AI in Drug Manufacturing Market: Industry Trends and Global Forecasts, Till 2040: Distribution by Type of Offering, Mode of Deployment, Type of AI Solution, Type of Technology, Application Area, Utility in Drug Manufacturing, Geographical Regions and Key Players

The global AI in drug manufacturing market is estimated to grow from USD 0.88 billion in the current year to USD 34.8 billion by 2040, representing a CAGR of 27.8% during the forecast period.

AI IN DRUG MANUFACTURING MARKET: GROWTH AND TRENDS

Artificial Intelligence (AI) is a field of computer science enabling computers to conduct complex tasks that conventionally require human intelligence, such as learning, reasoning and decision making. Recent years have witnessed the integration of AI in pharmaceutical manufacturing to cater to the existing challenges, such as inadequate workflows, equipment downtime, variations in quality, and supply chain disruptions. These inefficiencies can lead to increased costs, production delays, and inconsistencies in product quality. AI can address the above challenges by enhancing process inefficiency, monitoring plant / equipment performance, predicting equipment breakdowns before they occur, supply chain management, and automating quality control.

AI in healthcare is already being utilized across various use cases, including drug discovery, clinical trials, diagnostics, personalized medicine and data management. In pharmaceutical manufacturing, AI leverages technologies such as computer vision, machine learning, generative AI, deep learning to enhance process monitoring, identify bottlenecks, reduce production costs, and increase product yield.

Multiple pharmaceutical firms, including Pfizer, Moderna, Novartis, Merck, and Sanofi, are integrating AI into their production methods as the sector transitions to Pharma 4.0. For instance, Pfizer utilized AI to identify anomalies and suggest immediate actions to operators, aiming to decrease cycle time by 25% and enhance product yield by 10%. It is worth highlighting that the US government initiated the Equip-A-Pharma program, a joint effort spearheaded by the US Department of Health and Human Services (HHS), Administration for Strategic Preparedness and Response (ASPR), and the Defense Advanced Research Projects Agency (DARPA). The initiative includes several private sector collaborators, including Battelle Memorial Institute, Aprecia, BrightPath Laboratories, and Mark Cuban Cost Plus Drug Company. This program seeks to transform pharmaceutical manufacturing in the US through the use of artificial intelligence, machine learning, and informatics.

AI IN DRUG MANUFACTURING MARKET: KEY INSIGHTS

The report delves into the current state of AI in drug manufacturing market and identifies potential growth opportunities within industry. The key takeaways of the report are:

• About 130 companies (established as well as start ups) claim to have the necessary capabilities to offer advanced AI solutions for drug manufacturing; majority of these firms are based in North America.

• 80% of AI solutions in the drug manufacturing industry utilize machine learning, with majority of the solutions focusing on enhancing quality control, consistency, and regulatory compliance.
• In pursuit of gaining a competitive edge and to meet the evolving industry requirements, stakeholders are actively enhancing their existing AI capabilities by improving their respective product portfolios.
• Over 40% of the deals inked in this domain were focused on enhancing AI solutions through product / technology integration agreements; majority of the intercontinental deals were signed by players based in North America.
• In the past few years, over USD 2 billion has been raised by AI solution providers across various funding rounds; of these, ~95% of the total amount was raised by players based in North America.

• AI in drug manufacturing market is experiencing significant growth, driven by the increasing demand for improved process efficiency, coupled with the growing adoption of Pharma 4.0 practices.
• The AI in drug manufacturing market is likely to grow at an annualized rate (CAGR) of 27.8% till 2040; notably, close to 40% of the current market share is likely to be captured by North America.

• More than 35% of the market is anticipated to be captured by revenues generated from AI solutions utilizing computer vision technology; the market for generative AI solutions is likely to grow at a faster pace.
• The US AI in drug manufacturing market is anticipated to be worth 0.30 billion currently, with close to 50 players providing AI solutions for the drug manufacturing industry in this region
• The US AI in drug manufacturing market, driven by robust pharmaceutical manufacturing industry, significant investment activity, and favorable regulatory frameworks, is projected to reach USD 10.3 billion by 2040.

AI IN DRUG MANUFACTURING MARKET: KEY SEGMENTS

Software Segment Dominates the Overall AI in Drug Manufacturing Market During the Forecast Period

In terms of type of offering, the AI in drug manufacturing market is further divided into various sub-segments, such as hardware, software, and services. In the current year, the software segment (45%) is expected to dominate the market and is likely to grow at a higher CAGR (28.4%) during the forecast period. This dominance is propelled by the growing adoption of software-based solutions that integrate advanced methods, including predictive analytics, anomaly detection, generative AI models, and process optimization, thus enhancing operational efficiency and encouraging innovation in drug production.

Cloud-based Solutions Hold the Largest Share of AI in Drug Manufacturing Market

Based on the mode of deployment, the overall market is segmented into cloud-based deployment and on-premise deployment. Currently, cloud-based deployment (62%) holds the higher market share and is likely to grow at a higher CAGR (28.1%) during the forecast period. The higher share can be attributed to its flexibility, ease of deployment, and lower upfront infrastructure costs in comparison to on-premise solutions. Moreover, as regulatory standards continue to facilitate compliance for cloud solutions, the sector is slowly transitioning from on-site infrastructure to hybrid models.

Off-the-shelf AI Solutions to Dominate the Overall AI in Drug Manufacturing Market During the Forecast Period

Based on type of AI solution the global market includes standard / off-the-shelf AI solutions and personalized AI solutions. It is worth mentioning that the standard / off-the-shelf AI solutions hold the higher market share in the current year and are likely to grow at a higher CAGR (30.0%) during the forecast period. This is because the industry favors pre-validated, compliant, and ready-to-deploy solutions that can be deployed and scaled rapidly.

Computer Vision Holds the Largest Share of AI in Drug Manufacturing Market

In terms of type of technology, the global market is segmented across computer vision, deep learning, generative AI, machine learning and other technologies. In the current year, computer vision (36%) holds a higher market share owing to its prompt and broad implementation in automated quality assurance processes, thus gaining considerable momentum throughout the pharmaceutical sector. It is worth highlighting that the market share for generative AI is likely to grow at a relatively higher CAGR (29.9%), during the forecast period, attributing to advanced capabilities of generative AI in healthcare domain, such as in predictive analytics, process optimization and real time insights.

Supply Chain Optimization is Likely to Propel the Market in the Coming Years

This segment highlights the distribution of market across diverse types of applications within the pharmaceutical industry. Our estimates suggest that the quality control segment is likely to capture the majority (36%) of the market in the current year. This is due to its central role in ensuring regulatory compliance and manufacturing precision. It is worth mentioning that the supply chain optimization segment is likely to grow at a relatively higher CAGR (29.1%), during the forecast period.

Defect Defection Segment Holds the Largest Share of AI in Drug Manufacturing Market

This segment involves the distribution of AI in drug manufacturing market across various utilities in drug manufacturing. We anticipate defect detection segment to capture the majority (59%) share of the market in the current year, driven by the sector's significant focus on reducing batch failures and maintaining uniform product quality. It is worth highlighting that the packaging and label inspection segment is likely to grow at a relatively higher CAGR (28.7%), during the forecast period.

Asia-Pacific is Likely to Propel in the Coming Years

Our estimates suggest that North America is likely to capture the majority (39%) of the market in the current year, and this trend is unlikely to change in the future as well. This results from the existence of advanced pharmaceutical manufacturing facilities, the early integration of artificial intelligence (AI) in healthcare technologies, and a favorable regulatory environment throughout the region. It is worth highlighting that the market in Asia-Pacific is expected to grow at a higher CAGR (29.3%).

Example Players in AI in Drug Manufacturing Market

• C3.AI
• AMD
• IBM
• Kalypso
• SAS Institute
• Körber Pharma
• SDG Group
• Catalyx
• Elisa Industriq
• Straive
• Axiomtek
• Appinventiv
• Amplelogic
• Precognize

AI IN DRUG MANUFACTURING MARKET: RESEARCH COVERAGE

The report on AI in manufacturing market features insights into various sections, including:

• Market Sizing and Opportunity Analysis: An in-depth analysis of current market opportunity and the future growth potential of AI in drug manufacturing market, focusing on key market segments, including [A] type of offering, [B] mode of deployment, [C] type of AI solution, [D] type of technology, [E] application area, [F] utility in drug manufacturing and [G] geographical regions.
• Market Landscape: A comprehensive evaluation of companies offering AI solutions for drug manufacturing industry based on several relevant parameters, such as [A] type of offering, [B] type of AI solution, [C] type of technology, [D] type of application, [E] utility in drug manufacturing, [F] year of establishment, [G] company size and [H] location of headquarters.
• Company Competitiveness Analysis: An insightful company competitiveness and benchmarking analysis, based on various relevant parameters, such as [A] supplier strength and [B] portfolio strength.
• Company Profiles: Comprehensive profiles of prominent players engaged in this domain across North America, Europe and Asia-Pacific and rest of the world, featuring information on [A] company overview, [B] financial information (if available), [C] AI solution portfolio, [D] recent developments, and [E] future outlook statements.
• Partnerships and Collaborations: A detailed analysis of partnerships inked between stakeholders in the domain, based on several relevant parameters, such as [A] year of partnership, [B] type of partnership, [C] type of partner, [D] and [G] geography.
• Funding and Investment Analysis: A detailed analysis of the funding and investments raised by AI solution providers with relevant information across parameters, such as [A] year of funding, [B] amount invested, [C] type of funding, and [D] regional distribution.
• Start-up Health Indexing: An in-depth analysis of the various start-ups engaged in the AI in drug manufacturing market, based on relevant parameters, such as [A] portfolio strength, [B] application diversity, [C] utility in drug manufacturing, [D] funding activity and [E] revenue.
• Megatrends Analysis: A qualitative assessment of the various megatrends ongoing in the AI in drug manufacturing industry, including [A] adoption of Pharma 4.0 principles, [B] increasing emphasis on regulatory compliance, [C] transition towards continuous manufacturing, [D] digitization of batch records and manufacturing documentation, [E] shift towards predictive maintenance approach and [F] rise in strategic collaborations and investments.
• Market Impact Analysis: A thorough analysis of various factors, such as [A] drivers, [B] restraints, [C] opportunities, and [D] existing challenges that are likely to impact market growth.

KEY QUESTIONS ANSWERED IN THIS REPORT

• How many companies are currently engaged in this market?
• Which are the leading companies in this market?
• What factors are likely to influence the evolution of this market?
• What is the current and future market size?
• What is the CAGR of this market?
• How is the current and future market opportunity likely to be distributed across key market segments?

REASONS TO BUY THIS REPORT

• The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
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