Artificial Intelligence (AI) in Drug Discovery Market Size, Trends, Growth, Opportunities 2023-2030| Microsoft, Exscientia, and Benevolent

The global artificial intelligence (AI) in drug discovery market size was valued at USD 3.00 billion in 2022. The market is projected to grow from USD 3.54 billion in 2023 to USD 7.94 billion by 2030, exhibiting a CAGR of 12.2% during the forecast period (2023-2030).

The artificial intelligence (AI) in drug discovery market is experiencing a surge in innovation, offering immense potential for accelerating the development of life-saving medications. This press release explores a recent key industry development, leading segment, and the future outlook for this transformative field.

𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗿𝗲 𝗠𝗶𝘀𝘀𝗶𝗻𝗴: 𝗚𝗲𝘁 𝗮 𝗙𝗿𝗲𝗲 𝗥𝗲𝗽𝗼𝗿𝘁 (𝗣𝗗𝗙) 𝗦𝗮𝗺𝗽𝗹𝗲: https://www.fortunebusinessinsights.com/enquiry/sample/artificial-intelligence-in-drug-discovery-market-105354

𝗖𝘆𝗰𝗹𝗶𝗰𝗮 𝗦𝗲𝗰𝘂𝗿𝗲𝘀 𝗙𝘂𝗻𝗱𝗶𝗻𝗴 𝘁𝗼 𝗗𝗿𝗶𝘃𝗲 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗳𝗼𝗿 𝗡𝗲𝗴𝗹𝗲𝗰𝘁𝗲𝗱 𝗗𝗶𝘀𝗲𝗮𝘀𝗲𝘀:

In a move highlighting the promise of AI for global health, Cyclica, a leader in AI-powered drug discovery, received a USD 1.8 million grant from the Bill & Melinda Gates Foundation in November 2022. This grant enables Cyclica to leverage its cutting-edge platform to identify novel non-hormonal contraceptives targeting "low-data" biological targets. This development underscores the potential of AI to accelerate drug discovery for neglected diseases and improve health outcomes worldwide.

𝗧𝗼𝗽 𝗣𝗹𝗮𝘆𝗲𝗿𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗔𝗜 𝗶𝗻 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗠𝗮𝗿𝗸𝗲𝘁:

• Microsoft (U.S.)
• Schrödinger, Inc. (U.S.)
• Cresset (U.K.)
• IBM (U.S.)
• Atomwise Inc. (U.S.)
• Insilico Medicine (U.S.)
• Exscientia (U.K.)
• BenevolentAI (U.K.)
• Aria Pharmaceuticals, Inc. (U.S.)
• Integral BioSciences (U.S.)
• Alphabet Inc. (U.S.) (parent company of Google)

𝗠𝗮𝗿𝗸𝗲𝘁 𝗗𝗿𝗶𝘃𝗲𝗿𝘀 𝗮𝗻𝗱 𝗥𝗲𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀:

Several factors are propelling the AI in drug discovery market forward:

• 𝗛𝗶𝗴𝗵 𝗖𝗼𝘀𝘁 𝗮𝗻𝗱 𝗧𝗶𝗺𝗲-𝗖𝗼𝗻𝘀𝘂𝗺𝗶𝗻𝗴 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗠𝗲𝘁𝗵𝗼𝗱𝘀: Traditional drug discovery processes are expensive and time-consuming, driving the need for faster and more efficient methods.
• 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀: Advancements in data science and machine learning are empowering researchers to analyze vast datasets and identify potential drug candidates more effectively.
• 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗠𝗲𝗱𝗶𝗰𝗶𝗻𝗲: AI facilitates the development of personalized medicine approaches by analyzing individual patient data to design targeted therapies.

However, certain challenges remain:

• 𝗕𝗹𝗮𝗰𝗸 𝗕𝗼𝘅 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: The complex nature of AI algorithms can make it difficult to understand how they arrive at specific results, raising concerns about transparency and interpretability.
• 𝗗𝗮𝘁𝗮 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗣𝗿𝗶𝘃𝗮𝗰𝘆: The use of large patient datasets in AI-powered drug discovery necessitates robust data security measures to protect sensitive information.
• 𝗥𝗲𝗴𝘂𝗹𝗮𝘁𝗼𝗿𝘆 𝗖𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Regulatory frameworks may need to adapt to accommodate the integration of AI into drug discovery processes.

𝗙𝗼𝗿 𝗙𝘂𝗹𝗹 𝗥𝗲𝗽𝗼𝗿𝘁 𝗖𝗼𝘃𝗲𝗿𝗮𝗴𝗲 𝗩𝗶𝘀𝗶𝘁: https://www.fortunebusinessinsights.com/artificial-intelligence-in-drug-discovery-market-105354

𝗠𝗮𝗿𝗸𝗲𝘁 𝗥𝗲𝗽𝗼𝗿𝘁 𝗖𝗼𝘃𝗲𝗿𝗮𝗴𝗲:

For a comprehensive understanding of the AI in drug discovery market, Fortune Business Insights' report offers in-depth analysis on:

• 𝗠𝗮𝗿𝗸𝗲𝘁 𝗚𝗿𝗼𝘄𝘁𝗵 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝗶𝗼𝗻𝘀: The report provides detailed market size and growth forecasts for the AI in drug discovery market over the forecast period.
• 𝗠𝗮𝗿𝗸𝗲𝘁 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻:The report segments the market based on technology type (machine learning, deep learning, natural language processing), application (oncology, neurology, infectious diseases), and molecule type (small molecules, large molecules).
• 𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲:The report identifies key players in the market and analyzes their competitive strategies.
• 𝗥𝗲𝗴𝗶𝗼𝗻𝗮𝗹 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: The report provides insights into the growth potential of AI in drug discovery in different geographical regions.

𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀:

𝗦𝗺𝗮𝗹𝗹 𝗠𝗼𝗹𝗲𝗰𝘂𝗹𝗲𝘀 𝗟𝗲𝗮𝗱 𝘁𝗵𝗲 𝗪𝗮𝘆:

The small molecule segment is expected to dominate the AI in drug discovery market during the forecast period. Small molecules are typically easier to synthesize and administer compared to large molecules, making them a popular choice for drug development.

𝗔 𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲:

The AI in drug discovery market is a dynamic and competitive space. Established technology companies like Microsoft and Alphabet (Google) are playing a growing role, alongside specialized AI-powered drug discovery startups. This competition fosters continuous advancements in AI algorithms, data analysis methods, and drug discovery pipelines.

𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜 𝗶𝗻 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆:

The AI in drug discovery market is poised for significant growth as advancements in technology and increasing awareness of its potential transform the pharmaceutical industry. With ongoing research to address challenges like interpretability and regulatory considerations, AI holds immense promise for accelerating drug discovery timelines, reducing costs, and ultimately delivering life-changing treatments to patients worldwide.

𝗖𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗲 𝗧𝗵𝗶𝘀 𝗥𝗲𝗽𝗼𝗿𝘁 𝗔𝗰𝗰𝗼𝗿𝗱𝗶𝗻𝗴 𝗧𝗼 𝗬𝗼𝘂𝗿 𝗖𝗼𝗻𝘃𝗲𝗻𝗶𝗲𝗻𝗰𝗲: https://www.fortunebusinessinsights.com/enquiry/ask-for-customization/artificial-intelligence-in-drug-discovery-market-105354

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This release was published on openPR.