AI/ML Now: Bayesian Optimization and Automation for siRNA Method Development (Part One)

At ISC 2016, Edward Ahearne, a Senior Analytical Scientist in AstraZeneca's Early Chemical Development New Modalities group, was interviewed by LCGC International on why his team combined automated chromatography with Bayesian optimization to speed up method development for small interfering RNA (siRNA) medicines based on a presentation he gave at the event.¹ The focus of their research was on separating phosphorothioate (PS) diastereomers. A PS link is a backbone modification in which a non-bridging oxygen atom is replaced with sulfur, making the drug more resistant to breakdown by nucleases. Each PS link creates a chiral center at phosphorus, which can take one of two mirror-image arrangements, so a single siRNA strand can exist as several diastereomers: versions of the molecule that share the same atoms but differ in their 3D arrangement.