Top Companies in the 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.)

Market Trends

• Machine learning (ML) and deep learning are widely used for molecular modeling and prediction.

• Natural language processing (NLP) helps in analyzing scientific literature and patents.

• The use of generative AI for de novo drug design is emerging.

• Investment and startup activity in this space is growing significantly.

Key Industry Development

In November 2022, Cyclica received a USD 1.8 million grant from the Bill & Melinda Gates Foundation to apply its AI-enabled drug discovery platform to discover new non-hormonal contraceptives, leveraging multiple low-data biological targets. This initiative underscores the potential of AI in addressing unmet medical needs through innovative approaches.

Market Drivers & Restraints

Drivers:

• Increasing investment by pharmaceutical companies and research institutes in AI technologies to enhance drug discovery processes.
• Growing prevalence of chronic diseases necessitating the development of novel therapeutic solutions.
• Advancements in AI algorithms facilitating faster and more accurate identification of drug candidates.

Restraints:

• High initial investment costs associated with implementing AI technologies.
• Data privacy concerns and regulatory challenges in handling sensitive patient information.
• Lack of standardized protocols for integrating AI into existing drug discovery workflows.

Market Report Coverage

The report encompasses a comprehensive analysis of the AI in drug discovery market, including:

• Market size and forecast from 2023 to 2030.
• Segmentation by drug type, offering, technology, application, and end-user.
• Regional insights covering North America, Europe, Asia Pacific, and the rest of the world.
• Competitive landscape highlighting key players and their strategic initiatives.

Explore the full research report with detailed insights and TOC:https://www.fortunebusinessinsights.com/artificial-intelligence-in-drug-discovery-market-105354 

Market Competitive Landscape

The AI in drug discovery market is characterized by the presence of several key players focusing on strategic collaborations, product innovations, and research and development activities to strengthen their market position. Notable developments include:

• In December 2023, Merck KGaA launched AIDDISON, a drug discovery software aimed at accelerating drug development and increasing the success rate of new drugs.
• In September 2023, Merck KGaA partnered with BenevolentAI and Exscientia to enhance the drug discovery process with a higher probability of success.
• In May 2023, Google Cloud introduced two new AI-powered devices to assist pharmaceutical and biotechnology companies in accelerating drug discovery and advancing precision medicine.

Market Segments

The market is segmented based on various parameters:

• By Drug Type: Small Molecule and Large Molecule. The small molecule segment is expected to lead the market during the forecast period.
• By Offering: Software and Services.
• By Technology: Machine Learning, Natural Language Processing, and Others.
• By Application: Endocrinology, Cardiology, Oncology, Neurology, and Others.
• By End-user: Pharmaceutical & Biotechnological Companies, Academic & Research Institutes, and Others.

Market Regional Insights

North America dominated the AI in drug discovery market with a market share of 69.33% in 2022. The region's growth is attributed to the presence of major pharmaceutical companies, advanced healthcare infrastructure, and significant investments in AI technologies. Europe and Asia Pacific are also witnessing substantial growth due to increasing research activities and government initiatives supporting AI integration in drug discovery.

Future Market Scope

The AI in drug discovery market is poised for significant growth, driven by continuous technological advancements and increasing demand for efficient drug development processes. Future prospects include:

• Enhanced collaboration between AI technology providers and pharmaceutical companies to streamline drug discovery workflows.
• Development of AI models capable of predicting drug efficacy and safety profiles with higher accuracy.
• Expansion of AI applications into personalized medicine, enabling tailored therapeutic solutions for individual patients.
• Integration of AI with other emerging technologies such as blockchain and Internet of Things (IoT) to create comprehensive healthcare solutions.