Artificial Intelligence In Drug Discovery Market Size to Surpass US$ 9.7 BN By 2030

Latest Study on “Artificial Intelligence In Drug Discovery Market Size, Share, Trends, Growth, Production, Consumption, Revenue, Company Analysis and Forecast 2022-2030”.

The global Artificial Intelligence In Drug Discovery market size is expected to be worth around US$ 9.7 billion by 2030, according to a new report by Nova one advisor.

The global Artificial Intelligence In Drug Discovery market size was valued at US$ 1.2 billion in 2021 and is anticipated to grow at a CAGR of 30.4% during forecast period 2022 to 2030.

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The pandemic has made the adoption of AI more widespread in the pharma industry. AI and its related platforms aim to enhance medical imaging and diagnostics, management of chronic diseases, and drug designing. The overall human hours spent would be far more in comparison to the AI system scanning the same data, which reduces overall cost and is a more feasible approach.

The drug optimization and repurposing application segment held the largest revenue share in 2021. AI platforms help in the identification of target proteins for drugs to determine adverse events and possible side effects the drug can have. Drug molecules can be repurposed to make them more effective and with minimum side effects. Portfolio drugs for a company can be altered and studied using AI platforms at a much faster pace so as to hasten new drug development.

The oncology therapeutic area segment accounted for the largest revenue share in 2021. The majority of the pharmaceutical companies are pairing up with AI start-ups to optimize their cancer research, which is still an unchartered territory and there is a lot to be discovered. AI systems can identify cancer much earlier than a regular scan would indicate to even a thoroughly trained radiologist. This, in turn, can increase life expectancy and can also help identify markers to be studied for cancer research and drug development. Patients can be prescribed treatments suited to their genetic composition.

North America dominated the market in 2021. Many tech companies are now investing their money and efforts toward the use of AI in pharmaceutical companies. Companies like IBM, Microsoft, and other tech giants have formed collaborations with research institutes for faster drug development and clinical trials for multiple indications. Developing countries are also finding cost-effective measures to implement AI technology for their drug development and disease understanding.

Report Scope of the Artificial Intelligence In Drug Discovery Market

Key Takeaways:

• By Therapeutic Area, the U.S. Artificial Intelligence In Drug Discovery market was valued at USD 510 million in 2021 and expected to witness growth at a CAGR of 28.9% from 2022 to 2030.

• The drug optimization and repurposing application segment dominated the market and accounted for a revenue share of over 50.0% in 2021
• By therapeutic area, the oncology segment held the largest revenue share of over 20.4% in 2021. The infectious diseases segment is expected to register the fastest growth rate during the forecast period
• Asia Pacific is expected to expand at the fastest CAGR of 32.2% from 2022 to 2030. This can be attributed to the increasing adoption of AI among the developing countries in this region as a means to understand diseases and aid drug discovery
• North America led the market and accounted for a revenue share of over 55.1% in 2021. The U.S. is significantly contributing to the regional market growth as the country has been the forerunner in the artificial intelligence technology

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Therapeutic Area Insights

The oncology sub-segment held the largest revenue share of over 20.4% in 2021. Disease diagnosis is prone to human error, thus using AI systems can prove beneficial in the early detection of diseases. In recent years, AI has become more precise in identifying diseases. Lung cancer is mostly detected at later stages when survival rates become very less, in this scenario, earlier detection with the help of AI systems can prove an asset. A researcher at Northwestern University was able to successfully detect lung cancer in scans where any radiologists would not find anything. AI can be used to provide personalized treatments to patients by improving on the existing AI systems, which are designed to scan through enormous data sets and draw meaningful conclusions. Scans along with genetic sequences and patient histories can be a set pattern to detect cancers early and also to deliver medicine designed specifically for the patients.

The infectious diseases segment is expected to emerge as the fastest-growing application segment from 2022 to 2030. AI and related platforms such as the Internet of Things (IoT) are currently being deployed to understand infectious diseases, their transmission, and infection mechanism, and to improve vaccine design. These platforms use a network of connected devices like smartphones and other medical devices and data collected from these devices can be used for understanding lifestyle patterns and anomalies for studying diseases. In the wake of the current situation, it has become more necessary to develop methods for detecting infectious diseases and how to treat them.

A French start-up Clevy.io launched a chatbot, with information from the French government and the WHO, it was used to assess symptoms of users and direct them to better evaluation of risks, policies formed by the government for COVID, and various other questions related to the disease. This not only lessened the burden on the healthcare institutions but also paved the way to use AI more in terms of how the industry deals with infectious diseases. Many hospitals and institutions around Europe are coming together to use AI for a better diagnosis of COVID-19. They plan to design algorithms to read CT scans by feeding the substantial number of anonymous data from various sources and train the algorithm to detect signs of COVID where radiologists would not be able to identify early signs of the disease based on CT scans.

Application Insights

Based on application, the drug optimization and repurposing segment accounted for the largest revenue share of over 50.2% in 2021. Advanced AI systems such as Deep Learning (DL) and drug modeling can be used to study adverse drug effects and the efficacy of the drug on the whole. The advancements in AI technology have also made it easier for drugs to be studied and compared, for them to be repurposed into more effective forms so that the side effects are minimized and overall efficacy is improved. The pharmaceutical industry is adopting this approach to improve its existing drugs and also use them by altering them for different indications than previously used, which, in turn, reduces the cost of development.

The preclinical testing segment is another application of AI in drug development that is growing at the fastest pace. Manual selection of patients based on their history and suitability for the study can take a lot of time and using AI systems and related technologies can reduce the overall clinical timeline of the drug. Predictive machine learning algorithms can also assist in selecting lead molecules and patient populations based on genome-specific data. Amplion uses its AI platform to carefully choose biomarkers and helps its researchers to recruit appropriate patients and select the right biomarkers, thereby reducing the timeline of clinical studies.

Regional Insights

North America held the largest revenue share of over 55.1% in 2021. Since the beginning of AI, the U.S. has been the forerunner in this technology. IBM used its supercomputer ‘Watson’ to win a trivia game called ‘Jeopardy’, which led to the company improving on the idea of AI since then AI has become a major part of the tech industries and is frequently being deployed on multiple fronts such as the pharmaceutical sector. Major tech giants in the U.S. have all collaborated with prestigious institutes to fast forward drug discovery, designing, and repurposing. They are also using AI to study diseases to come to meaningful conclusions, which will improve disease management.

The APAC market is expected to expand at the fastest CAGR from 2022 to 2030. Developing countries in Asia Pacific are also adopting AI as a means to understand diseases and aid drug discovery. An AI company in India, Intuition Systems has collaborated with Lantern Pharma for drug discovery and biomarker identification. Niramai and Sigtuple are other such AI companies devoted to improving healthcare via faster drug discovery and better identification of target proteins and biomarkers.

Key Companies & Market Share Insights

The need to develop better drugs and do it faster is driving the adoption of AI in the pharmaceutical sector for studying diseases and drug designing as a whole. Major tech giants are taking initiatives for acceleration in the field of drug discovery. The majority of the share in the global market is held by corporations like IBM; Microsoft; Atomwise Inc.; Cloud pharmaceuticals; Benevolent AI; and BIOAGE. Collaborations between Tech companies and academic and research institutes are providing the necessary spurt for the expansion in the use of AI in the pharmaceutical industry as a whole. Better drugs can be formulated with minimum side effects and diseases can be studied in a much faster and much better way so as to find necessary cures with the help of AI and related platforms. Some prominent players in the global artificial intelligence in drug discovery market include:

• IBM Watson
• Exscientia
• GNS Healthcare
• Alphabet (DeepMind)
• Benevolent AI
• BioSymetrics
• Euretos
• Berg Health
• Atomwise
• Insitro
• Cyclica

Segments Covered in the Report

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2017 to 2030. For this study, Nova one advisor, Inc. has segmented the global Artificial Intelligence In Drug Discovery market

• Application Outlook
  • Drug Optimization and Repurposing
  • Preclinical Testing
  • Others
• Therapeutic Area Outlook 
  • Oncology
  • Neurodegenerative Diseases
  • Cardiovascular Diseases
  • Metabolic Diseases
  • Infectious Diseases
  • Others

Regional Segmentation

• Asia-Pacific [China, Southeast Asia, India, Japan, Korea, Western Asia]
• Europe [Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
• North America [United States, Canada, Mexico]
• South America [Brazil, Argentina, Columbia, Chile, Peru]
• Middle East & Africa [GCC, North Africa, South Africa]

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Objectives of the Study

• To define, describe, and forecast the Artificial Intelligence In Drug Discovery market based on type, technology, application, end user, and region
• To provide detailed information regarding the major factors influencing market growth (such as drivers, restraints, opportunities, and challenges)
• To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the total market
• To analyze opportunities in the market for stakeholders and provide details of the competitive landscape for market leaders
• To forecast the size of the market segments with respect to five major regions, namely, North America, Europe, the Asia Pacific, Latin America, and the Middle East and Africa
• To profile key market players and comprehensively analyze their product portfolios, market shares, and core competencies
• To track and analyze competitive developments, such as product launches, expansions, acquisitions, agreements, and collaborations in the Artificial Intelligence In Drug Discovery market

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