Artificial Intelligence (ai) In Drug Discovery Market

The global Artificial Intelligence (ai) In Drug Discovery Market is valued at USD 1.3 Billion in 2022 and is projected to reach a value of USD 7.1 Billion by 2030 at a CAGR (Compound Annual Growth Rate) of 23.72% between 2023 and 2030.

Premium Insights

Drug discovery and development is a cost-intensive and time-consuming process. As per the report, the average costs of discovering and developing novel drug therapies are USD 2.6 billion, and the period of more than 10 years. Early clinical studies are expensive and time-consuming since many possible treatments are discarded owing to a limited testing process.

The COVID-19 pandemic initially has an effect on AI in the market for drug discovery. The identification of prospective therapeutic candidates and the improvement of the drug design for COVID-19 were both made possible by AI. The National Institutes of Health (NIH), known as the National Institute of Allergy and Infectious Diseases (NIAID), awarded over USD 577 million for the establishment of nine Antiviral Drug Discovery (AViDD) Centers for Pathogens of Pandemic Concern. In July 2022, Exscientia entered a collaboration of nearly USD 70 Million for the discovery and development of small molecule therapeutics against Coronavirus.

The application of AI enables researchers to make use of tremendous amounts of data to find new drugs. For instance, a study done by Stanford University researchers showed that AI algorithms were capable of analyzing over 30 million research articles to find new drug targets. This easy access to a multitude of data enables academics to make data-driven decisions and unearth undiscovered insights that could result in ground-breaking findings.

‹›

Report Coverage & Deliverables

PDF report & online dashboard will help you understand:

• Competitive benchmarking
• Historical data & forecasts
• Company revenue shares
• Regional opportunities
• Latest trends & dynamics
• Power BI Report (Dashboard)

Speak To Analyst

AI has the potential to increase drug development success rates. A study published in the journal Nature Biotechnology found that AI algorithms had an accuracy of 80% in predicting the results of clinical trials. The likelihood of bringing successful therapies to market is increased thanks to this predictive power's ability to identify medication candidates who are more likely to succeed.

AI can significantly speed up the drug discovery process. According to data published by IQVIA claims that platforms driven by AI can save the time needed for drug discovery by up to 50%. This indicates that tasks that once required years to complete can now be completed in a fraction of the time.

Key Highlights

• North America generated more than 48.5% of revenue share in 2022.
• Asia Pacific is expected to expand at the fastest CAGR from 2023 to 2030.
• By Application, the Drug Optimization and repurposing segment contributed more than 52.2% of revenue share in 2022.
• By Therapeutic area, the Oncology segment registered more than 35% of revenue share in 2022.
• By the Component, services recorded the most significant market share in 2022.

Economic Insights

AI integration in the drug development sector has compelling economic benefits. In developed nations, such as the United States and European countries, indicating a potential decrease in research and development expenses of up to 70%, there is a potential savings of $100 billion by 2030 for pharmaceutical businesses due to AI-driven technology. The reduction of costly failures is accomplished by effective data analysis, improved trial designs, and the prioritization of promising medication concepts.

According to a study, AI has the potential to speed up the drug development process by up to 30%, providing earlier patient access to life-saving therapies as well as quicker revenue generation. A recent analysis conducted by the Massachusetts Institute of Technology (MIT) found that AI algorithms were able to identify a potential antibiotic candidate in just 46 days, a process that typically takes years using traditional methods. The use of AI in personalized medicine has the potential to improve results and lessen unfavorable side effects by analyzing patient data to create individualized treatment strategies.

Top Market Trends

• Accelerating therapeutic Discovery: By thoroughly analyzing enormous volumes of data and quickly discovering possible therapeutic candidates, AI is accelerating the drug discovery process. This pattern is enabling quicker innovation and better patient outcomes by lowering the time and expense needed to bring new medications to market.

• Precision medicine and personalized treatments: These are made possible by artificial intelligence (AI), which examines genetic information and patient data. As a result of this trend, medications are more effective and have fewer adverse effects since they can be customized depending on a patient's unique traits.
• Combination therapy and drug repurposing: AI systems can find existing medications that might be useful in treating new types of diseases. As a result of this trend, current medications can be repurposed, cutting down on costs and development time while increasing the effectiveness of existing pharmaceutical assets.
• Virtual Screening and Target Identification: AI systems are capable of virtual screening to find new drug candidates and predict their interactions with target proteins from huge chemical libraries. By increasing the effectiveness of target identification and drug discovery, this trend helps to conserve time and resources.
• Regulatory Considerations: AI is used more and more in the drug discovery process, and regulatory bodies are changing to accommodate this technology. Setting up rules and frameworks to guarantee the security, effectiveness, and moral application of AI in drug research is becoming more and more important.

Market Segmentation

The global Artificial Intelligence (ai) In Drug Discovery Market can be categorized into the following segments: Application, Therapeutic Area, Component, and Region.

The Global Artificial Intelligence (ai) In Drug Discovery Market can be segmented by Application, into Drug Optimization & Repurposing, Preclinical Testing, and Other Applications. Furthermore, based on the Therapeutic Area, Artificial Intelligence (ai) In Drug Discovery Market can be segmented into Oncology, Neurodegenerative Diseases, Cardiovascular Disease, Metabolic Diseases, Infectious Diseases, and Other Areas. In addition, based on Component, the market is segmented into Software, Hardware, and Services. Likewise, based on Region, Artificial Intelligence (ai) In Drug Discovery Market is segmented into North America, Europe, Asia Pacific, Latin America, and Middle East & Africa.

Based on Application

Drug optimization and Repurposing hold the largest share

The drug optimization and repurposing category generated the most revenue, with a share of nearly 52.2% in 2022. The efficacy of the drug as a whole, as well as undesirable pharmacological effects, can be studied using advanced Al systems like Deep Learning (DL) and drug modeling. The development of Al technology has also made it simpler to study, compare, and repurpose pharmaceuticals into more efficient versions, reducing adverse effects and increasing overall efficacy. The pharmaceutical industry is using this strategy to enhance its current medications and to make them more useful by changing their original indications, which lowers the cost of development.

Based on the Therapeutic Area

Oncology will dominate the market during Forecast Period

Oncology is expected to dominate the market during the forecasted period. Oncology has been a key area of research and medication development since it focuses on the prevention, diagnosis, and treatment of cancer. Oncology-focused drug development activities have increased as a result of the rising incidence of cancer in the world and the demand for more efficient and individualized treatment choices. The use of AI in oncology drug discovery has produced encouraging results, allowing scientists to analyze intricate biological data, find prospective drug targets, and create novel treatments. As a result, during the projection period, the cancer therapeutic area is anticipated to have notable breakthroughs and market expansion.

Based on Component

Services will dominate Artificial Intelligence (AI) in the Drug Discovery market

Services are anticipated to rule the Artificial Intelligence (AI) market for Drug Discovery based on the component analysis. Services are essential for the deployment and use of AI technology in the drug discovery process. Data analysis, algorithm creation, machine learning, and other AI-related jobs are rapidly being outsourced to AI service providers by pharmaceutical businesses and research institutions by AI service providers. These services facilitate effective model construction, data processing, and result interpretation, assisting researchers in gaining knowledge and making wise choices. The requirement for specialized knowledge, accessibility to cutting-edge AI tools and infrastructure, and the need to optimize the drug development process all contribute to the demand for AI services in the drug discovery market.

Based on Region

North America accounted for the most significant Revenue

Artificial Intelligence (AI) in the drug discovery industry generated the most significant revenue in North America. Due to the region's large concentration of pharmaceutical and biotech enterprises as well as academic institutions, it has been at the forefront of AI research and development. An excellent regulatory environment, a strong infrastructure, and significant investments in AI technology all favor North America. Additionally, the area has a significant concentration of both new and existing firms engaged in AI-driven drug discovery, which promotes innovation and market expansion. The region's dominance in revenue generation in the AI drug discovery market has been fueled by pharmaceutical companies' growing adoption of AI technology and the focus on precision medicine and personalized treatments.

Competitive Landscape

The global Artificial Intelligence (AI) in the drug discovery market is highly fragmented including the presence of numerous pharmaceutical firms, global technology leaders, and small and medium-sized AI startups. Established pharmaceutical businesses are adopting AI technology more frequently, either by building their own internal AI capabilities or working with AI startups. To integrate AI into their drug discovery pipelines, they use their substantial domain expertise, abundant resources, and access to large-scale data. Giant IT companies like IBM and Microsoft are also breaking into the industry with AI platforms and solutions designed specifically for drug discovery. A thriving ecosystem of AI firms dedicated to drug discovery is also present, providing specialized AI tools, media, and services.

Model Medicines, a pharma-tech company, launched its Oncology Program, which is focused on drug discovery and development of anti-cancer drugs that target AXL and BRD4. AI company, CytoReason expanded its multi-year partnership with Pfizer to utilize its AI technology for drug discovery and development.

The key players in the global AI in Drug Discovery market include – IBM Watson (U.S.), Exscientia (UK), GNS Healthcare (U.S.), Alphabet (U.S.), Benevolent AI (UK), BioSymetrics Inc. (Canada), Euretos (Netherlands), Berg Health (U.S.), Atomwise (U.S.), Insitro (U.S.), Cyclica Inc. (Canada) among others.

Recent Market Developments

• In March 2022, NVIDIA Corporation launched Clara Holoscan MGX to develop and deploy real-time AI applications. Clara Holoscan MGX expands the Clara Holoscan platform to provide an all-in-one, medical-grade reference architecture, as well as long-term software support, to accelerate innovation in the medical device industry. This will help the company for better AI performance in the health sector for surgery, diagnostics, and drug discovery.
• In May 2022, Benevolent AI, a leading clinical-stage AI-enabled drug discovery company, announced that AstraZeneca has selected an additional novel target for Idiopathic Pulmonary Fibrosis (IPF) for its drug development portfolio, resulting in a milestone payment to Benevolent AI. This is the third novel target from the collaboration that has been identified using the Benevolent Platform across two disease areas, IPF, and chronic kidney disease, and subsequently validated and selected for portfolio entry by AstraZeneca. This builds upon the recent extension of the collaboration with AstraZeneca to include two new disease areas, systemic lupus erythematosus, and heart failure, signed in January 2022. This has helped the company to make its collaboration stronger.

Segmentation of the Global Market