Artificial Intelligence (AI) In Drug Discovery Market Growth Is Driven At A 30% Rate With Increasing Adoption Of Cloud-Based Applications And Services As Per TBRC’s Artificial Intelligence (AI) In Drug Discovery Global Market Report 2022

TBRC Business Research PVT LTD

TBRC Business Research PVT LTD

TBRC’s market research report covers artificial intelligence in drug discovery market size, AI in drug discovery market forecasts, major AI in drug discovery companies and their market share, key strategies to undertake, and more.

LONDON, May 24, 2022 (GLOBE NEWSWIRE) — According to The Business Research Company’s research report on the artificial intelligence (AI) in drug discovery market, the rising adoption of cloud-based applications and services by pharmaceutical companies will contribute to the growth of AI in the drug discovery market. Among the various end-users of cloud-based drug discovery platforms, pharmaceutical vendors are likely to be major stakeholders, holding a high-value share of the global cloud-based drug discovery platform market. An opportunity analysis of the global market reveals that leading software vendors have already adopted cloud-based drug discovery platforms to facilitate seamless research and development processes. Moreover, the cloud-based drug discovery platform revolution will witness significant growth in the coming years, thereby creating better opportunities for software vendors for growth and expansion. For example, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced in December 2021 that it is collaborating with Pfizer to develop innovative, cloud-based solutions that have the potential to improve how new medicines are developed, manufactured, and distributed for clinical trials. The companies are exploring these advances through their newly created Pfizer Amazon Collaboration Team (PACT) initiative, which applies AWS capabilities in analytics, machine learning, compute, storage, security, and cloud data warehousing to Pfizer laboratory, clinical manufacturing, and clinical supply chain efforts. Thus, the increasing adoption of cloud-based applications and services by pharmaceutical companies will contribute positively to the AI ​​drug discovery market size.

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The global artificial intelligence in drug discovery market size is expected to grow from 0.79 billion in 2021 to $104 billion in 2022 at a compound annual growth rate (CAGR) of 31.6%. The growth in the market is mainly due to the companies resuming their operations and adapting to the new normal while recovering from the COVID-19 impact, which had earlier led to restrictive containment measures involving social distancing, remote working, and the closure of commercial activities that resulted in operational challenges. The AI ​​in drug discovery market is expected to reach $299 billion in 2026 at a CAGR or 30.2%.

Use of AI through Machine Learning (ML) is a trend in assessing pre-clinical studies during the drug development process. Pre-clinical studies are non-clinical studies for novel drug substances to establish clinical efficacy and safety in a controlled environment before testing with a final target population. ML modeling pharmacokinetic (PK) and pharmacodynamic (PD) methodologies are applied in in-vitro and preclinical PK studies to successfully anticipate the dose concentration response relationship of pipeline assets. In addition, deep learning methodologies are employed as ‘In-Silico’ methods for successfully predicting the therapeutic/pharmacological properties of novel molecules by utilizing transcriptomic data, which includes various biological systems and controlled conditions. Besides the drug discovery market, machine learning technology finds its application in the AI ​​in medical diagnostics market as well as AI in medical imaging market.

Major players in the artificial intelligence for drug discovery and development market are IBM Corporation, Microsoft, Atomwise Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, Benevolent AI, Exscientia, Cyclica, and BIOAGE.

The global artificial intelligence in drug discovery market report is segmented by technology into deep learning, machine learning; by drug type into small molecule, large molecules; by disease type into metabolic disease, cardiovascular disease, oncology, neurodegenerative diseases, others; by end-users into pharmaceutical companies, biopharmaceutical companies, academic and research institutes, others.

2021, North America was the largest region in the artificial intelligence (AI) in drug discovery market. It was followed by the Asia-Pacific, Western Europe, and then the other regions. The regions covered in the AI ​​in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, and Africa.

Artificial Intelligence (AI) In Drug Discovery Global Market Report 2022 – Market Size, Trends, And Global Forecast 2022-2026 is one of a series of new reports from The Business Research Company that provide artificial intelligence (AI) in drug discovery market overviews, artificial intelligence (AI) in drug discovery market analyze and forecast market size and growth for the whole market, artificial intelligence (AI) in drug discovery market segments and geographies, artificial intelligence ( AI) in drug discovery market trends, artificial intelligence (AI) in drug discovery market drivers, artificial intelligence (AI) in drug discovery market restraints, artificial intelligence (AI) in drug discovery market leading competitors’ revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.

The report also gives in-depth analysis of the impact of COVID-19 on the market. The reports draw on 150,000 datasets, extensive secondary research, and exclusive insights from interviews with industry leaders. A highly experienced and expert team of analysts and modelers provides market analysis and forecasts. The reports identify top countries and segments for opportunities and strategies based on market trends and leading competitors’ approaches.

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