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Simulation software thwarts polymorph problems.

When we think of pharmaceutical research, we usually think of drug discovery followed by clinical testing. Drug formulation - taking an active molecule and working out a safe, reliable, stable, and cost-effective method of delivering it - receives less attention.

But it is a complex discipline involving synthetic and analytical chemists, pharmacists, crystallographers, and chemical engineers. And it is an area in which high-tech computational methods, such as molecular simulation, are playing an increasing role.

The use of computer simulations to accelerate the drug-discovery process is well established. Almost every discovery lab uses molecular modeling to study the interactions between proteins, enzymes, and drug candidates.

Computational techniques like combinatorial chemistry are used to "mine" databases for useful structural information, focusing experimental work on the most promising synthetic routes. Similar techniques, developed to study materials-science problems related to crystal and surface structures, are now being used in drug development. Such techniques are being applied to problems like polymorphism and morphology control.

Most organic crystalline products can exist in more than one form because molecules may find a number of stable arrangements in which to pack.

This is polymorphism and it can create major problems, since different forms have different properties, and the exact polymorph formed will depend upon crystallization conditions. Variations in molecular packing alter density and mechanical behavior, which can be vital in processing and packaging.

More important, differences in dissolution rate and bioavailability can alter dosages when the patient takes the drug. In extreme cases, this can result in a toxic dose. To add to the uncertainty, one polymorph may transform to another structure after crystallization. If this transformation is slow, the properties of the product may change while it is in storage.

To avoid problems, formulation chemists need a detailed knowledge of all of the possible polymorphs of a drug. Traditionally, they use single-crystal x-ray diffraction data to establish these structures.

This approach has two drawbacks. Samples of the appropriate purity and size cannot always be prepared, and you cannot be sure that you have crystallized every possible polymorph. This is where the computational chemist comes in.

Computers can be used to test models of crystal structure, searching for those that are energetically favorable. The complex intermolecular forces that control molecular packing make this a difficult problem to solve.

The technology has taken a step forward with the recent release of [Cerius.sup.2] Polymorph, a software module from Molecular Simulations Inc., (MSI) of San Diego. The module predicts possible polymorphs based solely on molecular structure.

The Polymorph Predictor has been validated for a range of pigment and small drug molecules and is already in use at several major chemical and pharmaceutical companies. MSI is working on extending its applicability.

Many issues surround the shape, or morphology, of a crystalline solid.

Needle-like crystals may, for example, be harder to process than isometric crystals. They could clog filters and be difficult to transport as slurries.

Some drugs, such as the chloramphenicol-3-palmitate, don't dissolve when administered, but are hydrolyzed in their solid state. In such cases, morphology can alter dosages by affecting the accessibility of active groups. Shape depends upon molecular-level crystal structure, since crystal surfaces to which molecules can bond strongly an grow faster than others.

Shape can also be affected by solvents, additives, and crystallization conditions. Computer simulation is used to analyze key growth surfaces in the crystallization process. Crystal growth and its disruption by solvent or additive molecules is modeled, providing information that's used to understand the effects of solvents or morphology-controlling additives.

Stephen Warde is manager of product marketing support at MSI.
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Title Annotation:computer-aided drug discovery process through the Cerius Polymorph
Author:Warde, Stephen
Publication:R & D
Article Type:Product Announcement
Date:Aug 1, 1996
Words:594
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