The creation of new medications is a challenging and costly process, with less than 10% of drug candidates successfully reaching the market. To improve this, innovations in data analytics and artificial intelligence (AI) are playing a critical role in making drug development more efficient and accessible.
Advances in fields like life sciences, robotics, and computational technologies have significantly boosted progress in the pharmaceutical industry. By utilizing extensive datasets and AI-driven tools, the industry is discovering new opportunities in drug development. But how exactly do AI and big data contribute to breakthroughs in this area?
AI and big data are pivotal in identifying promising drug candidates and assessing their commercial viability. Machine learning, in particular, speeds up the analysis of large datasets, which enhances decision-making and accelerates the creation of new treatments. Animal models, such as transgenic rats, are also playing an increasingly important role in uncovering novel therapies and driving the research process forward.
Despite the substantial investment needed for drug development, the pharmaceutical sector remains poised for considerable growth. Projections suggest the market could exceed $71 billion by 2025, largely thanks to the integration of AI, big data, and emerging technologies that are revolutionizing healthcare and drug discovery.
For a deeper dive into the drug discovery process and the trends shaping its future, consult the detailed resource below.