PORTLAND, Ore., April 20, 2023 (GLOBE NEWSWIRE) — According to a report published by Allied Market Research, Machine learning in the pharmaceutical industry market It is estimated to garner $1.2 billion in 2021 and generate $26.2 billion by 2031, at a CAGR of 37.9% from 2022 to 2031. This report provides extensive analysis of changing market dynamics, key segments, value chains, competitive scenarios, and regional landscapes. The research provides key players, investors, shareholders, and start-ups with valuable guidance in devising strategies for sustainable growth and gaining a competitive edge in the market.
Request a sample report: https://www.alliedmarketresearch.com/request-sample/74979
Report coverage and details
| Report coverage | detail |
| Forecast period | 2022–2031 |
| base year | 2021 |
| Market size in 2021 | $1.2 billion |
| Market size in 2031 | $26.2 billion |
| CAGR | 37.9% |
| number of pages in the report | 280 |
| Target segment | Component, company size, deployment, geography |
| driver | Diverse Applications of Machine Learning to Predict Efficacy and Safety of New Drug Candidates |
| Reducing time and cost in the drug discovery and development process with machine learning | |
| chance | ML is particularly useful in identifying drug candidates that are likely to succeed, potentially reducing the risk of failure during clinical trials. |
| Restraint | High cost and complexity of data collection |
Covid-19 Scenario:
- The COVID-19 pandemic has positively impacted the growth of global machine learning in the pharmaceutical industry market due to the role of machine learning in drug discovery and development. Machine learning algorithms have been increasingly used in drug discovery and development for several years, and the pandemic has accelerated this trend.
- The urgency to find a cure and vaccine for COVID-19 has increased investment in machine learning and artificial intelligence for drug development. Machine learning was used to rapidly analyze large amounts of data related to coronaviruses and potential treatments.
- Virtual trials have become more popular because COVID-19 concerns have made many people unable or unwilling to participate in traditional clinical trials.
The study offers an in-depth segmentation of the global Machine Learning in Pharmaceutical Industry market based on component, company size, deployment, and region. The report details the segment and its subsegments using tables and charts. Market players and investors can strategize according to the highest-earning and fastest-growing segments mentioned in the report.
Procurement Completion Report (280 page PDF, includes insights, charts, tables, and diagrams) and:
https://www.alliedmarketresearch.com/global-machine-learning-in-pharmaceutical-industry-market/purchase-options
Based on components, the solutions segment will hold the highest share in 2021, accounting for more than two-thirds of the global machine learning in the pharmaceutical industry market, and is expected to maintain its leadership position during the forecast period. increase. However, the services segment is expected to register the highest CAGR of 39.5% from 2022 to 2031.
Based on company size, the large enterprise segment is expected to account for the highest share in 2021, contributing nearly three-quarters of the global machine learning in the pharmaceutical industry market, and maintain its lead in terms of revenue during the forecast period. Moreover, the SME segment is expected to exhibit the highest CAGR of 40.1% from 2022 to 2031.
Based on deployment, the cloud segment will account for the highest share in 2021, accounting for more than two-thirds of the global machine learning in the pharmaceutical industry market, and is expected to maintain its leadership position during the forecast period. . This segment is estimated to grow at the highest CAGR of 40.0% during the forecast period. This report also covers the on-premises segment.
Based on region, North America is projected to hold the largest share in 2021, contributing to nearly half of the global machine learning market share in the pharmaceutical industry, and to maintain a dominant share in terms of revenue in 2031. Moreover, the Asia-Pacific region is expected to exhibit the fastest CAGR of 42.4% during the forecast period. The report also analyzes the markets in Europe and his LAMEA region.
Key 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, cycloica inc., Cloud Includes Pharmaceuticals, Inc. , and Alphabet Inc.
Pre-purchase inquiries: https://www.alliedmarketresearch.com/purchase-enquiry/74979
The report offers an in-depth analysis of these major players of the global Machine Learning in Pharmaceutical Industry market. These players are adopting various strategies such as new product launches, collaborations, expansions, joint ventures and agreements to grow their market share and maintain dominant shares in various regions. . The report helps showcase the competitive scenario by highlighting the business performance, business segments, product portfolios, and strategic moves of market players.
about us
Allied Market Research (AMR) is the full-service market research and business consulting arm of Allied Analytics LLP, based in Portland, Oregon. Allied Market Research provides unparalleled quality “market research reportAMR has a targeted view to provide business insight and consultancy to help clients make strategic business decisions and achieve sustainable growth in their respective market domains. I have.
We have professional corporate relationships with various companies that help us dig into market data, generate accurate research data tables and help ensure the highest accuracy in our market forecasts. Pawan Kumar, CEO of Allied Market Research, is committed to inspiring and encouraging everyone associated with the company to maintain high quality data and help our clients succeed in every way possible. increase. All data presented in the reports we publish are extracted through primary interviews with the heads of major companies in the domain concerned. Our secondary data sourcing methods include in-depth online and offline research and discussions with knowledgeable industry experts and analysts.
