Machine Learning in Pharmaceutical Industry Market Big Changes to Have Big Impact | Registering a CAGR of 37.9%

The limited data availability is a significant challenge for machine learning applications in the pharmaceutical industry.

PORTLAND, PORTLAND, OR, UNITED STATES, October 16, 2023 /EINPresswire.com/ -- According to the report published by Allied Market Research, the global machine learning in the pharmaceutical industry market garnered $1.2 billion in 2021, and is estimated to generate $26.2 billion by 2031, manifesting a CAGR of 37.9% from 2022 to 2031. The report extensively analyzes changing market dynamics, major segments, value chains, competitive scenarios, and regional landscape. This research offers valuable guidance to leading players, investors, shareholders, and startups in devising strategies for sustainable growth and gaining a competitive edge in the market.

Machine learning is a subset of artificial intelligence that involves the use of algorithms and statistical models to enable computer systems to learn from data and make predictions or decisions without being explicitly programmed. Machine learning is a driving force in the pharmaceutical industry's pursuit of personalized medicine. Personalized medicine involves tailoring treatments to individual patients based on their unique genetic makeup, health history, and other personal factors. Machine learning algorithms can analyze vast amounts of patient data, including genetic data, medical records, and lifestyle factors, to identify patterns and predict how different patients will respond to different treatments.

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Machine learning has significant opportunities in the pharmaceutical industry market, especially in the area of predictive analytics. With the large amounts of data available in healthcare, machine learning algorithms can be trained to identify patterns and make predictions about disease outbreaks and individual patient risks. Machine learning can assist in both the identification of patients who are more likely to respond to a particular treatment and the design of clinical trials that are more effective. In addition, using machine learning to forecast drug safety and effectiveness can lower the likelihood of unfavorable events and guarantee patient safety. Owing to these factors, the use of machine learning services and solutions are expected to increase at a rapid pace and offer ample opportunities to the market players.

Based on region, North America held the largest share in 2021, contributing to nearly half of the global machine learning in the pharmaceutical industry market share, and is projected to maintain its dominant share in terms of revenue in 2031. In addition, the Asia-Pacific region is expected to manifest the fastest CAGR of 42.4% during the forecast period. The report also analyzes the markets in Europe and LAMEA regions.

Based on deployment, the cloud segment accounted for the highest share in 2021, holding more than two-thirds of the global machine learning in the pharmaceutical industry market, and is expected to continue its leadership status during the forecast period. This segment is estimated to grow at the highest CAGR of 40.0% during the forecast period. The report also discusses the on-premise segment.

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On the basis of enterprise size, the large enterprises segment accounted for the highest share in 2021, contributing to around three-fourths of the global machine learning in the pharmaceutical industry market, and is expected to maintain its lead in terms of revenue during the forecast period. Moreover, the SMEs segment is expected to manifest the highest CAGR of 40.1% from 2022 to 2031.

Leading market players of the global machine learning in pharmaceutical industry market analyzed in the research include BioSymetrics Inc., Deep Genomics, Atomwise Inc., NVIDIA Corporation, International Business Machines Corporation, Microsoft Corporation, IBM, Cyclica Inc., Cloud Pharmaceuticals, Inc., and Alphabet Inc.

The report provides a detailed analysis of these key players of the global machine learning in the pharmaceutical industry market. These players have adopted different strategies such as new product launches, collaborations, expansion, joint ventures, agreements, and others to increase their market share and maintain dominant shares in different regions. The report is valuable in highlighting business performance, operating segments, product portfolio, and strategic moves of market players to showcase the competitive scenario.

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Key Findings of the Study;

• Based on component, the solution sub-segment emerged as the global leader in 2021 and the services sub-segment is anticipated to be the fastest growing during the machine learning in the pharmaceutical industry market Forecast period.

• Based on enterprise size, the large enterprises sub-segment emerged as the global leader in 2021 and the SMEs sub-segment is predicted to show the fastest growth in the upcoming years.

• Based on deployment, the cloud sub-segment emerged as the global leader in 2021 and is predicted to show the fastest growth in the ML in the pharmaceutical industry market in upcoming years.

• Based on region, the North American machine learning in pharmaceutical industry market analysis registered the highest market share in 2021 and is projected to maintain its position during the forecast period.

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