New technology to aid crystallization prediction

The software, which has been developed at the University of Leeds, in collaboration with the Cambridge Crystallographic Data Centre (CCDC) is called Visual HABIT. It offers a significant improvement on existing predictive resources and will enable companies to adopt a more 'bottom up' approach to the design of products or formulated products in the pharmaceutical, agrochemical and fuel sectors.

The software helps companies predict crystal properties in different chemical environments, something which will reduce extensive early-stage laboratory research, bringing down development costs and helping to bring new products to market more efficiently. It also has the ability to show what happens to crystalline particles under different processing conditions.

"Being able to see how crystal properties change within different processing environments is really important, because often companies have put in years of work before they even get to this stage," says Professor Kevin Roberts who is leading the research. "As chemical engineers, we have to make sure that the quality of a product remains the same in a manufacturing environment as in the laboratory. It's a bit like ensuring a meal cooked for 1000 guests is exactly the same quality as the same meal cooked for just four people. Our aim is to ensure that in scaling up different processes, none of the quality is lost. Our technology will help overcome some of the obstacles that slow down the research and development processes in these sectors."

Visual HABIT will also be a valuable resource for the nuclear sector, where crystallisation during long term storage can create difficulties in the effective processing of waste.

"We're excited about our software because we can see enormous benefits to all the sectors we're working with," says Professor Roberts. "If companies already know – at the beginning of the development process - how different chemical formulations are going to behave under a range of conditions, it'll speed up development times, cut costs and may result in superior products."

The Leeds research group, called Synthonic Engineering, is working with CCDC and five industry partners from across the pharmaceutical, agrochemical, fuel, nuclear and instrumentation sectors to ensure effective translation of the new technology. It aims to commercialise the technology within 12 months.

"We are delighted to be part of this collaborative venture" says Colin Groom, Executive Director of the CCDC. "In the past we have focussed on how knowledge and understanding derived from Cambridge Structural Database can be used in the discovery and development of drugs. This partnership allows us to explore the application of crystallographic and structural information to particle engineering. Our experience in software development will ensure practical and useful software tools are delivered in an exciting area that is new to us."

Provided by University of Leeds (news : web)

Tough crystal nut cracked: Correct prediction of all three known crystal structures of a sulfonimide

  It's not just the type of molecules a material is made of, the way in which they are arranged in space is important too. For many organic molecules, multiple crystal structures are known, and their physical properties can differ significantly. For example, a drug can be effective in one crystalline form but much less effective in another because it doesn't dissolve fast enough. Unfortunately, it has not been possible until recently to reliably predict crystal structures by using computer simulations. Frank Leusen and his co-workers at the University of Bradford (UK) are making significant progress on this front. As the scientists report in the journal Angewandte Chemie, they successfully used a quantum mechanical approach to predict the three known crystal structures of a sulfonamide.

Small differences in the production conditions, such as variations in pressure or temperature, can be enough to cause fine chemicals, such as pharmaceuticals, pigments, explosives, or agrochemicals, to crystallize in a different form. This can lead to problems with the production process or to undesirable product properties. It is correspondingly important to know which crystal structures are possible.

Scientists use computational chemistry methods to obtain information about molecular structures and crystallization processes. However, taking all of the parameters into account would exceed current computational capacities. “Precise, reliable predictions of the crystal structures of organic molecules have remained somewhat of a Holy Grail for crystallography,” says Leusen.

An international project regularly organizes blind studies in which research groups are asked to predict crystal structures. In 2007, Leusen and two co-workers were able to successfully predict the crystal structures of all four test compounds by using a quantum mechanical approach. A team led by Leusen then took on another test compound, a sulfonamide, which was the subject of a blind study in 2001; none of the participating teams was able to predict the crystal structure at the time. Interestingly, two additional, previously unknown crystal structures of this sulfonamide were discovered after the study. “By using the computational process developed by Marcus Neumann at Avant-garde Materials Simulation in Freiburg, Germany, we were able to correctly predict all three crystal structures,” says Leusen.

“Even though it is currently not possible to predict the outcome of a specific crystallization experiment under specific boundary conditions,” explains Leusen, “our results demonstrate that precise calculations of the lattice energy are sufficient to model crystallization thermodynamics and thus predict the different crystal structures of small organic molecules.”

More information: Frank J. J. Leusen, Molecule VI, a Benchmark Crystal-Structure-Prediction Sulfonimide: Are Its Polymorphs Predictable? Angewandte Chemie International Edition, http://dx.doi.org/ … ie.201007488