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.
(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
Aitia bio
Atomwise Inc.
Benevolent AI
BioSymetrics
BPGbio Inc.
Bristol-Myers Squibb
Cyclica
Euretos
Exscientia
GE Healthcare
Google DeepMind
IBM Corporation
Insitro
Johnson & Johnson
Merck & Co
Microsoft
Novartis AG
Novo Nordisk
NVIDIA Corporation
Pfizer Inc
Context-Aware Processing
Natural Language Processing
Querying Method
Deep Learning
Others
Drug Discovery
Clinical Trial Research
Research & Development
Medical Imaging
Others (Such as Epidemic Prediction)
North America:
The U.S., Canada
Europe:
Germany, The UK, Italy, France, Spain, Rest of Europe
Asia-Pacific:
China, India, Japan,South Korea, Rest of Asia-Pacific
LAMEA:
Brazil, South Africa, UAE, Rest of LAMEA
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