May 1, 2007 (Vol. 27, No. 9)

DynoChem Platform Designed to Facilitate API Process Development and Scale-up

Already used by 11 of the world’s biggest pharmaceutical companies, the DynoChem ( platform was developed to facilitate API process development and expedite scale-up. DynoChem says the product represents a single platform for parameter fitting, simulation, and the optimization of any rate-based unit operation, for example, reaction, crystallization, evaporation, or drying.

The platform essentially uses data obtained at the lab bench in mechanistic models to expedite safe and efficient progression to pilot and commercial manufacture, explains Steve Cropper, the company’s director of sales. “In essence, DynoChem is a modelling tool that helps chemists and engineers understand the mechanics of their reactions and associated workup and isolation steps. The simulation software can predict and help circumvent process development setbacks, including the generation of reaction impurities/by-products, incompatibilities in scale-up, or yield loss and batch failure.”

For example, he continues, “an API manufacturer has shown how a modelling approach using DynoChem resulted in a reduction in the number of lots required to produce a stable process from 100 to less than 10.”

Performance Fluid Dynamics (PFD), which owns DynoChem, claims that unlike competing products, DynoChem has been developed specifically for users in the pharmaceutical, agrochemical, and specialty chemicals industries who do not have a background in modelling. The platform features over 160 predefined template models and examples for common organic synthesis reactions, work-up, and isolation steps, along with lab reactor templates. This past February the latest version, DynoChem 3.2, was released. According to the company, it delivers a new level of productivity, enabling the completion of calculations up to six times faster.

Mechanistic Modeling

“DynoChem gives companies the opportunity to produce a mechanistic model of their basic reaction, allowing them to input different chemical or physical parameters such as heat, pressure, or even stirring speed,” Cropper continues. The modelling software predicts how the process will run under different conditions or when using different equipment or reaction vessels. This approach negates the need for time-consuming and costly trial and error and can be applied much earlier in the development cycle than statistical approaches, which are only really useful when a number of batches have already been manufactured.

Generating detailed insights into reaction chemistry, kinetics, and critical parameters at an early stage can thus significantly save time and money further downstream, allowing companies to circumvent pinch-points through the earlier design of safe, efficient processes that will be suitable for manufacture at pilot or commercial scale.”

More Data, Faster Approval

The pharma industry is also under increasing pressure by regulatory agencies, such as the FDA, to more fully understand their reaction chemistry and processes, Cropper stresses. “The less process understanding demonstrated to the regulatory authorities, the more constrained the approved manufacturing conditions will be. Companies that can demonstrate a true understanding of their chemistry, on the other hand, will have a faster route to approval and, once at the manufacturing stage, are more likely to have a wider range of operating conditions sanctioned, which allows greater flexibility if manufacturing scale, location, or equipment need to be changed in the future”.

Enterprise-wide Utility

PFD claims the technology has broad utility for scientists in process development, safety groups, pilot plant and technical operations, as well as unit operations specialists, such as crystallization specialists. The product can be used to help interpret IR and FBRM data, convert between CLD and CSD, assess vessels and mixing, and simulate all types of crystallization.

“DynoChem started life in 1994 as a piece of software developed by scientists at what was then Zeneca (now Syngenta) for use in the scale-up of particular agrochemical processes,” Mr. Cropper explains.

“Performance Fluid Dynamics took the product on in 2000 and initially exploited DynoChem on a consultancy basis. Pharmaceutical clients would come to us with a process or manufacturing problem, and we’d use the software as a tool to demonstrate which changes were needed to optimize, for example, yield or reaction time. By adding user features that would enable nonsoftware specialists to use DynoChem in-house, we were then able to license out the product, starting in 2001. In addition to nearly all the major pharma companies, four of the top six global agrochemical players also now use our software.”

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