificial intelligence-driven precision drug design and discovery capabilities for the discovery of novel small-molecule drug candidates across oncology, neuroinflammation, and immunology.

Some other prominent players, such as Atomwise Inc., Schrödinger, Inc., Insilico Medicine, Alphabet Inc., and IBM Watson Health, among others, are actively focused on strengthening their portfolios to increase their market presence. In 2021, Alphabet Inc., together with DeepMind, launched Isomorphic Labs to apply artificial intelligence in drug discovery and basic biology.

LIST OF KEY COMPANIES PROFILED:

• Microsoft (U.S.)


• Schrödinger, Inc. (U.S.)


• Cresset (U.K.)


• IBM (U.S.)


• Atomwise Inc. (U.S.)


• Insilico Medicine (U.S.)


• Exscientia (U.K.)


• BenevolentAI (U.K.)


• Aria Pharmaceuticals, Inc. (U.S.)


• Integral BioSciences (U.S.)


• Alphabet Inc. (U.S.)

KEY INDUSTRY DEVELOPMENTS:

• November 2022: Cyclica received a USD 1.8 million grant from the Bill & Melinda Gates Foundation to apply its artificial intelligence-enabled drug discovery platform to discover new non-hormonal contracts, leveraging multiple low-data biological targets.


• October 2022: Ginkgo Bioworks, a horizontal platform provider for cell programming, acquired Zymergen. The acquisition is expected to enhance Ginkgo's platform by integrating strong automation and software capabilities as well as a wealth of experience across diverse biological engineering approaches.


• September 2022: CytoReason, an Israel-based biology modeling company, collaborated with Pfizer at the worth of USD 110 million. Pfizer started using CytoReason’s biological models in research to develop new drugs for immune-mediated diseases and cancer immunotherapies.


• August 2022: Sanofi partnered with Atomwise in a drug design deal worth USD 1.2 billion. As per the deal, Sanofi paid USD 20 million upfront to leverage the U.S. company’s AtomNet platform to research small molecules for up to five drug targets.


• May 2022: AstraZeneca collaborated with BenevolentAI to collect a second pulmonary fibrosis target from BenevolentAI’s artificial intelligence-driven drug discovery platform.

REPORT COVERAGE

The research report provides a detailed analysis of the market. It focuses on key aspects such as leading companies, offerings, technology, applications, and end-users. Besides this, it offers insights into the market trends, the impact of COVID-19, and the prevalence of key chronic diseases, among other key insights. In addition to the factors mentioned above, the report encompasses several factors that have contributed to the growth of the market over recent years.

Report Scope & Segmentation

ATTRIBUTE	DETAILS
Study Period	2017-2030
Base Year	2022
Estimated Year	2023
Forecast Period	2023-2030
Historical Period	2017-2021
Growth Rate	CAGR of 12.2% from 2023 to 2030
Unit	Value (USD Billion)
Segmentation	By Drug Type, Offering, Technology, Application, End-user, and Region
By Drug Type Small Molecule Large Molecule
By Offering Software Services
By Technology Machine Learning Natural Language Processing Others
By Application Endocrinology Cardiology Oncology Neurology Others
By End-user Pharmaceutical & Biotechnological Companies Academic & Research Institutes Others
By Region North America (By Drug Type, Offering, Technology, Application, End-user, and Country) U.S. Canada Europe (By Drug Type, Offering, Technology, Application, End-user, and Country/Sub-Region) U.K. Germany France Italy Spain Scandinavia Rest of Europe Asia Pacific (By Drug Type, Offering, Technology, Application, End-user, and Country/Sub-Region) Japan China India Australia Southeast Asia Rest of Asia Pacific Latin America (By Drug Type, Offering, Technology, Application, End-user, and Country/Sub-Region) Brazil Mexico Rest of Latin America Middle East & Africa (By Drug Type, Offering, Technology, Application, End-user, and Country/Sub-Region) GCC South Africa Rest of the Middle East & Africa