ImageWith a faltering economy, increased competition generated by generic drugs, skyrocketing costs of marketing blockbusters, and unsustainable R&D expenditures, pharmaceutical companies are looking for ways to reduce costs and improve the effectiveness of their drug discovery and development operations.

As a result, pharmaceutical companies are accelerating the pace and extent to which they are outsourcing their R&D operations. However, many companies are focusing primarily, or even exclusively, on the cost savings component of outsourcing. This strategy, as appealing as it may be, is not sustainable and overlooks other important criteria in restoring drug pipelines.

It’s not that lowering R&D costs isn’t important (especially in today’s economic climate), but history has shown that the benefit of outsourcing simply to lower cost is transitory. To be sustainable over the long term, R&D outsourcing in pharma has to increase productivity, as well as reduce costs.

One way for pharmaceutical companies to adopt an outsourcing strategy focused on increasing productivity is to partner with a contract research organization (CRO) that utilizes microscale, parallel experimentation and advanced informatics technology.

Parallel experimentation over offshoring

As an alternative to offshoring tedious tasks to unskilled laborers abroad, microscale, parallel experimentation speeds fundamental, preclinical drug discovery research by automating lab tasks such as sample preparation, processing, and analysis. Outsourcing that utilizes automated experimentation shortens the path to more viable drug candidates by exploring multiple scenarios, running hundreds, or even thousands, of experiments in parallel, all while examining economies of scale on a per experiment basis. Automated experimentation can accelerate a wide range of common workflow tasks including solubility profiling, polymorph and salt selection, liquid formulations, forced degradation, excipient compatibility, and process optimization. Compared to a scientist who can run about 500 experiments per year, parallel experimentation can run up to 25,000 experiments a year. It can enable up to 90 percent lower cost per experiment, and up to a 90 percent decrease in the amount of expensive, early-development material required for experiments. This improvement, while eliminating costly, labor-intensive work, dramatically increases not only productivity, but enables companies to demonstrate increased ROI.

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