Innovation in screening software

Software development for early-stage drug discovery must meet many needs – flexibility, compatibility and scalability. Dr Oliver Leven, Genedata, offers an insight into the R&D requirements of screening data analysis.

To appreciate today’s landscape of different software systems applied in early-stage drug discovery, it helps to review the evolution of software concepts. Broadly speaking, between 1990 and 2000, two major types of software applications emerged to support drug discovery research processes:

a) packages introduced by research IT departments to address broad or specific needs in scientific analysis or data handling; and b) software built by individuals to address a single issue at hand, which was not supported by option a). The former had a defined life cycle, was fully documented and supported; the latter was more of a one-off with the potential to be adapted to other needs yet was not well-supported by research IT departments, so it rarely became part of a supported package. No single software solution met cross-departmental research needs, resulting in many different installations of software packages that lacked compatibility and scalability. Moreover, they did not advance productivity and innovation.

At the turn of this century, new workflow-based software applications were introduced to help bridge the two camps. Based on a set of pre-defined rules, specific applications were supposed to automate data processing, yet offer the flexibility to accommodate slightly different workflows. While such applications were a major step forward, they did not prove to be truly scalable nor flexible enough, particularly when it came to meeting evolving requirements created by newer technologies like high content screening (HCS), high throughput screening (HTS) and other assays, e.g. label-free.