Artificial intelligence (AI) has transformed numerous industries, including pharmaceuticals. It has revolutionized various aspects of the pharmaceutical industry, particularly drug discovery, clinical trials, and personalized medicine, by leveraging advanced computing techniques such as machine learning, deep learning, and natural language processing (NLP). 

The transformative potential of AI in drug discovery is evident through the emergence of several late-stage AI-discovered candidates, including BXCL501 by BioXcel Therapeutics, XF-02 by Xbiome, and INS018_055 by Insilico Medicine.

The Global Artificial intelligence (AI) in the pharmaceutical Market was valued at 1,490.08 million in 2022 and is estimated to reach USD 9,441 million by 2030, registering a CAGR of 19.6% from 2023 to 2030.🚀

Following Factors Driving the Market Growth 📈:

(1) Surging Investment in AI for Pharma 💸: 

The Venture capital landscape of AI in the Pharma market is soaring with high investments. For instance, in 2021 AI-driven biotech companies raised USD 2,685 million, marking a 46% increase from the previous year. Notably, Xtalpi and Insitro secured impressive funding of USD 400 million each in their Series D and Series C funding rounds, respectively. 

(2) Increasing M&A and collaboration deals 🤝: 

The growing potential of AI in the pharmaceutical sector has led to a rise in M&A and collaboration deals between major pharma companies and AI-driven biotech firms. For instance, Takeda's acquisition of Nimbus Lakshmi, a wholly-owned subsidiary of Nimbus Therapeutics, for a remarkable $6 billion, including the AI-discovered candidate NDI-034858. Similarly, Sanofi engaged in a $5 billion collaboration deal with Exscientia to jointly develop 15 AI-based small molecule candidates across oncology and immunology. 

Other factors that fuel the market growth involve, the growing incidence of chronic diseases, strong government support for AI initiatives, and a rising demand for AI-based solutions in drug discovery and development. 

However, the high initial cost for deployment and the lack of skilled professionals might hamper the market growth. 

The report also presents a detailed quantitative analysis of the current market trends and future estimations from 2023 to 2030. 

The forecasts cover 5 Technology Types, 5 Applications, and 4 Regions. The report comes with an associated file covering quantitative data from all numeric forecasts presented in the report.

The report covers the following topics:

• Market Drivers, Restraints, and Opportunities

• Porter’s Five Forces

• Eco System Analysis

• COVID-19 Impact

• Analysis of by Technology, Application, and Region

• Investment Analysis by Venture Capital and IPO

• Key M&A’s and Collaboration Timeline from 2017 to 2022 

• Key Breakthrough Timeline from 2018 to Q2 2023

• Computational Methods Used by AI Companies

• AI-Discovered Candidates Analysis

• 20 Key Company Profiles, Financial Overview, and Key Strategies

• Market analysis and forecast from 2018 to 2030