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AI in Drug Discovery Market Analysis 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) 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) & Forecast By 2031

  • PUBLISHED ON
  • 2024-07-14
  • NO OF PAGES
  • 231
  • CATEGORY
  • Healthcare & Life Sciences

Market Overview

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.

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

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

Quality Assurance Process

  1. We Market Research’s Quality Assurance program strives to deliver superior value to our clients.

We Market Research senior executive is assigned to each consulting engagement and works closely with the project team to deliver as per the clients expectations.

Market Research Process




We Market Research monitors 3 important attributes during the QA process- Cost, Schedule & Quality. We believe them as a critical benchmark in achieving a project’s success.

To mitigate risks that can impact project success, we deploy the follow project delivery best practices:
  • Project kickoff meeting with client
  • Conduct frequent client communications
  • Form project steering committee
  • Assign a senior SR executive as QA Executive
  • Conduct internal editorial & quality reviews of project deliverables
  • Certify project staff in SR methodologies & standards
  • Monitor client satisfaction
  • Monitor realized value post-project

Case Study- Automotive Sector

One of the key manufacturers of automotive had plans to invest in electric utility vehicles. The electric cars and associated markets being a of evolving nature, the automotive client approached We Market Research for a detailed insight on the market forecasts. The client specifically asked for competitive analysis, regulatory framework, regional prospects studied under the influence of drivers, challenges, opportunities, and pricing in terms of revenue and sales (million units).

Solution

The overall study was executed in three stages, intending to help the client meet its objective of precisely understanding the entire market before deciding on an investment. At first, secondary research was conducted considering political, economic, social, and technological parameters to get a gist of the various aspects of the market. This stage of the study concluded with the derivation of drivers, opportunities, and challenges. It also laid substantial emphasis on understanding and collecting data not only on a global scale but also on the regional and country levels. Data Extraction through Primary Research

The second stage involved primary research in which several market players and automotive parts suppliers were contacted to study their viewpoint concerning the development of their market and production capacity, clientele, and product line. This stage concluded in a brief understanding of the competitive ecosystem and also glanced through the strategies and pricing of the companies profiled.

Market Estimates and Forecast

In the final stage of the study, market forecasts for the electric utility were derived using multiple market engineering approaches. This data helped the client to get an overview of the market and accelerate the process of investment.

Case Study- ICT Sector

Business process outsourcing, being one of the lucrative markets from both supply- and demand- side, has appealed to various companies. One of the prominent corporations based out of Japan approached us with their requirements regarding the scope of the procurement outsourcing market for around 50 countries. Additionally, the client also sought key players operating in the market and their revenue breakdown in terms of region and application.


Business Solution

An exhaustive market study was conducted based on primary and secondary research that involved factors such as labor costs in various countries, skilled and technical labors, manufacturing scenario, and their respective contributions in the global GDP. A comparative study of the market was conducted from both supply- and demand side, with the supply-side comprising of notable companies, such as GEP, Accenture, and others, that provide these services. On the other hand, large manufacturing companies from them demand-side were considered that opt for these services.


Conclusion

The report aided the client in understanding the market trends, including country-level business scenarios, consumer behavior, and trends in 50 countries. The report also provided financial insights of crucial players and detailed market estimations and forecasts till 2033.


Frequently Asked Questions

What is the market size and growth projections?

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.

Who are the key competitors of market Players?

Some of the major players operating within the 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.

What are the top performing segments, and countries / regions of each of the markets?

Geographically, the global AI in drug discovery market is segmented into North America, Latin America, Asia Pacific, Europe, and Middle East & Africa.

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