Process software speeds solvent selection for api crystalisation

Pharmaceutical companies are reducing r&d time and costs with new process software

GlaxoSmithKline, AstraZeneca, and other pharmaceutical companies are reducing their r&d time and costs using newly patented technology marketed as part of AspenTechnology Inc’s aspenONE Process Development for Pharmaceuticals software.

The simulation modeling technology optimises crystallisation design workflow by allowing pharmaceutical companies to quickly evaluate the solubility properties of a NCE.

Drug solubility is a critical factor in determining efficient manufacturing processes for a candidate drug. Aspen Technology says the solubility modeling technology, developed in collaboration with pharmaceutical companies, provides “Quality by Design”(QbD) capabilities that help manufacturers comply with the latest industry regulatory initiatives. It can also help drug companies design a repeatable manufacturing process.

The process also enables process development activities to begin sooner using the predictive modeling capabilities of the software to quickly design optimised manufacturing and purification processes.

By quickly evaluating the solubility properties of a NCE, laboratories can focus precious experimentation efforts in areas that have a high likelihood of success based on the simulation results.

Stephen Carino, Investigator, Solid Form Sciences Group, GlaxoSmithKline, said: ‘Screening for crystalline forms is an essential component in pharmaceutical drug development. In our high-throughput screening workflow, we have utilised NRTL-SAC in Aspen Properties to predict the equilibrium solubility of the drug in single- and multi-component solvent systems.

‘The predicted solubility values are used in selecting an appropriate set of solvent systems that are explicitly unique for each of the crystallisation modes. This rational solvent selection coupled with the systematic screening approach has allowed us to assess risk around solid forms and improve our confidence in the robustness of the API processes.’