For pharmaceutical companies, animal-based biological studies, including drug metabolism and pharmacokinetics (DMPK), pharmacological, and toxicological studies, provide some stepwise checkpoints before promising lead compounds proceed to clinical testing in humans and ultimately regulatory submission. However, a gap often exists between the data scientists who develop biological data analysis tools and the bench-level biologists and chemists who use them to improve R&D productivity in drug discovery.
Mitsubishi Tanabe Pharma worked with MathWorks Consulting Services to bridge this gap and make drug candidate selection more efficient. The company developed MATLAB® based biological data analysis tools that shorten iterations in developing analytical algorithms, increase the biologists’ efficiency, enable them to evaluate more drug candidates, and accelerate the discovery process.
“Using tools we developed in MATLAB, our biologists can obtain quantitative results automatically, reliably reproduce and manage results, and compare the effects of multiple drugs,” says Ryuta Saito, research scientist on bioinformatics at Mitsubishi Tanabe Pharma. “As a result we can screen more drug candidates, perform retrospective analysis of previously abandoned samples, and double the number of feasibility studies we complete annually.”