Artificial Intelligence
Generative AI in Drug Discovery Market Size [+USD 1,129 Mn] | Expands Steadily at a CAGR of 27.1% by 2032
New York, June 13, 2023 (GLOBE NEWSWIRE) — According to MarketResearch.Biz, the generative AI in drug discovery market size is projected to surpass around USD 1,129 million by 2032, and it is poised to reach a CAGR of 27.1% from 2023 to 2032.
The global generative AI in drug discovery market accounted for USD 109 million in 2022. The generative AI in drug discovery market refers to the market for the uses of generative artificial intelligence technologies in the drug discovery process. Generative AI is a type of machine learning that involves the formation of new data like new molecules, based on patterns learned from existing data. In the context of drug discovery, generative AI algorithms can be trained on large databases of known drug molecules and their properties to create new compounds that are predicted to have therapeutic effects. The generative AI in drug discovery market is driven by the maximizing demand for the most efficient & effective price drug discovery processes.
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Key Takeaway:
- By technology, the deep learning segment has dominated the market, and it accounted for the most prominent global revenue of 36% in 2022.
- By end-user, the pharmaceutical and biotechnology segment generated the largest revenue share of 42% in 2022.
- In 2022, North America dominated the market with the highest revenue share of 49%.
- The Asia Pacific region is expected to grow at a significant CAGR from 2023 to 2032.
Factors Affecting the Growth of the Generative AI in Drug Discovery Market
- Increasing Complexity of Drug Discovery: The drug discovery process is coming more complex, requiring advanced tools and techniques to define potential drug candidates. Generative AI supplies a solution by leveraging its ability to operate large datasets, extract complex patterns as well as generate novel molecules with desired properties.
- Advancements in Artificial Intelligence: Continuous advancements in artificial intelligence, including deep learning and machine learning techniques, enhance the capabilities of generative AI in drug discovery. These advancements enable more accurate predictions, efficient optimization, and improved generation of drug candidates.
- Availability of Big Data and Molecular Information: The increasing availability of large-scale datasets and molecular information, such as chemical structures, biological assays, and genomic data, provides a rich resource for training and validating generative AI models. This abundance of data enhances the performance and accuracy of generative AI in drug discovery.
- Collaborations and Partnerships: Collaborations between pharmaceutical companies, AI technology providers, academic institutions, and research organizations drive innovation in generative AI for drug discovery. By combining expertise, resources, and data, these collaborations accelerate the development and adoption of generative AI in the pharmaceutical industry.
- Regulatory Support and Recognition: Regulatory agencies are recognizing the potential of AI-driven technologies in drug discovery and providing support and guidance for their integration into the drug development process. This regulatory support boosts confidence in the use of generative AI and facilitates its implementation.
- Addressing Unmet Medical Needs: Generative AI in drug discovery has the potential to address unmet medical needs by enabling the discovery of new drug candidates for diseases that currently lack effective treatments. This potential to make a significant impact on patient outcomes drives interest and investment in generative AI.
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Top Trends in Global Generative AI in Drug Discovery Market
The use of generative AI in drug discovery is a repeatedly evolving field, and there are a few latest trends that are shaping its development. One trend is the maximized uses of deep learning algorithms, which can analyze larger & the most complex datasets than traditional machine learning algorithms. This has led to enhanced accuracy in predicting potential drug candidates & drug targets. Another trend is the use of generative adversarial networks, which can generate novel compounds that are structurally different from known drugs. This can help to identify new therapeutic pathways and drug classes, leading to the development of more effective treatments. The integration of AI with other technologies like high-throughput screening & lab automation is also a rising trend.
Market Growth
The increasing availability of large-scale datasets, molecular information, and biomedical databases provides a wealth of data for training and validating generative AI models. Integrating diverse data sources with generative AI techniques allows for more comprehensive and accurate drug discovery efforts. Collaborations between pharmaceutical companies, AI technology providers, academic institutions, and research organizations foster innovation in generative AI for drug discovery. These collaborations bring together expertise, resources, and data, driving the development and adoption of generative AI in the pharmaceutical industry. Regulatory agencies are recognizing the potential of AI-driven technologies in drug discovery and are supportive of their application. They provide guidance and frameworks for integrating generative AI into the drug development process, further boosting its adoption and market growth.
Regional Analysis
North America is the leading region in the global Generative AI in Drug Discovery Market. Owing to the presence of leading pharmaceutical companies, a well-established research infrastructure, and a supportive regulatory environment. The United States is the highest market in the region, with significant spending on AI technology for drug discovery & development. Europe is also expected to experience significant growth in the generative AI in the drug discovery market, with a strong emphasis on research & development in the pharmaceutical industry and the availability of government funding for innovative technologies.
Competitive Landscape
The market for generative AI in drug discovery is highly competitive, with a few key players vying for market share. These companies are spending heavily on research & development to develop advanced AI algorithms and expand their product offerings. For example, one of the key players in the market is Insilico Medicine which has developed a deep-learning platform for drug discovery that uses AI to generate and screen potential drug candidates. The company has collaborations with leading pharmaceutical companies and has received significant investment from venture capital firms.
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Scope of Report
| Report Attribute | Details |
| Market Value (2022) | US$ 109 Mn |
| Market Size (2032) | US$ 1129 Mn |
| CAGR (from 2023 to 2032) | 27.1% |
| North America Revenue Share | 49% |
| Historic Period | 2016 to 2022 |
| Base Year | 2022 |
| Forecast Year | 2023 to 2032 |
Market Drivers
The generative AI in drug discovery market is driven by several factors. One of the important drivers is maximizing demand for the most efficient and effective price drug discovery process. The old drug discovery process is consuming time & expensive and often involves the screening of the biggest numbers of compounds that may not be effective. Generative AI has the potential to accelerate the drug discovery process by generating new drug candidates that are optimized for specific properties and are most likely to be effective in treating a particular disease. Another driving factor is the rising availability of bigger datasets of chemical compounds. The pharmaceutical industry is generating wide amounts of data on drug molecules and AI algorithms can be used to analyze this data as well as define new drug candidates.
Market Restraints
Despite the potential advantages of employing generative AI in drug discovery, there are a few restricting constraints that may hinder the rise of this sector. Firstly, the shortage of transparency in AI algorithms can impede securing regulatory approval. Regulators may not fully grasp how the AI systems are developing medication candidates, which might lead to uncertainty & potential safety concerns. In addition, the adoption of AI technology in drug discovery may be constrained by its high cost, especially for smaller biotech & pharmaceutical firms. It can be challenging to acquire and retain the highest quality datasets, which makes the requirement for large volumes of data to train AI models a challenge as well.
Market Opportunities
The pharmaceutical industry will significantly benefit from the application of generative AI in drug discovery. The time and cost of drug research can be considerably reduced by using AI to continually generate and screen prospective therapeutic candidates. It may also result in new options for treating a variety of diseases. Some of these illnesses are difficult to treat or have no cure at all. The usage of AI-generated data assists in discovering medication targets that were previously missed. This leads to the development of new therapeutic paths and drug classes. It may enhance patient outcomes and broaden the range of possible treatments. AI can be used for both personalized medicine and the discovery of new drugs. This is when a patient’s genetic makeup is used to tailor the medicine compositions.
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Report Segmentation of the Generative AI in Drug Discovery Market
Technology Insight
The deep learning segment is dominant in the technology segment in generative AI in the e-commerce market, with a market share of 36%. Owing to Deep learning is a subset of machine learning that focuses on artificial neural networks with multiple layers, enabling the model to learn & extract complex patterns and features from data. It is inspired by the structure & function of the human brain and its interconnected neural networks. Deep learning has gained significant attention & popularity owing to its ability to handle large and high-dimensional datasets and its capacity to automatically learn hierarchical representations of data.
End-User Insight
The pharmaceutical and biotechnology segment dominates the market with a revenue share of 42% in the forecasted period. Pharmaceutical and biotechnology companies are the primary end-users of generative AI in drug discovery. They leverage generative AI technologies to accelerate the drug discovery process, identify new drug candidates, optimize lead compounds, and improve target selection.
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Market Segmentation
Based on Technology
- Machine learning
- Reinforcement learning
- Deep learning
- Molecular docking
- Quantum computing
Based on End-User
- pharmaceutical and biotechnology companies
- academic and research institutions
- contract research organizations (CROs)
- Other End-Users
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
Competitive Landscape
The market is very competitive, with some key players dominating it. Market players adopt various strategic initiatives, such as increasing production capacities and forming technology partnerships to gain an edge.
Market Key Players:
- Insilico Medicine
- Atomwise Inc.
- BenevolentAI
- XtalPi Inc
- Numerate Inc
- Cyclica Inc
- BioSymetrics
- Other Key Players
Recent Development of the Generative AI in Drug Discovery Market
- In April 2021, Insilico Medicine announced that it had generated novel small molecules for a challenging protein target in a matter of weeks using its deep generative models. The company used its AI platform to identify potential drug candidates and then validated them using experimental assays.
- In February 2021, Atomwise announced that it had raised $123 million in a Series B funding round, which it would use to expand its AI platform for drug discovery. The company’s platform has been used to identify potential drug candidates for a variety of diseases, including COVID-19.
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Artificial Intelligence
How AIoT shapes the future of mobility: Hikvision at ITS World Congress 2024
HANGZHOU, China, Sept. 27, 2024 /PRNewswire/ — Hikvision made a significant impact at the ITS World Congress in Dubai with its captivating theme, “Embrace AIoT for safer, smarter, and greener mobility.” Its booth became a hub of innovation, where visitors explored AIoT solutions that are reshaping the transportation landscape, sparking deep conversations on the future of urban mobility.
Road safety revolution: harnessing AIoT for secure transportation
Hikvision’s commitment to road safety was on full display at its booth through the impressive array of AIoT solutions designed to create secure and reliable traffic environments. The company’s technology provides 24/7 traffic monitoring, ensuring continuous oversight of motor vehicles, non-motorized vehicles, pedestrians and environmental factors. This comprehensive, real-time information collection enables traffic managers to prevent accidents and enhance road safety. Among the showcased products was the 20 MP IR ANPR Checkpoint Capture Unit, renowned for its high-definition capture capabilities, bolstering traffic safety measures.
A standout innovation was the integration of advanced radar and camera technologies, ensuring uninterrupted, comprehensive detection even in adverse weather conditions. The Radar-Video Fusion Incident Detection Cameras, featured prominently in the product experience area, enable early detection and warning of potential hazards. They are particularly effective in challenging situations such as curved roads, blind spots at intersections, and obstacles beyond visual range.
Attendees also engaged with onboard monitoring products on the simulated bus, including dome network cameras, which is designed to enhance passenger safety. Driving assistance products, such as the Driver Status Monitor (DSM), were demonstrated to mitigate unsafe driving behaviors and ensure safer journeys.
Urban mobility redefined: smart traffic innovations
In the realm of smarter mobility, Hikvision showcased its multidimensional sensing technology, which integrates visible light sensors, infrared sensors, radar, and sonar. This technology expands perception capabilities, significantly improving traffic management and situational awareness. The use of AI-powered comprehensive sensing elevates incident monitoring and violation detection to unprecedented levels of accuracy and efficiency.
A major attraction was the Radar-Video Fusion TandemVu PTZ Camera, which integrates millimeter-wave radar with high-resolution cameras for extensive traffic detection and data analysis. AI-based algorithms combine these two systems to enhance target information, detecting up to 16 types of incidents. This leads to the development of a large-scale fusion model that merges spatial physical data with image semantic information. The result is ultra-long-range perception, achieving over 95% accuracy in vehicle trajectory detection. This robust system improves traffic violation management and optimizes traffic flow, significantly enhancing road efficiency.
At the simulated bus station, visitors observed how AI-assisted people counting automated the collection of passenger flow statistics at peak stop hours and bus line frequency during busy periods. Paired with smart bus stop digital signage, the solution improves bus service quality, operational efficiency, passenger experience, and overall public transport effectiveness.
Sustainable transportation: leading the charge for greener cities
Hikvision’s commitment to sustainable urban mobility was evident through its innovative green wave technology and eco-friendly checkpoint solutions. Green wave technology efficiently manages traffic flow to reduce congestion and lower carbon emissions, aligning with global sustainability goals. Visitors were particularly impressed by a case study showcasing a green wave solution implemented in Zhoushan, China. Over a stretch of 21 kilometers and 34 intersections, this main road cut travel times by 50%.
The use of DarkFighterX technology in checkpoint cameras also received significant attention. This technology senses both visible and invisible light, resulting in more accurate and realistic images. It enhances traffic violation enforcement efficiency while minimizing the need for high ambient light levels, thus reducing light pollution. The 9M DarkfightX ANPR Checkpoint Camera exemplified this dedication to environmental stewardship.
Frank Zhang, President of Hikvision MEA, remarked, “Hikvision supports sustainable urban planning by empowering traffic departments to address congestion and transportation challenges.” He further emphasized, “Our system’s openness fosters a secure and reliable platform for developing smart and green cities. Additionally, our solar technology is extensively utilized in remote areas, while our smart street lighting solutions reduce energy consumption by 20-30%, promoting intelligent urban transportation and advancing global sustainability objectives.”
Hikvision’s presence at the ITS World Congress in Dubai underscored its leadership in integrating AIoT technologies to drive safer, smarter, and greener mobility solutions. The engaging presentations and advanced product demonstrations captured significant attention from industry partners and customers, reaffirming the company’s role as a pioneer in shaping the future of urban transportation. As the world moves towards more intelligent and sustainable transportation systems, Hikvision remains at the forefront, embracing AIoT to create a safer, smarter, and greener future for all.
To find out more about Hikvision’s advanced traffic and public transport solutions, please explore the Hikvision official website.
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Artificial Intelligence
Anti-Drone Market worth $7.05 billion by 2029 – Exclusive Report by MarketsandMarkets™
DELRAY BEACH, Fla., Sept. 27, 2024 /PRNewswire/ — The global anti-drone market was valued at USD 2.16 billion in 2024 and is projected to reach USD 7.05 billion by 2029; it is expected to register a CAGR of 26.7% during the forecast period according to a new report by MarketsandMarkets™. Increasing government spending on counter-drone technologies, rising incidence of critical infrastructure security breaches by unauthorized drones, and surge in adoption of aerial remote sensing technologies to safeguard critical infrastructure are attributed to the demand for anti-drone.
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Browse in-depth TOC on “Anti-Drone Market” 178 – Tables61 – Figures253 – Pages
Anti-Drone Market Report Scope:
Report Coverage
Details
Market Revenue in 2024
$ 2.16 billion
Estimated Value by 2029
$ 7.05 billion
Growth Rate
Poised to grow at a CAGR of 26.7%
Market Size Available for
2020–2029
Forecast Period
2024–2029
Forecast Units
Value (USD Million/Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
By System Type, Application, Platform type, Vertical, and Region
Geographies Covered
North America, Europe, Asia Pacific, and Rest of World
Key Market Challenge
Vulnerability to hacking
Key Market Opportunities
Emphasis on improving unmanned aircraft systems technology
Key Market Drivers
Growing number of illicit activities
By System Type: Hybrid systems to account for the larger market share in the forecasted year.
The hybrid segment accounted for the largest share of the anti-drone market in 2029. The trends of integrating multiple anti-drone technologies are rising since they are most effective in detecting, tracking, and neutralizing drone threats. These systems merge electronic, kinetic, and lasers, providing a comprehensive defense solution against UAVs. Hybrid systems use electronic, kinetic, and laser-based countermeasures to offer optimum protection against drones. These systems are designed to detect, track, identify, categorize, and mitigate drones at operational wide ranges ranging from a few km up to tens of km.
By Platform: The ground-based segment accounted for the largest market share in the forecast year.
The ground-based segment will hold a major share of the anti-drone market in 2029. Many ground-based anti-drone systems use several electronic technologies, such as radar, IR sensors, acoustic systems, and RF & GNSS jammers. MESA radar solutions are used mostly for counter-UAS purposes, protecting critical infrastructure, military camps, and other security-sensitive sites from unauthorized drones. One such solution is EchoGuard, a ground-based airspace management solution that contains a software-defined 3D radar that can be specific to the site. This system can identify single or multiple off-chance drones, including swarms in unauthorized areas. They provide accurate and sustained airspace surveillance for the field of view (FOV) they are configured, and both human and AI-monitored visual checks. The system can be easily transported and integrated directly with the command-and-control centers or another identification sensor for portable use, and multiple units of the system can be combined to cover vast areas or lengths of borders. Major providers of ground-based counter-drone systems include companies like EchoDyne Corporation, DeTect, Meteksan Defense, and WhiteFox Defense. Acoustics-based Discovair G2 utilizes patented microphone arrays. With 128 interconnected microphone elements, the Discovair sensor units can establish azimuth and elevation to the target in real-time using advanced digital signal processing.
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By Region: Americas are expected to hold the largest share of the anti-drone market during the forecast period.
Americas is expected to capture the largest share in the anti-drone industry during the forecast period. The growth can be attributed to protecting crucial infrastructure in the region. Governments, particularly in the US, invest in anti-drone systems for military bases, borders, and critical infrastructure. For Instance, in April 2023, RTX secured a USD 237 million contract from the US Army to provide Ku-band Radio Frequency Sensors (KuRFS) and Coyote effectors. These systems are designed to detect and neutralize unmanned aircraft systems (UAS). The contract includes stationary and mobile systems and a specified quantity of effectors, all aimed at enhancing the Army’s operations within the US Central Command region.
Key Players-
The key companies offering anti-drone companies include RTX (US), Lockheed Martin Corporation (US), Leonardo S.p.A. (Italy), Thales (France), and IAI (Israel).
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Artificial Intelligence
CluePoints Launches Medical & Safety Review (MSR) Software to Revolutionize Clinical Data Review
CluePoints furthers its commitment to delivering innovative solutions that enhance clinical trial efficiency with this latest addition to its enterprise software platform.
KING OF PRUSSIA, Pa., Sept. 27, 2024 /PRNewswire/ — CluePoints continues to transform clinical trial review and leverage its industry-leading software to enhance the interrogation, analysis and presentation of data with the launch of its latest application, Medical & Safety Review (MSR).
The tool simplifies and streamlines the medical analysis of study data through user-friendly dashboards, data manipulation and cleaning, query management and full transparency over the data history. This not only improves efficiency and communication in medical oversight, but also elevates patient safety, differentiating MSR as a smarter and unique solution.
Designed by, and for Medical and Safety Reviewers, MSR converts the manual analysis of patient outcomes, which can be prone to inefficiency and error, into an accurate, efficient process. MSR tackles time-consuming study preparation for specific visualizations by featuring a comprehensive standard visualization library as well as the ability to copy and reuse dashboards across different studies, enabling the identification of outlying values, change tracking, and improved communication for smarter clinical trials.
Other benefits of MSR include:
Enhanced medical review efficiency and reduced human errors via automated checksReduced time spent by clinical and data management teams in reviewing dataImproved collaboration with integrated review workflows across departmentsEnsured record quality and accountability with comprehensive change trackingDriving faster decision making with the proactive detection of trends and safety issuesEnsuring regulatory compliance with rule-based detection and user assignmentsAndy Cooper, Chief Executive Officer at CluePoints, commented, “We are thrilled to announce the launch of Medical & Safety Review to our growing product offerings. MSR is the latest application addition to the CluePoints platform, which includes products such as Risk-Based Quality Management (RBQM) and our Site Profile & Oversight Tool (SPOT). Together, they provide a comprehensive approach to clinical trial optimization, enhancing data integrity, ensuring regulatory compliance, and accelerating drug development. The creation of MSR ensures a more streamlined review process while prioritizing patient safety at every step and empowers medical teams to swiftly identify outliers, track data changes, and improve communication.”
To learn more about CluePoints’ award-winning solutions, please visit www.cluepoints.com
About CluePoints
CluePoints is the premier Risk-Based Quality Management (RBQM) and Data Quality Oversight Software provider. We are leveraging the potential of Artificial Intelligence using Advanced Statistics and Machine Learning to determine the quality, accuracy, and integrity of clinical trial data both during and after study conduct. Aligned with guidance from the FDA, EMA, and ICH E6 (R2), CluePoints is deployed to support central and on-site monitoring, medical review, quality risk management and to drive a holistic Risk-Based strategy in all trials. Coupled with thought leadership and consulting expertise to aid pre-study risk assessment, identification of risk controls and solution implementation, you now have everything you need to adhere with global regulatory guidance. The result is positive clinical development outcomes, increased operational efficiency, lower costs and reduced regulatory submission risk as part of the industry paradigm shift to RBQM.
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