Predicting pharmacokinetic parameters and curves
Pharmacokinetics (PK) describes how the body affects a drug after administration. The concentration-time profile of a compound reflects its exposure,…
Pharmacokinetics (PK) describes how the body affects a drug after administration. The concentration-time profile of a compound reflects its exposure,…
In this webinar we demonstrated how this new platform provides interactive access to deep learning imputation to extract more value…
This article outlines practical applications of deep learning on drug discovery data. It introduces some of the research behind our…
In this webinar, we explore how the limitations of pharmaceutical data can impact conventional predictive model building. Our speakers, Julian Levell (Constellation pharmaceuticals), Ben Irwin and matt Segall (Optibrium) demonstrate how the deep learning imputation algorithm underlying our Cerella platform, overcomes these challenges.
This article describes a novel deep learning neural network method and its application for the imputation of bioactivity data, such…
This paper, co-authored with our colleagues at NextMove Software, explores applications of Matched Series Analysis within StarDrop’s Nova module to…
Summary This review article discusses recent developments in the methods and opinions around multi-parameter optimisation, focusing on applications to de novo drug…
Summary This article on applying med chem transformations and multi-parameter optimisation describes the concepts and algorithms underlying StarDrop’s Nova module. We’ve developed…
Join Optibrium at HubXchange in Boston to hear more about implementing AI in drug discovery.
In this ebook we demonstrate our deployable AI discovery platform, Cerella™. Browse real-world stories of success from our collaborations with AstraZeneca, Genetech, Takeda Pharmaceuticals, Constellation Pharmaceuticals and many more.
In this ebook, you’ll discover the key considerations which every leader needs to take in order to successfully implement AI in their drug discovery pipelines.