Artificial intelligence (AI) continued to stay in the news with several high-profile deals this year, as the pharmaceutical industry readily took to adopting AI models to improve drug discovery. But as the field grows in leaps and bounds, many authorities have prioritised the release of new guidelines, frameworks, and regulations to keep pace with these advances. AI applications such as ChatGPT, an Open AI chatbot that understands human speech and produces in-depth writing, have taken the world by storm and expanded the possibilities of using AI. Across all sectors, AI applications are being used to increase efficiency and reduce costs. This is true not only in the case of the general public using applications for creating images or text, but also for pharma companies to improve drug discovery, clinical trial recruitment, and finding new biomarkers.

Increasing investments in AI indicate the benefits of applying machine learning to identify and screen potential drug candidates. The applications of artificial intelligence (AI) in healthcare are numerous, with the potential to transform key aspects of the industry, such as drug discovery. For many pharmaceutical companies, machine learning is the most important aspect of AI, with the potential to allow machines to ultimately surpass the intelligence levels of humans. Increasing investments in AI in drug discovery by big pharma suggest a truth behind the benefits of applying machine learning to identify and screen potential drug candidates. More and more, big pharma is partnering with AI-driven companies in hopes of more accurately predicting drug candidates and cutting R&D costs and time, prompting GlobalData to ask--Is AI the future of drug discovery?