In 2021, the market for AI in Drug Discovery worldwide was worth $0.8 billion US dollars. AMR Group projects that the market will reach US$ 9 billion by 2031, growing at a CAGR of 40 percent between 2022 and 2031.
Industry Overview
Artificial Intelligence (AI) has grabbed the attention of medical practitioners and lab technicians. In the past few years, many companies and leading research laboratories have worked and perfect these technologies for clinical uses and trials. The commercialized demonstrations of how Artificial Intelligence, also known as Machine Learning, Deep Learning, or Artificial Neural Networks (ANNs) could assist physicians are now available in the market. These systems could lead to a paradigm shift in physician’s workflow and increase the productivity along with the enhancing treatment & patient output. AI for drug discovery is a technology that uses machines to simulate human intelligence in solving the complicated challenges of drug development procedures. The acceptance of AI solutions in the clinical trial process eliminates possible obstacles. It also reduces clinical trial cycle time and enhances the productivity and accuracy of the clinical trial process. Moreover, to this the acceptance of advanced AI solutions in drug discovery processes is influencing amongst life science industry stakeholders. In the pharmaceutical sector, it helps in the discovery of novel compounds, therapeutic target identification and the development of customized medications. AI platforms used for drug discovery can prove to be a feasible option for deriving insights into the discovery of drugs in the treatment and lowering the severity of various chronic diseases.
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The AI in drug discovery Market tends to grow due to a rising in cross industry agreements and collaborations drives the market. Increasing relevance of AI in drug discovery & development and a rise in investments for R&D activities boosts the market growth. Additionally, AI technology in the field of drug research are expected to increase the global market growth.
Market Dynamics
Digitalization in clinical research spaces and biomedical are creating a way for the implementation of AI solutions. The large amount of data base is generated from drug discovery processes such as preclinical studies and molecule screening phase are increasing the adoption of AI-powered solutions. For instance, a University of Michigan, researchers team have used an AI-powered image to identify over 17 existing drugs to reduce coronavirus infection in cells during the period of time.
Rising incidences of chronic diseases initiates, the need for AI in drug discovery. The incidence of chronic diseases is rising at a faster rate around the globe. According to the Centers for Disease Control and Prevention (CDC), six out of ten adults in the U.S. have a chronic disease, and four out of ten adults have two or more at the same time. The importance of AI in oncology is estimated to offer high growth opportunities. AI helps the researchers and physicians to understand how cancer cells become resistant to anticancer drugs, further leading to drug development and adjust drug use. However, the healthcare sector is facing complex challenges, including the increased cost of drugs & therapies and patients’ needs specific significant changes in this area. The entire success of AI depends on the availability of a substantial amount of data because these data are used for the subsequent training provided to the system enabling high cost associated with technology & technical limitations.
COVID Impact
The AI in drug discovery market has shown a positive impact during the COVID-19 pandemic period. The COVID-19 outbreak has highly impact on the expansion of AI in drug discovery industry due to its wider and different uses by various organizations for the identification and screening of existing medicines used in the COVID-19 treatment. AI is useful in detecting active chemicals for the prevention of SARS-CoV, SARS-CoV-2, HIV, influenza virus and others. During the pandemic, investors all over the globe depended on AI-based medication discovery more than traditional vaccine detection processes. Helping to reduce the years to create and are of similar expense contributing to the market growth. Manufacturers are making different strategies to bounce back post-COVID-19.
Regional Trend
Geographically, the global AI in drug discovery market is segmented into North America, Latin America, Asia Pacific, Europe, and Middle East & Africa. North America is dominating the largest share of the global AI in drug discovery market with a share of 53% in 2021. Moreover, Asia Pacific is lined up to register the highest CAGR during the forecast period. The growth in the market in Asia-Pacific is driven by collaborations and partnerships between the countries for establishing AI in drug discovery facilities. Growing awareness programs for an increase in the R&D expenditure. The rise in different medical conditions, such as the rising prevalence of chronic diseases and population among countries such as China & India that require the use of AI in drug discovery products. Also the increasing geriatric population in the Asia Pacific region contributes to the market growth.
Competitive Landscape
Key players operating in the global tissue diagnostics market are Alphabet (DeepMind), Aria Pharmaceuticals, Inc., Atomwise Inc., Benevolent AI, BERG LLC, BIOAGE Inc., BioSymetrics, Cloud, Cyclica, DEEP GENOMICS, Envisagenics, Euretos, Exscientia, GNS Healthcare, IBM Corp., Insilico Medicine, Insitro, Microsoft, NuMedii, Inc., NVIDIA Corporation, Owkin Inc., Schrödinger, Inc., and XtalPi Inc. among others. In March 2022, NVIDIA Corporation launched Clara Holoscan MGX to develop real-time AI applications. Clara Holoscan MGX extends the Clara Holoscan platform to provide, long-term software support and medical-grade reference architecture, to encourage the innovation in the medical device industry. This will help the company for better AI performance in health sector for diagnostics, surgery, and drug discovery.
Key USP’s-
AI has the potential to transform drug discovery by rapidly increasing the R&D, making drug development faster, cheaper and improving the probability of approvals. AI can also help in increasing the effectiveness of drug repurposing research.
Market Segmentation
Based upon the Drug Type used in AI in drug discovery Market is segmented into two segments of Small Molecule and Large Molecule in the drug discovery process. Based on Indication, the AI in drug discovery Market is segmented into Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases. Based on Component, the AI in drug discovery Market is segmented into Software, Hardware and Services. Based on application, the AI in drug discovery Market is segmented into novel drug candidates, drug optimization and repurposing preclinical testing and approval, drug monitoring, finding new diseases associated targets and pathways, understanding disease mechanisms, aggregating and synthesizing information, formation & qualification of hypotheses, de novo drug design, and finding drug targets of an old drug. In this segments, the drug optimization and repurposing segment accounted for the largest revenue share of over 50.0% in 2021 to dominate the largest share of the AI in drug discovery market.
Based on technology, the AI in drug discovery Market is segmented into Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP). End user segment of AI in drug discovery market is further classified into pharmaceutical & biotechnology companies, Contract Research Organizations (CROs), research centers and academic institutes. The increasing healthcare expenditure is some of the major factors driving the growth of this segment.
By Drug Type
• Small Molecule
• Large Molecule
By Indication
• Immuno-Oncology
• Neurodegenerative Diseases
• Cardiovascular Diseases
• Metabolic Diseases
By Component
• Software
• Hardware
• Services
By Application
• Novel Drug Candidates
• Drug Optimization and Repurposing Preclinical Testing and Approval
• Drug Monitoring
• Finding New Diseases Associated Targets and Pathways
• Understanding Disease Mechanisms
• Aggregating and Synthesizing Information
• Formation & Qualification of Hypotheses
• De Novo Drug Design
• Finding Drug Targets of an Old Drug
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By Technology
• Machine Learning (ML)
• Deep Learning (DL)
• Natural Language Processing (NLP)
By End User
• Pharmaceutical & Biotechnology Companies
• Contract Research Organizations (CROs)
• Research Centers and Academic Institutes
Key Questions answered with an analysis in this report:
- What are the current market trends? Will there be an increase or decrease in market demand in the following years?
- Which product categories are expected to have the highest demand? What kind and applications might we expect in the future?
- What Economic Predictions are Available for the Industry Considering Capacity, Production, and Production Value?
- Which costs and profits are projected? What Will the Market Share, Consumption, and Supply Be? How do imports and exports operate?
- In light of the strategic advancements, where will the industry be in the mid- to long-term?
- What are the primary raw materials employed in the production?
- What is the value of the global market? How much was the market worth in 2022?
- Which companies are the main players in the market? Which businesses are leading the pack?
- What are the current business trends that can be used to create new sources of income?
- What Entry Strategies, Economic Impact Countermeasures, and Marketing Channels Should the Industry Use?
