The AI-based drug discovery market is projected to grow at an annualized rate of 25%, during the period 2022-2035, claims Roots Analysis

September 16 00:50 2022
Stakeholders in the pharmaceutical industry are currently exploring the implementation of artificial intelligence (AI) based tools to expedite drug discovery timelines, minimize attrition rates of candidates and reduce capital investments

Roots Analysis has announced the addition of AI-based Drug Discovery Market, 2022 – 2035” report to its list of offerings.

The use of AI-based tools in drug discovery operations is likely to not only improve overall R&D productivity, but also reduce clinical failure with accurate predictions of a drug candidate’s safety and efficacy during the early stages of drug development. As the adoption of AI and machine learning increases amongst innovators in the pharmaceutical industry, lucrative opportunities are expected to be created for players engaged in the AI-based drug discovery market.    

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Key Market Insights 

Over 205 companies claim to offer AI-based drug discovery services / technologiesMajority of the firms (80%) engaged in this domain are small players, followed by mid-sized companies (15%) and large or very large firms (5%). Additionally, more than 50% of the stakeholders were established post 2015. Further, 54% of the players are based in North America; within this region, the US emerged as the most prominent hub, featuring the presence of the maximum number of players.

Around 45 companies offer AI-based drug discovery services / technologies for all three steps of drug discoveryMajority (91%) of the players engaged in AI-based drug discovery market claim to have required expertise in lead identification / optimization / generation. Over 55 stakeholders claim to offer AI-based drug discovery services for both small molecules and biologics. 

Partnership activity within this domain has grown at a CAGR of 50%, between 2015 and 2021Over 375 agreements have been inked in the last 5 years; 65% of the deals were focused on research and development. Other popular types of partnership models adopted by players engaged in this domain include technology access / utilization (10%) and acquisitions (4%).

~11 USD billion has been invested by both private and public investors in this domain, since 2006Specifically, in 2021, industry players raised over USD 4.7 billion. In addition, majority of the companies (66%) primarily received funding through venture capital rounds. Further, around 60% of the total funding instances were reported by players headquartered in the US.

250+ patents related to AI-based drug discovery have been granted / filed between 2019 and 2022R&D activity related to AI-based drug discovery is largely concentrated in North America, considering the fact that 48% of the total number of patents were filed in this region. In addition, most of the patents in this domain are patent applications (91%), followed by granted patents (7%).

An elaborate valuation analysis of companies that are engaged in providing AI-based drug discovery services / technologiesWe have prepared a proprietary, multi-variable dependent valuation model to estimate the current valuation of a number of companies focused on deploying AI-based technologies in the drug discovery and development operations.

Use of AI-based solutions in drug discovery has demonstrated the ability to enable up to 25% cost savings Based on inputs gathered from both secondary and primary sources, the report features an informed and insightful analysis, estimating cost saving potential associated with AI-based solutions. In fact, the adoption of such technologies has the potential to save more than USD 20 billion in drug discovery by 2035.

North America and Europe are anticipated to capture over 85% of the market share, by 2035In addition, the market in Asia Pacific is likely to grow at a relatively faster pace (25%) in the long term. Further, in 2035, the AI-based drug discovery market for oncological disorders is expected to capture the majority share (~38%) of the total market. 

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Key Questions Answered

  • Who are the leading players engaged in the AI-based drug discovery market?
  • Who are the leading players engaged in the AI-based drug discovery market?
  • Which of the key AI technologies are presently being most commonly adopted by drug discovery focused companies?
  • What is the likely valuation / net worth of companies engaged in this domain?
  • What is the likely cost saving potential associated with the use of AI in the drug discovery process?
  • How is the intellectual property landscape for AI-based drug discovery technologies likely to evolve in the foreseen future?
  • Which partnership models are most commonly adopted by stakeholders engaged in this industry?
  • What is the overall trend of funding and investments within this domain?
  • How is the current and future opportunity likely to be distributed across key market segments?

The financial opportunity within the AI-based drug discovery market has been analyzed across the following segments:

  • 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
    • Other Disorders
  • Key Geographical Regions 
    • North America
    • Europe
    • Asia-Pacific
    • Latin America
    • MENA
    • Rest of the World 

The opinions and insights presented in the report were also influenced by discussions held with senior stakeholders in the industry. The report includes detailed transcripts of discussions held with the following experts:

  • Steve Yemm (Chief Commercial Officer, Aigenpulse) and Satnam Surae (Chief Product Officer, Aigenpulse)
  • Ed Addison (Co-founder, Chairman and Chief Executive Officer, Cloud Pharmaceuticals)
  • Bo Ram Beck (Head Researcher, DEARGEN)
  • Simon Haworth (Chief Executive Officer, Intelligent Omics)
  • Immanuel Lerner (Chief Executive Officer and Co-Founder, Pepticom)
  • David Chiang (Chairman, Sage-N Research)

The research includes profiles of key players (listed below); each profile features a brief overview of the company, details related to its AI-based drug discovery technologies, recent developments and an informed future outlook.

  • 3BIGS
  • Aiforia Technologies
  • Atomwise
  • BioSyntagma
  • ChemAlive
  • Collaborations Pharma
  • Cyclica
  • Deep Matter
  • Exscientia
  • Gero
  • Insilico Medicine
  • InveniAI
  • KeenEye
  • MAbSilico
  • Optibrium
  • Recursion Pharmaceuticals
  • Sensyne Health
  • Valo Health

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