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Germany Generative AI in Chemical Market Assessment, By Model [Deep Learning, Natural Language Processing, Discriminative Model, Reinforcement Learning, Others], By Application [Complex Structure Predictions, Novel Formulation Optimization, Chemical Process Optimization, Real-time Equipment Monitoring, Production Capacity Optimization, Pricing Optimization, Laboratory Automation, Others], By End-user [Chemical Processing Industry, Research & Development, Others], By Region, Opportunities and Forecast, 2016-2030F
Market Report I 2024-04-19 I 84 Pages I Market Xcel - Markets and Data
Germany Generative AI in Chemical Market size was valued at USD 31.2 million in 2022, which is expected to reach USD 161.3 million in 2030 with a CAGR of 22.8% for the forecast period between 2023 and 2030. The revolution brought up by generative AI can be recognized substantially in various sectors, including chemical operations. The incredible potential of generative AI models can generate novel molecules with significant implications for drug development, materials selection, and optimizing different chemical operations. Generative AI models develop underlying patterns among humongous datasets comprising molecular structures, their properties, and reactions.
Insilico Medicine has developed a generative AI model Chemistry42, providing solutions to Merk KGaA, Germany - a drug development company. The customized Chemistry42 v1.0 has successfully integrated Merk's state-of-the-art high-performance computing (HPC) infrastructure to facilitate effective and rapid drug design. Generative AI has opened various opportunities through collaborations between AI-driven and drug companies, revolutionizing the chemical sector and generating market potential in Germany.
Chemical Manufacturing Process Using Generative AI
Conventional chemical operations are very tedious and complex, requiring constant quality monitoring and supervision. The incorporation of AI and ML technologies has significantly provided solutions to the problems encountered by chemical manufacturers. Generative AI models has produced solutions for several problems such as downtime on processing line, unstable along with compromised quality, low or fluctuating yields, energy optimization, etc.
Generative AI tools can optimize operating conditions by minimizing the input (energy cost reduction, compositional requirements, etc.) while maximizing the outputs. Available data from previous operations are considerably important as they better understand the ongoing process and on implementing relevant AI models assist in predicting future scenarios. Smart manufacturing with generative AI models enables product optimization through improved throughput, yields, and safety concerns. Undesirable substances even in a minimum quantity can contaminate the entire batch operations quickly. Generative AI models can identify such harmful carriers and prevent them from progressing through the production line. Nexocode's AI solutions assist in predicting and identifying the operational equipment that requires any maintenance and schedule the work accordingly. The importance of generative AI in processing industries can be recognized which deliver phenomenal solutions and can create tremendous market opportunities for AI-driven companies in Germany.
Retrosynthesis using Generative AI
Retrosynthesis a prominent process that assist in creating potential drugs using desired molecules that target specifically and reversibly tracing the chemical reactions for obtaining that specific molecule. The reaction is very challenging and time-consuming, making it difficult to discover such molecules and reaction pathways. A tool named G2Retro is developed using generative AI, it automatically generates chemical reactions which can assist in accelerating the drug development process. G2Retro AI model is trained on 40,000 chemical reactions. The model takes input as a graphical representation of each molecule and implements deep neural networks to identify novel potential chemical structures to synthesize the molecule.
The generative AI G2Retro tool was tested to predict the reactant configuration of four existing drugs Oteseconazole, Mitapivat, Tapinarof, and Mavacamten. The tool successfully generated the patented synthesis routes required for this drug development and provided feasible alternative synthesis routes. The corresponding AI tool can significantly generate hundreds of retrosynthesis predictions within minutes compared to conventional human analysis. This innovative technology is going to develop infrastructure for lab experiments to increase the accuracy of reaction predictions in drug development. The market-based opportunities can be derived for generative AI models in the molecule discovery that ultimately enhance the revenue for AI-driven techies.
Impact of COVID-19
The COVID-19 pandemic has inadvertently affected tech companies across Germany and many European countries. The development of AI technologies has aggravated where companies back-dropped from investing in generative AI. The disruptions in chemical practices and its supply chains during the pandemic led to an aggravation in innovation and shut down of relevant R&Ds. The giant chemical companies always encouraged AI companies and startups to collaborate with them and provide automation to their processing units. On a contrary negative impact of COVID-19 compensated by measures adopted by innovative companies across chemical domain. This significantly unveiled European markets to develop more opportunities in generative AI to generate decisive growth.
Impact of Russia-Ukraine War
The annexation of Russia on Ukraine has unprecedently led to various sanctions on Russia restricting its trade with the other countries. Germany has imposed different legal sanctions on Russia such that it could reduce the imports from Russia. Consequently, it has impacted negatively exports of Germany AI technologies including AI-inbuilt chips. Generative AI models in chemicals significantly troubled in terms of developing more innovations and built proper automation for chemical practices and drug discoveries. But with the developed smoothness with time the market for AI technologies can create great potential to expand its innovative models in the chemical industry.
Key Players Landscape and Outlook
The advancement in AI and ML has revolutionized various sectors and encouraged AI-driven companies to explore solutions using generative AI. Merck KGaA has leveraged generative AI models to discover novel drugs by exploring huge chemical space and significant parameters. Company's new AIDDISON drug discovery software, an AI-generative tool harnessing the technology of AI, ML, and CADD methods that assist in the virtual screening of large chemical spaces resulting in novel development. Another developed model SYNTHIA, a retrosynthesis software that helps predict optimal reaction steps for determining the novel chemical drug. The company has progressively integrated generative AI software that assists in accelerating drug discovery and evaluation of specific molecules. The generative AI market in chemicals has tremendous potential to grow in Germany by motivating more companies to generate significant solutions.
1. Research Methodology
2. Project Scope & Definitions
3. Impact of COVID-19 on Germany Generative AI in Chemical Market
4. Impact of Russia-Ukraine War
5. Executive Summary
6. Voice of Customer
6.1. Market Awareness and Product Information
6.2. Brand Awareness and Loyalty
6.3. Factors Considered in Purchase Decision
6.3.1. Brand Name
6.3.2. Quality
6.3.3. Quantity
6.3.4. Price
6.3.5. Product Specification
6.3.6. Application Specification
6.3.7. Availability of Product
6.4. Frequency of Purchase
6.5. Medium of Purchase
7. Germany Generative AI in Chemical Market Outlook, 2016-2030F
7.1. Market Size & Forecast
7.1.1. By Value
7.1.2. By Volume
7.2. By Model
7.2.1. Deep Learning
7.2.1.1. Variational Autoencoders
7.2.1.2. Generative Adversarial Networks
7.2.1.3. Others
7.2.2. Natural Language Processing
7.2.3. Discriminative Model
7.2.4. Reinforcement Learning
7.2.5. Others
7.3. By Applications
7.3.1. Complex Structure Predictions
7.3.2. Novel Formulation Optimization
7.3.3. Chemical Process Optimization
7.3.4. Real-time Equipment Monitoring
7.3.5. Production Capacity Optimization
7.3.6. Pricing Optimization
7.3.7. Laboratory Automation
7.3.8. Others
7.4. By End-user
7.4.1. Chemical Processing Industry
7.4.1.1. Food
7.4.1.2. Pharma
7.4.1.3. Others
7.4.2. Research & Development
7.4.3. Others
7.5. By Region
7.5.1. Northwest
7.5.2. Southwest
7.5.3. South
7.5.4. East
7.6. By Company Market Share (%), 2022
8. Supply Side Analysis
8.1. Capacity, By Company
8.2. Production, By Company
8.3. Operating Efficiency, By Company
8.4. Key Plant Locations (Up to 25)
9. Market Mapping, 2022
9.1. By Model
9.2. By Application
9.3. By End-user
9.4. By Region
10. Macro Environment and Industry Structure
10.1. Supply Demand Analysis
10.2. Import Export Analysis - Volume and Value
10.3. Supply/Value Chain Analysis
10.4. PESTEL Analysis
10.4.1. Political Factors
10.4.2. Economic System
10.4.3. Social Implications
10.4.4. Technological Advancements
10.4.5. Environmental Impacts
10.4.6. Legal Compliances and Regulatory Policies (Statutory Bodies Included)
10.5. Porter's Five Forces Analysis
10.5.1. Supplier Power
10.5.2. Buyer Power
10.5.3. Substitution Threat
10.5.4. Threat from New Entrant
10.5.5. Competitive Rivalry
11. Market Dynamics
11.1. Growth Drivers
11.2. Growth Inhibitors (Challenges, Restraints)
12. Key Players Landscape
12.1. Competition Matrix of Top Five Market Leaders
12.2. Market Revenue Analysis of Top Five Market Leaders (in %, 2022)
12.3. Mergers and Acquisitions/Joint Ventures (If Applicable)
12.4. SWOT Analysis (For Five Market Players)
12.5. Patent Analysis (If Applicable)
13. Pricing Analysis
14. Case Studies
15. Key Players Outlook
15.1. Merck KGaA
15.1.1. Company Details
15.1.2. Key Management Personnel
15.1.3. Products & Services
15.1.4. Financials (As reported)
15.1.5. Key Market Focus & Geographical Presence
15.1.6. Recent Developments
15.2. AI Superior
15.3. InstaDeep
15.4. Nexocode
15.5. Innophore GmbH
15.6. Aleph-Alpha
15.7. Unit8
15.8. Syntelly
15.9. Iktos
15.10. Biomatter
*Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work
16. Strategic Recommendations
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