Overview


Generative AI in pharmaceuticals refers to the use of artificial intelligence, specifically generative models, to assist in various aspects of drug discovery and development. Generative models are a class of AI models that can generate new data samples similar to the training data they were exposed to. Generative models can create virtual chemical compounds that have specific properties of interest. This can speed up the process of finding potential drug candidates. AI can also help design clinical trials, including patient recruitment, protocol design, and data analysis, to make the process more efficient and cost-effective. By leveraging generative AI, pharmaceutical companies aim to accelerate the drug development process, reduce costs, and increase the chances of successfully bringing a new drug to market. Additionally, it can lead to the discovering of novel compounds and formulations that might have been overlooked using traditional methods.

Generative AI, a groundbreaking technology, relies on various technologies to achieve this, including deep learning, natural language processing, querying methods, context-aware processing, and others. Deep learning involves training neural networks on vast amounts of data to enable them to make predictions or generate content independently. This enables the AI system to learn complex patterns and relationships within the data it processes. Natural Language Processing (NLP) is another critical part of generative AI. It empowers the system to understand, interpret, and generate human language in a way that's contextually relevant and coherent. NLP algorithms are designed to comprehend the nuances of language, including syntax, semantics, and even sentiment, allowing the AI to produce text that is not only grammatically accurate but also contextually relevant. Moreover, the querying method is a crucial aspect of generative AI, as it determines how the system interacts with and responds to user input or prompts. This method is responsible for understanding the user's intent and generating a relevant and meaningful response.

FutureWise Market Research has published a report that provides an insightful analysis generative AI in pharmaceutical market trends that are affecting the overall market growth. This report will provide a detailed analysis of market share, regional insights, and competitor analysis that includes stature of key manufacturers operational in this industry. According to the analysis conducted by FutureWise research analysts generative AI in pharmaceutical market estimated to register a considerable growth rate over the forecast period. This report lists the market segments and potential prospects available across this industry, in addition providing crucial information on the total valuation currently held by the industry. Moreover, this report will assist key management individuals in an organisation to enhance their decisions pertaining to business expansion as well as strategic changes for increasing customer base.

  • Bayer AG
  • Insilico Medicine Inc.
  • Atomwise Inc.
  • BenevolentAI Ltd.
  • Numerate Inc.
  • XtalPi Inc.
  • Berg Health LLC
  • Conduent Incorporated
  • Fujitsu
  • OKRA.ai

(Note: The list of the major players will be updated with the latest market scenario and trends)

The increasing prevalence of generative AI's capacity to swiftly analyze extensive datasets and generate potential drug candidates presents a transformative force in drug discovery. By leveraging sophisticated algorithms, it expedites the identification of promising compounds, optimizing the selection process for further research. This acceleration not only streamlines the development pipeline but also promises to yield more effective and safer pharmaceuticals, potentially revolutionizing patient care by expediting the availability of advanced treatments. Moreover, automation and AI-driven processes are formidable cost-saving drivers in pharmaceutical industries. Through streamlined workflows and precise data analysis, they reduce human error, increase efficiency, and expedite decision-making at every stage of drug development. This includes tasks from initial screening to clinical trial design, significantly curtailing resource expenditure. Also, in manufacturing, AI-driven systems may optimize production processes, ensuring higher yields and lower wastage. Therefore, fueling the growth of the target market over the projection period. However, the implementation of generative AI in the pharmaceutical industry poses a challenge in the form of a skilled workforce requirement. This technology demands professionals well-versed in both pharmaceutical sciences and advanced AI methodologies. The lack of such specialized expertise may hinder the seamless integration of generative AI into existing workflows. Also, training existing personnel or hiring new experts comes with associated costs and time investments, potentially acting as a restraint for some companies seeking to adopt this innovative approach.

By Technology

  • Deep Learning
  • Natural Language Processing
  • Querying Method
  • Context-aware Processing
  • Others

By Drug Type

  • Small Molecule
  • Large Molecule

By Application

  • Clinical Trial Research
  • Drug Discovery
  • Research and Development
  • Others

By Region

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

This market research report also emphasis on factors affecting the growth rate in various regions listed above. A deep-down analysis of region will also be provided in the final version of this market which is based on conclusion of primary interviews and secondary data point gathered during the process.

By region, the market is segmented into North America, Latin America, Europe, Asia-Pacific, and Middle East & Africa. North America registered highest revenue share in the market in 2022. The regional growth is driven by several factors, including increasing AI usage in pharmaceutical clinical trials, rising drug discovery and development, rising prevalence of chronic diseases, and technical breakthroughs in the pharmaceutical sector, which are anticipated to propel market growth during the projection period. Also, the presence of major key players and growing business activities such as product launches, partnerships, and collaboration are the key factors further driving the market growth in the region. For instance, in March 2022, Insilico Medicine and EQRx formed a strategic partnership to combine their respective capabilities in de novo small molecule creation, clinical development, and commercialization.

  • Tier 1 players- established companies in the market with a major market share
  • Tier 2 players
  • Emerging players which are growing rapidly
  • New Entrants

  • Growth prospects
  • SWOT analysis
  • Key trends
  • Key data-points affecting market growth

  • To provide with an exhaustive analysis on the Generative AI in Pharmaceutical Market By Technology, By Drug Type, By Application and By Region
  • To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints)
  • To evaluate and forecast micro-markets and the overall market
  • To predict the market size, in key regions— North America, Europe, Asia Pacific, Latin America and Middle East and Africa.
  • To record and evaluate competitive landscape, mapping- product launches, technological advancements, mergers and expansions

  • We have a flexible delivery model and you can suggest changes in the scope/table of content as per your requirement
  • The customization Mobility Care offered are free of charge with purchase of any license of the report
  • You can directly share your requirements/changes to the current table of content to: sales@futurewiseresearch.com

Table of Contents


  • 1.  Market Introduction
    •   1. Objectives of the Study 
        2. Market Definition 
        3. Market Scope 
           3.1. Years Considered for the Study
           3.2. Market Covered
        4. Currency 
        5. Limitations 
        6. Stakeholders 

  • 2.  Research Methodology
    •   1 Research Data 
           1.1. Secondary Data
              1.1.1. Key Data from Secondary Sources
           1.2 Primary Data
              1.2.1. Key Data from Primary Sources
        3.Market Size Estimation 
        4. Market Breakdown and Data Triangulation 
        5. Assumptions for the Study 

  • 3.  Executive Summary
    •   1. Market Outlook
        2. Segment Outlook
        3. Competitive Insights

  • 4.  Generative AI in Pharmaceutical Market Variables, Trends & Scope
    •   1. Market Lineage Outlook
        2. Penetration and Growth Prospect Mapping
        3. Industry Value Chain Analysis
        4. Cost Analysis Breakdown
        5. Application Overview
        6. Regulatory Framework
           6.1. Reimbursement Framework
           6.2. Standards and Compliances

  • 5.  Market Overview
    •   1. Market Dynamics
           1.1. Market Driver Analysis
              1.1.1. Increasing focus of Generative AI in Pharmaceutical Market Companies on Brand Protection
              1.1.2. Untapped Opportunities in Emerging Regions
           1.2. Market Restraint Analysis
              1.2.1. High Cost Associated with Implementation of Predictive Analysis
           1.3. Industry Challenges
              1.3.1. Presence of Ambiguous Regulatory Framework

  • 6.  Generative AI in Pharmaceutical Market Analysis Tools
    •   1. Industry Analysis - Porter’s
           1.1. Supplier Power
           1.2. Buyer Power
           1.3. Substitution Threat
           1.4. Threat from New Entrants
           1.5. Competitive Rivalry
        2. Pestel Analysis
           2.1. Political Landscape
           2.2. Environmental Landscape
           2.3. Social Landscape
           2.4. Application Landscape
           2.5. Legal Landscape
        3. Major Deals And Strategic Alliances Analysis
           3.1. Joint Ventures
           3.2. Mergers and Acquisitions
           3.3. Licensing and Partnership
           3.4. Application Collaborations
           3.5. Strategic Divestments
        4. Market Entry Strategies
        5. Case Studies

  • 7.  Generative AI in Pharmaceutical Market, By Technology Historical Analysis and Forecast 2023-2031 (USD Million)
      1. Deep Learning
      2. Natural Language Processing
      3. Querying Method
      4. Context-aware Processing
      5. Others
  • 8.  Generative AI in Pharmaceutical Market, By Drug Type Historical Analysis and Forecast 2023-2031 (USD Million)
      1. Small Molecule
      2. Large Molecule
  • 9.  Generative AI in Pharmaceutical Market, By Application Historical Analysis and Forecast 2023-2031 (USD Million)
      1. Clinical Trial Research
      2. Drug Discovery
      3. Research And Development
      4. Others
  • 10.  North America Generative AI in Pharmaceutical Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)
    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
           2.1. U.S.A
           2.2. Canada
           2.3. Mexico
        3. Market Size (USD Million) Forecast for North America 2023-2031

  • 11.  Latin America Generative AI in Pharmaceutical Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)
    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
           2.1. Brazil
           2.2. Venezuela
           2.3. Argentina
           2.4. Rest of Latin America
        3. Market Size (USD Million) Forecast for Latin America 2023-2031

  • 12.  Europe Generative AI in Pharmaceutical Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)
    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
           2.1. Germany
           2.2. U.K
           2.3. France
           2.4. Italy
           2.5. Spain
           2.6. Russia
           2.7. Poland
           2.8. Rest of Europe
        3. Market Size (USD Million) Forecast for Europe 2023-2031

  • 13.  Asia Pacific Generative AI in Pharmaceutical Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)
    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
           2.1. Japan
           2.2. China
           2.3. India
           2.4. Australia and New Zealand
           2.5. ASEAN
           2.6. Rest of Asia Pacific
        3. Market Size (USD Million) Forecast for Asia Pacific 2023-2031  

  • 14.  Middle East and Africa Market Analysis 2017-2022 and Forecast 2023-2031 (USD Million)
    •   1. Introduction
        2. Historical Market Size (USD Million) Analysis By Country, 2017-2022
           2.1. GCC
           2.2. Israel
           2.3. South Africa
           2.4. Rest of MEA
        3. Market Size (USD Million) Forecast for MEA 2023-2031

  • 15.  Market Share Analysis and Competitive Landscape
    •   1. Global Landscape - Key Players, Revenue and Presence
        2. Global Share Analysis - Key Players (Tier 1, Tier 2, Tier 3)
        3. Global Emerging Companies
        4. North America - Market Share Analysis and Key Regional Players
        5. Europe - Market Share Analysis and Key Regional Players
        6. Asia Pacific - Market Share Analysis and Key Regional Players
        7. Global Key Player - Growth Matrix

  • 16.  Company Profiles (Competition Dashboard, Competitors Deep Dive, Products Offered and Financial Layouts)
    •   1. Bayer AG
           1.1. Company Overview
           1.2. Product Portfolio
           1.3. SWOT Analysis
           1.4. Financial Overview
           1.5. Strategic Overview
        2. Insilico Medicine Inc.
           2.1. Company Overview
           2.2. Product Portfolio
           2.3. SWOT Analysis
           2.4. Financial Overview
           2.5. Strategic Overview
        3. Atomwise Inc.
           3.1. Company Overview
           3.2. Product Portfolio
           3.3. SWOT Analysis
           3.4. Financial Overview
           3.5. Strategic Overview
        4. BenevolentAI Ltd.
           4.1. Company Overview
           4.2. Product Portfolio
           4.3. SWOT Analysis
           4.4. Financial Overview
           4.5. Strategic Overview
        5. Numerate Inc.
           5.1. Company Overview
           5.2. Product Portfolio
           5.3. SWOT Analysis
           5.4. Financial Overview
           5.5. Strategic Overview
        6. XtalPi Inc.
           6.1. Company Overview
           6.2. Product Portfolio
           6.3. SWOT Analysis
           6.4. Financial Overview
           6.5. Strategic Overview
        7. Berg Health LLC
           7.1. Company Overview
           7.2. Product Portfolio
           7.3. SWOT Analysis
           7.4. Financial Overview
           7.5. Strategic Overview
        8. Conduent Incorporated
           8.1. Company Overview
           8.2. Product Portfolio
           8.3. SWOT Analysis
           8.4. Financial Overview
           8.5. Strategic Overview
        9. Fujitsu
           9.1. Company Overview
           9.2. Product Portfolio
           9.3. SWOT Analysis
           9.4. Financial Overview
           9.5. Strategic Overview
        10. OKRA.ai
           10.1. Company Overview
           10.2. Product Portfolio
           10.3. SWOT Analysis
           10.4. Financial Overview
           10.5. Strategic Overview

  • 17.  Pre and Post COVID-19 Impact
    •   1. Positive influence on the healthcare industry
        2. The financial disruption of the manufacturing sector
        3. Impact of COVID-19 on emerging companies
        4. Significant mandates in the healthcare regulations initiated by administrations
        5. The overall economic slowdown of the developing and developed nations

  • 18.  FutureWise SME Key Takeaway Points for Client
    •   

Partner

Our Clients