Artificial Intelligence (AI) in Drug Discovery Market Growing at a CAGR of 45.7% - Research Provides Detailed Analysis of Trends, Growth and Forecast

The AI in Drug Discovery Market is projected to reach USD 4.0 billion by 2027 from USD 0.6 billion in 2022, at a CAGR of 45.7% during the forecast period.

What benefits AI show in drug discovery and development process?

Drug discovery is a very costly and lengthy process, owing to which there is a need for alternative tools for discovering new drugs. Drug discovery and development are commonly conducted through in vivo and in vitro methods, which are very costly and time-consuming. Furthermore, it takes ~10 years on average for a new drug to enter the market at a cost of ~USD 2.6 billion (Source: Biopharmaceutical Research and Development.org). Several players operating in this market are developing platforms that can help in the rapid discovery of drugs. For instance, Insilico Medicine (US) developed an AI-based drug discovery system, GENTRL, with which it could develop six experimental novel molecules within 21 days.

How and why AI workforce shortage is important retraining factor holding back the growth of the market?

AI is a complex system, and companies require a workforce with specific skill sets to design, manage, and implement AI systems. Personnel dealing with AI systems should be familiar and aware of technologies such as machine intelligence, deep learning, cognitive computing, image recognition and other AI technologies. Additionally, integrating AI technologies into existing systems is a challenging task that necessitates substantial data processing in order to replicate human brain behavior. Even slight errors might cause system failure and have a negative impact on the desired outcome. The absence of professional standards and certifications in AI/ML technologies is restraining the growth of AI

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The growth of this Artificial Intelligence in Drug Discovery Market is driven by the growing need to control drug discovery & development costs, and growing number of cross-industry collaborations and partnerships, On the other hand, a lack of data sets in the field of drug discovery and the inadequate availability of skilled labor are some of the factors challenging the growth of the market.

Services segment is expected to grow at the highest rate during the forecast period.

Based on offering, the AI in drug discovery market is segmented into software and services. In 2021, the services segment accounted for the largest market share of the global AI in drug discovery services market and also expected to grow at the highest CAGR during the forecast period. The benefits associated with AI services and the strong demand for AI services among end users are the key factors driving the growth of this market segment.

Machine learning technology segment accounted for the largest share of the global AI in drug discovery market.

Based on technology, the AI in drug discovery market is segmented into machine learning and other technologies. The machine learning segment accounted for the largest share of the global market in 2021 and expected to grow at the highest CAGR during the forecast period. The machine learning technology segment further segmented into deep learning, supervised learning. reinforcement learning, unsupervised learning, and other machine learning technologies. Deep learning segment accounted for the largest share of the market in 2021, and this segment also expected to grow at the highest CAGR during the forecast period.

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The immuno-oncology application segment accounted for the largest share of the AI in drug discovery market in 2021.

On the basis of application, the AI in drug discovery market is segmented into neurodegenerative diseases, immuno-oncology, cardiovascular diseases, metabolic diseases, and other applications. The immuno-oncology segment accounted for the largest share of the market in 2021, owing to the increasing demand for effective cancer drugs. The neurodegenerative diseases segment is estimated to register the highest CAGR during the forecast period. The role of AI in resolving existing complexities in neurological drug development and strategic collaborations between pharmaceutical companies & solution providers are the key factors responsible for the high growth rate of the neurodegenerative diseases segment.

Pharmaceutical & biotechnology companies segment accounted for the largest share of the global AI in drug discovery market.

On the basis of end user, the AI in drug discovery market is segmented into pharmaceutical & biotechnology companies, CROs, and research centers and academic & government institutes. The pharmaceutical & biotechnology companies segment accounted for the largest market share of AI in drug discovery market, in 2021, while the research centers and academic & government institutes segment is projected to register the highest CAGR during the forecast period. The strong demand for AI-based tools in making the entire drug discovery process more time and cost-efficient is driving the growth of this end-user segment.

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North America is expected to dominate the Artificial Intelligence in Drug Discovery Market in 2022.

North America accounted for the largest share of the global AI in drug discovery market in 2021 and also expected to grow at the highest CAGR during the forecast period. North America, which comprises the US, Canada, and Mexico, forms the largest market for AI in drug discovery. These countries have been early adopters of AI technology in drug discovery and development. Presence of key established players, well-established pharmaceutical and biotechnology industry, and high focus on R&D & substantial investment are some of the key factors responsible for the large share and high growth rate of this market

Prominent players in this Artificial Intelligence in Drug Discovery Market are NVIDIA Corporation (US), Microsoft Corporation (US), Google (US), Exscientia (UK), Schrödinger (US), Atomwise, Inc. (US), BenevolentAI (UK), NuMedii (US), BERG LLC (US), Cloud Pharmaceuticals (US), Insilico Medicine (US), Cyclica (Canada), Deep Genomics (Canada), IBM (US), BIOAGE (US), Valo Health (US), Envisagenics (US), twoXAR (US), Owkin, Inc. (US), XtalPi (US), Verge Genomics (US), Biovista (US), Evaxion Biotech (Denmark), Iktos (France), Standigm (South Korea), and BenchSci (Canada). Players adopted organic as well as inorganic growth strategies such as product upgrades, collaborations, agreements, partnerships, and acquisitions to increase their offerings, cater to the unmet needs of customers, increase their profitability, and expand their presence in the global market.

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