Laboratory information management systems (LIMS) are widely used in the pharmaceutical industry, especially where compliance with regulatory needs such as FDA 21 CFR Part 11, HIPPA, CLIA, and GLP are required. However, during the early stages of the drug discovery process—where large volumes of data on many different samples are generated—LIMS are generally underutilized. The ability of LIMS systems to bind data to a large number of samples, interface with a wide variety of instrumentation, and integrate with electronic laboratory notebooks (ELN) make LIMS ideal for the discovery process.

A case in point is protein crystallization. The pharmaceutical industry relies on developing small molecules that interact with proteins, and a protein’s function is determined by its 3D structure. To characterize how compounds bind to a protein, it is helpful to crystallize them in a stable form to enable scientists to conduct further experiments around energy calculations, folding, active sites, hydrophobic centers, and also aid in computer-aided drug design.

The workflow for crystallizing a protein is a tedious process. It begins with isolating the protein of interest, which includes vector design and construction, host transformation, expression, purification, folding, and testing for proper activity. Most of these steps require some optimization, such as obtaining proper purity levels and concentration. Once the protein is obtained, the proper conditions for crystallization must be empirically determined for each protein. This is typically done by first putting the protein through a sparse-matrix screen¹ that will expose it to the most widely used conditions that have previously been successful for other proteins. Once starting conditions have been obtained, fine tuning is needed to optimize conditions such as temperature, pH, protein concentration, and precipitant type. To further complicate the process, any additional mutated, truncated, or compound-bound forms of the protein usually need the whole process repeated. All steps in this process create a large volume of data for each sample that would greatly benefit from having an integrated tracking system.

LabVantage Solutions designed a custom LIMS solution for the protein crystallization group of a leading global pharmaceutical company. Historically, their scientists employed manual laboratory processes to conduct and manage experiments, as well as, track associated experimental data, managed mostly in Excel. However, with ensuing high volume of data, scientists unavoidably spent more time on data entry, parsing, and reorganization than on analysis. The LIMS interfaces with instruments and captures data in real-time at the project, study, experiment, task, and sample level, streamlining data entry process with ultimate data integrity. It also manages information in advanced database through automated workflows and enables the companies scientists to securely share knowledge globally, visualized on dashboards. In addition, each report generated contains hyperlinks to all data and results of each experimental step, all of which are accessible via electronic laboratory notebook (ELN). A custom-tailored protein crystallization task library was also configured in the experimental design framework of the system. The scientists can now easily build their own experiments for crystal structures around a particular protein or construct, swiftly produce protein crystal structures and efficiently enhance the chemistry around a potential small molecule. Based on the company analysis, implementing a state-of-the-art LIMS had undeniably significant process improvement over previous manual processes, and they expect their return on their investment to be exponential.

In the competitive world of drug discovery, an individual compound can bring success to a pharmaceutical company. Only an adequate IT/Informatics environment can enable this, and a LIMS is the platform informatics solution that provides it.

References
1. Jancarik J and Kim SH. Sparse-matrix sampling—a screening method for crystallization of proteins. J Appl Cryst. 1991; 24:409–411.