Artificial Intelligence (AI) in Drug Discovery Market - By Component (Software, Service), Technology (Machine learning {Deep Learning}), Application Type (Target Identification), Therapeutic Area (Oncology), End-use (CRO), Global Forecast, 2023 - 2032

Artificial Intelligence (AI) in Drug Discovery Market - By Component (Software, Service), Technology (Machine learning {Deep Learning}), Application Type (Target Identification), Therapeutic Area (Oncology), End-use (CRO), Global Forecast, 2023 - 2032

Global Artificial Intelligence (AI) in Drug Discovery Market will expand at 30.1% CAGR from 2023 to 2032, driven by the growing number of cross-industry collaborations and partnerships. The convergence of pharmaceutical expertise with AI-driven technologies enables faster and more efficient drug discovery processes. Collaborations facilitate the integration of AI algorithms into drug research, accelerating the identification of potential compounds and reducing development timelines. This synergy between different sectors fuels innovation, driving the growth of the AI in drug discovery industry.

Quoting an instance, in October 2023, Evozyn revealed the completion of an $81 million Series B funding round dedicated to supporting the advancement of its generative AI-powered drug discovery platform and product development efforts. This development comes on the heels of a productive partnership with NVIDIA earlier in 2023, during which the two companies jointly created an innovative AI model capable of designing therapeutic proteins.

The overall AI in drug discovery market is categorized based on component, technology, application, therapeutic area, end-use, and region.

The services segment could garner commendable gains throughout 2023-2032. AI in drug discovery services is in high demand due to their ability to significantly expedite the drug development process. AI algorithms can analyze vast datasets, predict potential drug candidates, and optimize molecular structures with remarkable speed and precision. This not only reduces research and development timelines but also lowers costs. With the need for faster and more efficient drug discovery solutions, the demand for AI services in this sector continues to grow.

AI in drug discovery solutions and services could experience surging demand in preclinical testing applications by 2032 because they enhance accuracy and efficiency. AI-powered algorithms can swiftly analyze complex biological and chemical data, aiding in the identification of promising drug candidates and predicting their behavior in preclinical testing. This reduces the need for extensive laboratory experiments, accelerates the drug development timeline, and ultimately lowers costs, making AI indispensable in the preclinical testing phase of drug discovery.

Europe AI in drug discovery industry could exhibit noteworthy CAGR between 2023-2032. Europe boasts a strong pharmaceutical sector and is investing significantly in AI research. According to EFPIA's Annual Report for 2022, the research-based pharmaceutical industry in Europe has seen substantial growth in production value, rising from 127.5 billion euros in 2000 to 300 billion euros in 2021. Equally noteworthy is the remarkable increase in exports, which surged from 90.9 billion euros to 565 billion euros during the same timeframe. In 2021, imports accounted for 390 billion euros, resulting in a positive trade balance of 175 billion euros.

Regulatory support for innovation and partnerships between academia, startups, and established pharmaceutical companies fosters AI adoption. Additionally, the need for more efficient drug development processes to combat diseases like COVID-19 accelerates the demand for AI solutions in drug discovery across the European region.