AI in Drug Discovery Market 2022

Industry Size, Regions, Emerging Trends, Growth Insights, Opportunities, and Forecast By 2030

AI in Drug Discovery Market by Offering (Software, Service), by Technology (Machine Learning, Others), by Application (Cardiovascular, Metabolic, Neurodegenerative), by End User (Pharma, Biotech, and CROs), by Region – Global Share and Forecast to 2030

Region: Global | Format: Word, PPT, Excel | Report Status: Published

According to the Market Statsville Group (MSG), the global AI in drug discovery market size is expected to grow from USD 910.7 million in 2021 to USD 9,072.2 million by 2030, at a CAGR of 29.1% from 2022 to 2030. A machine that uses contemporary technology to carry out tasks that are similar to those carried out by the human mind is referred to as having artificial intelligence (AI). Finding drugs that can help prevent or treat particular diseases is the main goal of drug discovery research. The need for artificial intelligence (AI) in the drug discovery industry was fuelled by the challenges of assessing, acquiring and using data to tackle challenging medical problems.

The increasing usage of cloud-based apps and services by pharmaceutical organizations will help AI flourish in the drug discovery business. Pharmaceutical vendors are projected to be key players among the numerous end-users of cloud-based drug discovery platforms, with a high-value share of the worldwide cloud-based drug discovery platform market. According to a worldwide market potential study, prominent software suppliers have already embraced cloud-based drug discovery systems to promote smooth research and development operations. Furthermore, the cloud-based drug discovery platform revolution will increase significantly in the next years, providing stronger prospects for software companies to grow and expand.

COVID-19 Impact on the Global AI in Drug Discovery Market

As many nations fight to manage the deadly virus, quick medication discovery for COVID-19 might be a help. Lockdowns and strong limits on people's movement have had a detrimental impact, including massive losses for firms in the AI in the drug development sector. However, finding a suitable therapy for COVID-19 patients might be beneficial in various ways. A team of researchers from the University of Michigan utilized an AI-powered picture to find over 17 current medications to lower coronavirus infection in cells. Such tools and techniques aid in finding current medications' effectiveness against COVID-19, contributing to AI's expansion in the drug discovery market.

Global AI in Drug Discovery Market Dynamics

Drivers: Increasing patent protection expiration

The rising relevance of innovative drug development due to the increasing patent expiration of key medications and the increased outsourcing of formulation development services by most pharmaceutical and biotechnological businesses are significant drivers driving market expansion. Most biopharmaceutical businesses collaborate with outsourcing services in the early stages of drug development to mitigate risk and save time and money as the medicine progresses through the development process.

Restraints: AI workforce shortage

AI is a complicated system requiring a workforce with certain skill sets to create, manage, and deploy AI systems. Personnel interacting with AI systems should be conversant and aware of technologies such as machine intelligence, deep learning, cognitive computing, image recognition, and other AI technologies. Additionally, integrating AI technology into current systems is a hard endeavor that demands extensive data processing to emulate human brain activity. Even little faults might cause system failure and negatively affect the desired output. The lack of professional standards and qualifications in AI/ML technologies limits AI's growth.

Opportunities: Mindful AI's Popularity to Provide Huge Opportunities

Mindful AI is quickly becoming an excellent alternative for creating pharmaceuticals in a more human-centric and ethical approach. Mindful AI is an intention-based technique used for producing effective AI-based technology. Pharmaceutical businesses may use conscious AI to learn how rapidly a medicine can be created and how inclusive it is in terms of effectiveness. As a result, the increasing popularity of conscious AI in the pharmaceutical sector will create potential development prospects, propelling the overall AI in the drug discovery market.

Scope of the Global AI in Drug Discovery Market

The study categorizes AI in the drug discovery market based on offering, technology,  end user, and application at regional and global levels.

By Offering Outlook (Sales, USD Million, 2017-2030)

  • Software
  • Services

By Technology Outlook (Sales, USD Million, 2017-2030)

  • Machine Learning
    • Deep Learning
    • Supervised Learning
    • Reinforcement Learning
    • Unsupervised Learning
    • Other Machine Learning Technologies
  • Other Technologies

By End User Outlook (Sales, USD Million, 2017-2030)

  • Pharmaceutical & Biotechnology Companies
  • Contract Research Organizations
  • Research Centers and Academic & Government Institutes

By Application Outlook (Sales, USD Million, 2017-2030)

  • Immuno-Oncology
  • Neurodegenerative Diseases
  • Cardiovascular Diseases
  • Metabolic Diseases
  • Other Applications

By Region Outlook (Sales, USD Million, 2017-2030)

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • Italy
    • France
    • UK
    • Spain
    • Poland
    • Russia
    • The Netherlands
    • Norway
    • Czech Republic
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Indonesia
    • Malaysia
    • Thailand
    • Singapore
    • Australia & New Zealand
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Rest of South America
  • The Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Northern Africa
    • Rest of MEA

Deep learning accounts for the largest market share by technology

Based on the technology, the AI in drug discovery market is divided into machine learning technology and Others. The machine learning technology segment is further sub-segmented into deep, supervised, reinforcement, and unsupervised learning. Deep learning witnessed the highest market share in 2021 due to the consistent management of data, saves time, decreases the likelihood of mistakes in the drug development process, and minimizes the burden for end users, which are some of the important aspects driving the market growth of this segment.

North America accounts for the highest CAGR during the forecast period by Region

Based on the regions, the global AI in drug discovery market has been segmented across North America, Asia-Pacific, Europe, South America, and the Middle East & Africa. North America, being an early adopter of advanced technologies expected to have the highest CAGR. North America is home to several important AI technology suppliers and top startup companies. Other market drivers include the region's well-established pharmaceutical sector, a strong focus on R&D with significant R&D investments, and the strong presence of prominent pharmaceutical firms such as Pfizer (US), Abbott Laboratories (US), and Johnson & Johnson (US).

As a result, such market trends are likely to assist North America in dominating the overall market.

Key Market Players in the Global AI in Drug Discovery Market

The global AI in drug discovery market is highly competitive, with key industry players adopting strategies such as partnerships, product development, acquisitions, agreements, and expansion to strengthen their market positions. Most companies in the market are indulged in expanding business across regions, enhancing their capabilities, and molding strong partner relations.

Major players in the global AI in drug discovery market are:

Key Issues Addressed

  • What is the market size by various segmentation of the AI in drug discovery by region and its respective countries?
  • What are the customer buying behavior, key takeaways, and Porter's 5 forces of the AI in drug discovery market?
  • What are the key opportunities and trends for manufacturers involved in the AI in drug discovery supply chain?
  • What are the fundamental dynamics (drivers, restraints, opportunities, and challenges) of the market?
  • What and how regulations, schemes, patents, and policies are impacting the growth of the market?
  • What are the upcoming technological solutions influencing market trends? How will existing companies adapt to the new change in technology?
  • The market player positioning, top winning strategies by years, company product developments, and launches will be?
  • How has COVID-19 impacted the demand and sales of AI in drug discovery in the global market? Also, the expected BPS drop or rise count of the market and market predicted recovery period.
  • Detailed analysis of the competitors and their latest launch, and what are the prominent startups introduced in the target market? Also, detailed company profiling of 25+ leading and prominent companies in the market.

Frequently Asked Questions

  • Key Issues Addressed
  • What is the market size and growth rate for different segmentations at a global, regional, & country level?
  • What is the customer buying behavior, key takeaways, and Porter's 5 forces of the market?
  • What are the key opportunities and trends for manufacturers involved in the supply chain?
  • What are the fundamental dynamics (drivers, restraints, opportunities, and challenges) of the market?
  • What and how regulations, schemes, patents, and policies are impacting the growth of the market?
  • How will existing companies adapt to the new change in technology?
  • The market player positioning, top winning strategies by years, company product developments, and launches will be?
  • How has COVID-19 impacted the demand and sales of in the market? Also, the expected BPS drop or rise count of the market and market predicted recovery period.
  • Who are the leading companies operating in the market? Also, who are the prominent startups that disrupt the market in coming years?
  • PUBLISHED ON: MARCH, 2024
  • BASE YEAR: 2023
  • FORECAST PERIOD: 2024-2033
  • STUDY PERIOD: 2019 - 2033
  • COMPANIES COVERED: 15
  • COUNTRIES COVERED: 24
  • NO OF PAGES: 216

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