Quotient Sciences and Acesion Pharma are collaborating on the development of oral formulations for Acesion’s early-stage atrial fibrillation drug candidates. The work will use a machine-learning approach within Quotient’s Translational Pharmaceutics platform to help select formulations for further testing.
Acesion, based in Copenhagen, is developing small-molecule treatments for atrial fibrillation, a heart rhythm disorder. Formulation development determines how an experimental drug is prepared for administration and can affect its performance during clinical testing.
Quotient said its approach uses active machine learning and Bayesian optimization to analyze formulation data and prioritize candidates. The companies will apply it to Acesion’s compounds as they assess which oral drug products to advance.
Translational Pharmaceutics combines formulation work with early clinical activities. In this collaboration, Quotient’s newer data-analysis tools will be used within that existing development platform.
The project focuses on decisions made before or during early clinical development, rather than on testing whether Acesion’s compounds treat atrial fibrillation. Elisabeth V. Carstensen, Acesion’s vice president of chemistry, manufacturing and controls, said the company will explore whether the algorithms can guide oral formulation work and help it reach a desired product profile.
Quotient Chief Scientific Officer Andrew Lewis said the collaboration is intended to support faster decisions about drug product formulations. Quotient provides research, development and manufacturing services to pharmaceutical companies, while Acesion focuses on therapies for cardiac arrhythmia.
Atrial fibrillation can raise the risk of stroke, making the development of treatment options an area of interest for drug developers. The companies’ work will center on preparing Acesion’s experimental medicines for clinical evaluation.