AI IN DRUG DISCOVERY MARKET: OVERVIEW
As per Roots Analysis, the global AI in drug discovery market is estimated to grow from USD 1.8 billion in the current year to USD 13.4 billion by 2035, at a CAGR of 16.5% during the forecast period, till 2035.
The market sizing and opportunity analysis has been segmented across the following parameters:
Drug Discovery Steps
- Target identification / validation
- Hit generation / lead identification
- Lead optimization
Therapeutic Area
- Oncological disorders
- CNS disorders
- Infectious diseases
- Respiratory disorders
- Cardiovascular disorders
- Endocrine disorders
- Gastrointestinal disorders
- Musculoskeletal disorders
- Immunological disorders
- Dermatological disorders
- Others
Key Geographical Regions
- North America
- Europe
- Asia-Pacific
- Latin America
- Middle East and North Africa
- Rest of the World
AI IN DRUG DISCOVERY MARKET: GROWTH AND TRENDS
Drug discovery is a complex process that involves significant utilization of time and resources. As per several sources, on average, the entire drug development process (from initial proof-of-concept to commercial launch) takes around 10-15 years and capital investments worth USD 4-10 billion to develop a drug from concept to commercial launch. The early stages, including target discovery and lead molecule identification, play an important role in the success of the drug in both preclinical and clinical studies. Despite the advances in technology and improved understanding of biological systems, the drug discovery process is still considered to be inefficient. In order to optimize the ongoing and future drug development projects, stakeholders are exploring advanced technology solutions (such as artificial intelligence in drug discovery) in order to facilitate better decision-making during the various stages of drug discovery and development.

Artificial intelligence-based tools, such as big data analytics, deep learning, and machine learning help to collect data in real-time with seamless accuracy. This capability aids in reducing clinical failures and ensuring safety during the early stages of development. Notably, over 50% of investments have been made in this domain over the last two years, reflecting a rapid inclination towards AI-based tools for drug discovery and development. In fact, several industry players, namely Pfizer, Sanofi and Genentech, are already using different AI-enabled platforms for internal drug discovery efforts. Considering the ongoing interest and rising adoption of AI in drug discovery, it is anticipated that the market will expand at a steady rate during the forecast period.
AI IN DRUG DISCOVERY MARKET: KEY INSIGHTS
The report delves into the current state of the AI in drug discovery market and identifies potential growth opportunities within the industry. Some key findings from the report include:
- Presently, around 210 players across the globe claim to use AI-based technologies across various steps of the drug discovery and development process.
- Majority of the stakeholders have the required AI-related expertise for lead identification and optimization of drug candidates targeting a range of therapeutic areas.
- Foreseeing the lucrative potential, a large number of players have made significant investments to advance the initiatives of industry stakeholders across multiple funding instances.

- A rise in partnerships focused on research and development of drugs using AI-based technologies validate the growing interest of stakeholders in this market.
- Some players have managed to establish strong competitive positions; in future, we expect multiple acquisitions to take place wherein the relative valuation of a firm is likely to be a key determinant.
- Over 260 patents related to AI-based drug discovery have recently been filed / granted, indicating the growing pace of innovation in this domain.
- The adoption of AI-enabled tools and operational approaches, across different stages of drug discovery and development, is likely to have an impact on R&D expenditure, enabling significant cost savings worldwide.
- The market is expected to grow at a CAGR of 16.5% in the coming years; the opportunity is anticipated to be well distributed across various drug discovery steps, therapeutic areas and regions.
AI IN DRUG DISCOVERY MARKET: KEY SEGMENTS
Lead Optimization Segment Occupies the Largest Share of AI in drug discovery market
Based on the drug discovery steps, the market is segmented into target identification / validation, hit generation / lead identification and lead optimization. At present, the lead optimization segment holds the maximum share of global AI in drug discovery market. Further, the lead optimization segment is likely to grow at a faster pace compared to the other segments.
By Therapeutic Area, Infectious Diseases is the Fastest Growing Segment of the Global AI in Drug Discovery Market During the Forecast Period
Based on the therapeutic area, the market is segmented into oncological disorders, CNS disorders, infectious diseases, respiratory disorders, cardiovascular disorders, endocrine disorders, gastrointestinal disorders, musculoskeletal disorders, immunological disorders, dermatological disorders, and others. Currently, the oncological disorders segment captures the highest proportion of the global AI in drug discovery market. The growth of the oncological disorders segment stems from the widespread adoption of artificial intelligence in oncology to identify targeted therapeutics and biomarkers. Further, it is worth highlighting that the AI in drug discovery market for the infectious diseases segment is likely to grow at a relatively higher CAGR.
North America Accounts for the Largest Share of the Market
Based on key geographical regions, the market is segmented into North America, Europe, and Asia-Pacific, Latin America, Middle East and North Africa and Rest of the World. Currently, North America dominates the AI in drug discovery market and accounts for the largest revenue share. Additionally, the market in Asia-Pacific is likely to grow at a higher CAGR in the future.
Example Players in the AI in Drug Discovery Market
- Aiforia Technologies
- Atomwise
- BioSyntagma
- Chemalive
- Collaborations Pharmaceuticals
- Cyclica
- DeepMatter
- Recursion
- InveniAI
- MAbSilico
- Optibrium
- Recursion Pharmaceuticals
- Sensyne Health
- Valo Health
AI IN DRUG DISCOVERY MARKET: RESEARCH COVERAGE
- Market Sizing and Opportunity Analysis: The report features an in-depth analysis of the global AI in drug discovery market, focusing on key market segments, including [A] drug discovery steps, [B] therapeutic area, and [C] key geographical regions.
- Market Landscape: A comprehensive evaluation of AI drug discovery companies, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] type of company, [E] type of AI technology, [F] type of drug molecule and [G] target therapeutic area.
- Company Profiles: In-depth profiles of key players engaged in the domain of AI in drug discovery, focusing on [A] overview of the company, [B] technology portfolio, and [C] recent developments and an informed future outlook.
- Partnerships and Collaborations: An insightful analysis of the deals inked by stakeholders in the AI in drug discovery market, based on several parameters, such as [A] year of partnership, [B] type of partnership, [C] target therapeutic area, [D] focus area, [E] type of partner company, [F] most active players (in terms of the number of partnerships signed) and [G] geographical distribution of partnership activity.
- Funding and Investments: An in-depth analysis of the fundings raised by AI in drug discovery companies, based on relevant parameters, such as [A] year of funding, [B] amount invested by year, [C] type of funding, [D] amount invested by company size, [E] type of investor, [F] amount invested by type of investor, [G] most active players, [H] most active investors and [I] geographical analysis.
- Patent Analysis: An in-depth analysis of patents filed / granted till date in the AI in drug discovery domain, based on various relevant parameters, such as [A] type of patent, [B] patent application year, [C] patent publication year, [D] geography, [E] CPC symbols, [F] emerging focus area, [G] type of applicant, [H] leading players, [I] patent age, [J] patent benchmarking, and [K] patent valuation analysis.
- PORTER'S Five Forces Analysis: A detailed analysis of the five competitive forces prevalent in AI in the drug discovery market, including [A] threats for new entrants, [B] bargaining power of drug developers, [C] bargaining power of AI-based drug discovery companies, [D] threats of substitute technologies, and [E] rivalry among existing competitors.
- Company Valuation Analysis: An in-depth analysis of the companies engaged in the AI in drug discovery market, based on [A] our proprietary, multi-variable dependent valuation model to estimate the current valuation / net worth of industry players.
- Cost Saving Analysis: An in-depth analysis of the likely cost-saving potential associated with the use of AI in the drug discovery sector, based on various parameters, such as [A] pharmaceutical R&D expenditure, [B] drug discovery expenditure / budget, and [C] adoption of AI across various drug discovery steps.
- Market Impact Analysis: A thorough analysis of various factors, such as drivers, restraints, opportunities, and existing challenges that are likely to impact market growth.
KEY QUESTIONS ANSWERED IN THIS REPORT
- How many companies are currently engaged in this market?
- Which are the leading companies in this market?
- What factors are likely to influence the evolution of this market?
- What is the current and future market size?
- What is the CAGR of this market?
- How is the current and future market opportunity likely to be distributed across key market segments?
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