The hunt for new medicines is getting a technology overhaul. According to a feature published by News-Medical.net, experts at the technology and product development firm TTP say that artificial intelligence, laboratory automation, and a modernized approach to the so-called DMTA cycle are speeding up drug discovery.
DMTA stands for Design, Make, Test, Analyze — the repeating loop researchers move through as they create a candidate compound, produce it, test how it behaves, and study the results before designing the next, improved version. Historically each turn of that loop has been slow and labor-intensive.
The News-Medical.net piece frames AI and automation as ways to accelerate this workflow, drawing on insights from TTP leaders. The report presents "next-generation" DMTA as the combination of these tools working together to move candidates through the cycle faster.
The source provided here is a single overview article rather than a study with detailed results, so specific figures, named drug programs, and performance benchmarks are not included. What it signals is a direction of travel: the industry is increasingly treating discovery less as a series of manual bench experiments and more as a faster, data-driven, partly automated process.
Why it matters: drug discovery is famously expensive and time-consuming, and shaving time off the design-test loop could mean promising treatments reach patients sooner and at lower cost — making how labs adopt AI and automation a development worth watching.