The DynoChem system provides active pharmaceutical ingredient (API) producers and drug manufacturers with a means of optimizing unit operations and process scale-up through advanced predictive modelling techniques. Steve Hearn, PFD's COO, told in-PharmaTechnologist.com that IndiaSoft's background in providing both consultation and training services to the manufacturing industry, coupled with its network of offices throughout India had made the firm an attractive distribution partner. The agreement, which is the first that PFD has signed with a local specialist, is a reflection of the demand for advanced scale-up solutions in India's booming drug manufacturing sector. Hearn said that several Indian drugmakers, including Chaitanya, CIPLA, Dr Reddy's, IPCA, Lupin and Ranbaxy, as well as "a number of specialty and fine chemicals companies and contract research organizations (CRO)," have expressed an interest in DynoChem. He went on to say that following the IndiaSoft deal, financial terms of which are not being disclosed, PFD will seek to establish a similar agreement with a distribution partner in Japan. Different approach to traditional scale-up The DynoChem system is designed to improve manufacturing productivity, by reducing the time and quantity of materials required to execute a given project. The platform also assists in the application of quality by design (QbD) and process application technology (PAT) principles. Hearn explained that it "uses a different approach to traditional techniques like Design of Experiments (DOE). For example, DOE does not take advantage of your knowledge that mass and energy will be conserved in a reaction, that you may have some idea of the overall reaction scheme, or that reaction rates depend on concentrations and temperature. Because DynoChem explicitly uses this information, it can produce a more detailed picture of your process with many fewer experiments." Such an approach is intended to help pharmaceutical manufacturers increase production yields and achieve better control of impurities. Effective scale-up can also help reduce the requirement for catalysts, solvent loading and minimize critical cycle times.