Life sciences R&D faces major challenges today: shortages of new drugs in company pipelines, growing costs to bring drugs to market, patents expiring, increased competition, downward price pressures from the market, new safety and regulatory measures coming into effect and increased public scrutiny. All of these factors are combining to make successful innovation much more difficult for pharmaceutical organizations.
The industry is responding to these challenges by pursuing new markets, new formulations and new uses for existing products. We’re also seeing attempts to reduce costs through mergers, acquisitions and aggressive externalization. At the lab level, pharmas and biotechs are also exploiting high-throughput and high-content technologies and advances in biotechnology and genomics. Pharmacogenomics, toxicogenomics, chemogenomics and pathway analysis are improving scientists’ insight into druggable targets and the metabolic pathways they control. Translational medicine is linking clinical information back to early-stage discovery.
A side effect of these advanced technologies has been a dramatic increase in the amount of data being collected, which has created another fundamental challenge—managing massive amounts of complex data and collaboratively transforming it into knowledge. Somewhere, hidden within this data-rich R&D environment, there may be pointers to the next pharmaceutical discovery: what proteins are encoded by these genes, what biological pathways do they impact, are these targets druggable, what kinds of molecules might interact with these targets, what adverse effects are expected?
The huge amount of data is often considered the main component of the challenge. But even when managing smaller amounts of data, informational complexity and diverse data “silos” spread across the enterprise (and externally among partners) still present a major obstacle to innovation that most informatics systems and data analysis tools simply cannot overcome.
While new technologies and specializations are resulting in enormous progress in the right direction, the data explosion they have created means that scientists today can spend about 20% of their time just managing information. The oft-repeated refrain is: “I’m spending nearly all my time, finding, processing, organizing and moving data around instead of being productive in the lab—and it’s only getting worse.”
The informatics challenge today is really a four-part puzzle around how to improve data access, data analysis, data reporting and overall team collaboration. With scientific data often locked in different database systems in various locations, data acquisition can be a complex, time-consuming, often manual and, therefore, error-prone task of cutting, pasting and joining. Scientists often do not or cannot complete these tasks, so they end up making decisions based on incomplete data or stale information collected at an earlier time. Likewise, large volumes of data can be overwhelming to analyze, sometimes requiring computational experts to intervene―and this can result in another bottleneck or the temptation to make fast decisions without the benefit of full analysis. Reporting can be another manual, labor-intensive and error-prone process resulting in a logjam of spreadsheets, PowerPoints and emails that hinders decision making with no real-time data sharing.
You and your team need to be making informed decisions every day. What’s the greatest challenge you face when it comes to accessing and sharing the right information in the right context and at the right time, so you can move your projects forward in an efficient, timely manner?
Accelrys will make a major announcement about our launch of an exciting new collaborative data access, analysis, reporting and decision support solution at the Pharmaceutical IT Congress on September 23-24 in London. If you’re at the conference, visit us to learn more. Be sure to attend Dr. Rob Brown’s presentation, “Next Generation Cheminformatics Suite for Enhancing R&D Productivity and Innovation,” in the “Managing Enterprise IT” track on Monday, September 23 at 12:20.