Global Generative AI in Pharma Market By Component (Software and Services), By Application (Drug Discovery, Clinical Trials, and Others), By Technology (Natural Language Processing, Context-Aware Processing, and Other ), By Deployment (On-premise and Cloud-based), By Region And Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, And Forecast 2023-2032

Report Overview

Global Generative AI in Pharma market size is expected to be worth around USD 2258.1 Mn by 2032 from USD 159.9 Mn in 2022, growing at a CAGR of 31.2% during the forecast period from 2023 to 2032.

Request Covid - 19 Impact

The generative AI in pharma market refers to the use of artificial intelligence for accelerating and improving the drug discovery & development process in the pharmaceutical industry. AI-powered platforms can be used for designing and optimizing drug molecules, predicting their efficacy & safety, and identifying potential drugs for further development. This can significantly reduce the time & cost required for developing new drugs and treatments while also improving success rates. The market is still new but it is expected to witness steady growth in the upcoming years which is driven by factors like the growing pharmaceutical industry, the increasing demand for more efficient drug discovery & development technologies, and the increasing availability of data & computing power.

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Driving Factors

There is Need for More Efficient and Effective Drug Discovery and Development Technologies

Several drivers are propelling the growth of the generative AI in pharma market. One major driver is the need for more efficient & effective drug discovery and development technologies. AI-powered platforms can significantly reduce the time & cost required for the development of new drugs & treatments, while also improving success rates. Another driver is the growing demand for personalized medicine which can be enabled through the use of AI to identify patients who are most likely to benefit from a particular treatment. Additionally, the increasing prevalence of chronic diseases like cancer & cardiovascular disease is creating a significant market for new drugs and treatments which can be addressed using AI-powered drug discovery and development platforms. Finally, the increasing availability of data and computing power is enabling the development of more advanced and effective AI-powered platforms which further drive innovation in the field. Overall, these drivers are expected to continue to propel the growth of the generative AI in pharma market in the coming years as companies & research institutions increasingly adopt AI technologies for improving the efficiency & effectiveness of drug discovery and development.

Restraining Factors

High Cost and Regulatory Challenges Can Hamper the Growth of the Market

While the market for generative AI in pharma has significant growth potential, it is not without its restraints. One major restraint is the high development costs associated with AI-powered drug discovery and development platforms. These costs can create barriers to entry for smaller companies and startups, limiting competition in the market. Another restraint is the regulatory challenges associated with AI-powered drug discovery and development, with uncertainty around how regulators will evaluate and approve AI-powered treatments creating delays and barriers to commercialization. Ethical considerations around issues such as privacy, data ownership, and algorithmic bias are also a concern, creating legal and reputational risks for companies operating in the market. Finally, there may be a limited understanding of AI technology among pharmaceutical companies and research institutions, creating a reluctance to adopt AI-powered platforms and a lack of investment in AI research and development. Addressing these restraints will be critical to the continued growth and evolution of the generative AI in pharma market.

COVID-19 Impact Analysis

There has Been an Increase in Demand for new Treatments and Vaccines to Combat the Virus

The COVID-19 pandemic has significant impact on the market for generative AI in pharma. One major effect has been the increased demand for new treatments & vaccines to combat the virus. This has led to a greater focus on AI-powered drug discovery & development with companies and research institutions leveraging AI-powered platforms for accelerating the development of new treatments and vaccines. However, the pandemic has also caused major disruptions to clinical trials delaying the development of new drugs & treatments. This has highlighted the need for more efficient & flexible clinical trial designs that can adapt to changing circumstances. Additionally, the pandemic has accelerated the shift towards remote work leading to increased adoption of cloud-based platforms and remote collaboration tools in the field of AI-powered drug discovery & development. Finally, governments have provided increased support for AI research & development in response to the pandemic, providing funding and other incentives to companies and institutions working in the field. Overall, while the COVID-19 pandemic has presented significant challenges to the market for generative AI in pharma, it has also created new opportunities and highlighted the importance of AI-powered drug discovery & development in responding to global health crises.

By Component Analysis

The Software Segment Accounted for the Largest Revenue Share in Generative AI in Pharma Market in 2022.

Based on the Component, the market is divided into software and services. Among these types, the software segment is expected to be the most lucrative in the global generative AI in pharma market, with the largest revenue share of 62.7% & projected CAGR of 31.7% during the forecast period. AI-powered software is essential to the drug discovery & development process allowing for the rapid and efficient analysis of large volumes of data to identify promising drug candidates. Secondly, the increasing availability of advanced machine learning & deep learning algorithms enables more accurate and efficient drug discovery & development. Finally, the scalability and flexibility of AI-powered software make it a more attractive option for companies & research institutions looking to adopt AI-powered drug discovery & development platforms.

The Services Segment is Fastest Growing Component Segment in Generative AI in Pharma Market.

The service segment is also an important component segment and it is expected to grow faster in the component segment in generative AI in pharma market with a CAGR of 32.2%. It is fastest growing due to the increasing demand for implementation, consulting, and support services from companies & research institutions that are adopting AI-powered drug discovery & development platforms. The complexity of these platforms requires specialized expertise, specifically in the areas of data analysis, algorithm development, and integration with existing drug discovery workflows.

By Application Analysis

The Drug Discovery Segment Accounted for the Largest Revenue Share in Generative AI in Pharma Market in 2022.

Based on application, the market is divided into drug discovery, clinical trials, personalized medicines, and disease diagnosis. Among these types, the drug discovery segment is expected to be the most lucrative in the global generative AI in pharma market, with the largest revenue share of 44.7% & projected CAGR of 31.8% during the forecast period. Due to the crucial role, it plays in the drug development process. AI-powered drug discovery platforms are designed to identify & optimize promising drug candidates which can be developed further into potential treatments for a range of diseases. This process involves the use of AI-powered software to design & optimize drug molecules, predict their efficacy & safety, and identify potential drug candidates for further development.

The Clinical Trial Segment is Fastest Growing Type Segment in Generative AI in Pharma Market.

The clinical trial segment is projected to be the fastest-growing application segment in generative AI in pharma market from 2022 to 2031. Owing to the increasing demand for more efficient & flexible clinical trial designs, particularly in light of the disruptions caused by the COVID-19 pandemic. AI-powered platforms can help to optimize clinical trial design and enable the identification of the most promising drug candidates & the most effective dosing regimens, also reducing the risk of adverse events. Another reason is the growing adoption of precision medicine which requires the development of treatments that are created for the specific needs of individual patients.

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By Technology Analysis

The Natural Language Processing Segment Holds the Significant Share of Generative AI in Pharma Market.

Based on technology, the market is divided into natural language processing, context-aware processing, deep learning, querying method, and other technologies. Among these, the natural language processing segment is dominant in the technology segment in generative AI in pharma market with a revenue share of 38.8% and CAGR of 31.2%. Owing to the ability of NLP-powered platforms for analyzing and understanding large volumes of unstructured data like scientific literature & clinical trial data. Another reason is the growing use of electronic health records in the healthcare industry which are rich sources of unstructured data that can be analyzed using NLP-powered platforms. Finally, the NLP segment is likely to benefit from the rising demand for personalized medicine which requires the analysis of huge amounts of patient data for identifying patient subgroups that are most likely to respond to the particular treatment.

Deep Learning is Identified as Fastest Growing Technology Segment in Projected Period.

Deep learning is also an important technology segment in the generative AI in pharma market and it is expected to grow faster in the technology segment in the generative AI in pharma market with a CAGR of 32.4% and market value is 34.2. It is fastest growing due to the increasing availability of advanced deep learning algorithms & the rising demand for more accurate and efficient drug discovery & development technologies. Deep learning algorithms are effective at processing different and high dimensional data like images & molecular structures which are important components of the drug discovery & development process.

By End-User Analysis

The Pharmaceutical Companies Hold the Significant Share of Generative AI in Pharma Market.

Based on end-user, the market is divided into pharmaceutical companies, contract research organizations, academic research institutes, and government organizations. Among this pharmaceutical companies are dominant in the end-user segment of generative AI in pharma market with a revenue share of 47.6% and a CAGR of 31.5%. Owing to the high cost & complexity of the drug discovery & development process which requires significant investments in research & development. Pharmaceutical companies have the required resources & expertise for investing in these processes which makes them the preliminary user of AI-powered drug discovery & development platforms. Additionally, pharmaceutical companies have the required knowledge & expertise to run the difficult process of drug development which is important for the successful development & commercialization of new drugs.

Contact Research Organization is Identified as Fastest Growing End-User Segment in Projected Period.

CROs are also important in the end-user segment in generative AI in pharma market and it is expected to grow faster in the end-user segment of generative AI in pharma market with a CAGR of 32.1% and a market value is 31.2 It is fastest growing due to they provide specialized expertise in drug development & offer a wide range of services which includes clinical trial design & management, data management, and regulatory support. CROs also have access to a broad range of drug discovery & development technologies which includes AI-powered platforms that can help to accelerate the drug development process.

By Deployment Analysis

The On Premise Segment Accounted for the Largest Revenue Share in Generative AI in Pharma Market in 2022.

Based on deployment, the market is divided into on-premise and cloud-based. Among these, the on-premise segment is dominant in the deployment segment in generative AI in pharma market with a market value of 45.7% and CAGR of 31.6%. Owing to the need for increased control & security over sensitive data in the drug discovery & development process. On-premise solutions enable companies & research institutions to maintain control over their data & infrastructure, reducing the risk of data breaches or other security issues. Another reason is the complexity of AI-powered drug discovery & development platforms, which often require significant computing power and specialized infrastructure to operate effectively.

Cloud Based is Identified as the Fastest Growing Deployment Segment in Projected Period.

Cloud Based is another major deployment area and it is expected to grow faster in the deployment segment of generative AI in pharma market with a CAGR of 32.1%. Owing to the scalability & flexibility of cloud-based solutions which can be easily scaled up or down to meet the needs of different drug discovery projects.  Another reason is the cost-effectiveness of cloud-based solutions which can be more affordable than on-premise solutions for smaller companies & research institutions with limited budgets.

Generative AI in Pharma Key Market Segments

Based on Component

• Software
• Services

Based on Application

• Drug Discovery
• Clinical Trials
• Personalized Medicines
• Disease Diagnosis

Based on Technology

• Natural Language Processing
• Context-Aware Processing
• Deep Learning
• Querying Method
• Other Technologies

Based on End-User

• Pharmaceutical Companies
• Contact Research Organizations
• Academic Research Institutes
• Government Organizations

Based on Deployment

• On-premise
• Cloud-based

Growth Opportunity

The Development of New Drugs and Treatments for a Range of Diseases Create Opportunities in the Generative AI in Pharma Market

The market for generative AI in pharma is filled with several opportunities. One big opportunity lies in the development of new drugs & treatments for a range of diseases. AI-powered drug discovery & development platforms have the potential to seriously speed up the drug development process which allows for the faster development & commercialization of new treatments. Another opportunity lies in the use of AI in personalized medicine which has the potential to transform healthcare by customized treatments to the specific needs of individual patients. Furthermore, the use of AI in clinical trials has the potential to seriously improve the efficiency & success rate of clinical trials which is leading to faster & more reliable compliance of new drugs. The use of AI in drug manufacturing also presents significant opportunities for improving the efficiency & quality of drug production, reducing costs & improving patient outcomes. Finally, the growing demand for more efficient & effective drug discovery and development technologies in emerging markets presents a significant opportunity for companies operating in the generative AI in pharma market to expand their reach and tap into new markets. Overall, the market for generative AI in pharma presents several opportunities for innovation, growth, and improved healthcare outcomes.

Latest Trends

Increasing Use of AI in Clinical Trials and The Integration of Generative AI into Drug Discovery is Trending in the Market

The market for generative AI in pharma is continually evolving with several latest trends that are shaping the market. One latest trend is the increasing use of AI in clinical trials with companies using generative AI for designing clinical trials, predicting the outcome of clinical trials, and optimizing patient recruitment. Another trend is the use of generative AI in customized medicine where AI is used to identify patients which most likely to benefit from a particular treatment based on their data. Furthermore, there is growing interest in using AI to repurpose existing drugs for new uses which can significantly reduce the cost & time required for drug development. Another latest trend is the use of generative AI for drug manufacturing where AI is used for optimizing drug manufacturing processes, reducing waste, and improving efficiency. Finally, the integration of generative AI into drug discovery workflows is becoming increasingly popular with many companies developing and refining their AI-powered platforms for improving their drug discovery capabilities. Overall, these latest trends show the continued growth & evolution of generative AI in pharma market and are expected to drive significant innovation in the field in the coming years.

Regional Analysis

North America Accounted for the Largest Revenue Share in Generative AI in Pharma Market in 2022.

North America will be the dominant region in the global generative AI in pharma market. It is expected that North America will have the highest revenue share, 45.2%. North America should also register a CAGR of 30.8% over the forecast period. Owing to the presence of several major pharmaceutical companies, research institutions, and technology startups that are developing & implementing AI-powered drug discovery and development platforms. The United States is home to several key players in the market which include Insilico Medicine, Atomwise, and Numerate. The country also has a large and well-established pharmaceutical industry, which has been quick to adopt AI technologies in drug discovery and development.

Asia-Pacific is Expected as Fastest Growing Region in Projected Period in Generative AI in Pharma Market.

APAC is expected as the fastest growing region in the forecast period in the Generative AI in Pharma market with a CAGR of 31.5%. The main reason for the growth is the increasing investment in AI research & development across the region. Several countries in the region including India, Japan, and China are significantly investing in Artificial Intelligence, including in the field of drug discovery & development. Additionally, the growing pharmaceutical industry in the region is driving demand for more efficient & effective drug discovery and development technologies like generative AI.

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Key Regions

• North America
  • The US
  • Canada
  • Mexico
• Western Europe
  • Germany
  • France
  • The UK
  • Spain
  • Italy
  • Portugal
  • Ireland
  • Austria
  • Switzerland
  • Benelux
  • Nordic
  • Rest of Western Europe
• Eastern Europe
  • Russia
  • Poland
  • The Czech Republic
  • Greece
  • Rest of Eastern Europe
• APAC
  • China
  • Japan
  • South Korea
  • India
  • Australia & New Zealand
  • Indonesia
  • Malaysia
  • Philippines
  • Singapore
  • Thailand
  • Vietnam
  • Rest of APAC
• Latin America
  • Brazil
  • Colombia
  • Chile
  • Argentina
  • Costa Rica
  • Rest of Latin America
• Middle East & Africa
  • Algeria
  • Egypt
  • Israel
  • Kuwait
  • Nigeria
  • Saudi Arabia
  • South Africa
  • Turkey
  • United Arab Emirates
  • Rest of MEA

Market Share & Key Players Analysis

The market for generative AI in pharma is still relatively new with a small number of companies operating in the space. However, several of these companies are considered leaders in the field & are likely to play a significant role in shaping the market going forward. Insilico Medicine, Atomwise, BenevolentAI, Numerate, and XtalPi are some of the key players in the market, and each offers their unique AI-powered platforms & services for drug discovery and development. While market share analysis may be limited at this early stage as these companies and others are expected to continue growing in the coming years as the pharmaceutical industry increasingly adopts generative AI technologies for improving the efficiency & effectiveness of drug development.

Market Key Players:

• Insilico Medicine Inc.
• Atomwise Inc.
• BenevolentAI Ltd.
• Numerate Inc.
• XtalPi Inc.
• Berg Health LLC.
• Other Key Players

Recent Developments

• In April 2021, A group of researchers from Stanford University & Novartis published a study in the journal Nature Communications showing how they used generative AI for discovering a new class of antibiotics.
• In March 2021, Exscientia announced a collaboration with Bayer to use its AI platform for accelerating drug discovery for cardiovascular & oncology diseases.
• In January 2021, BenevolentAI announced a partnership with AstraZeneca for using its AI platform to identify potential drug targets & develop new treatments for chronic kidney disease.

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