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Collecting and Managing Animal Study Data

By Eric Ibsen

May 12, 2006 | The pivotal decision to pursue preclinical development of a drug candidate is based on animal efficacy and safety studies. Remarkably, 80 percent of these studies are still conducted as they were 20 years ago — by manually recording data in paper notebooks and electronic spreadsheets. Commercially available animal study management systems (ASMSs) have been recently developed and are now being successfully deployed. ASMSs are essentially configured electronic laboratory notebooks (ELNs) that automate the processes of study design, data collection, task management, data analysis, graphing, and report generation and enable enterprisewide access to study information for current and archived studies.

The inefficiencies associated with manual study conduct are estimated at 25 to 50 percent. Data collection commonly involves one or two technicians recording data on paper. Data are then entered or transcribed into spreadsheets, manipulated and graphed, or reformatted for transfer into statistical analysis software. In some cases, data are then reentered into the institutional database. Data and results are pasted into the research notebook, which is later microfiched and archived. Twenty-five percent of surveyed scientists say they spend more than five hours per week transcribing data into notebooks. This constitutes almost three days per month of wasted time.

ASMSs streamline the data collection process by capturing data directly from measurement devices and managing it centrally. Data manipulation is minimized because the software automatically generates graphs and analyses that have been formatted to organizational standards, saving substantial time and providing a consistent output format for review. Instead of waiting for the study data to be collated and analyzed, research managers can view results immediately and can share progress with other departments. This facilitates error detection, next-step planning, and decision making across the research enterprise. The costs for study management software tools are recouped rather quickly. The return on investment for such programs is conservatively estimated to be $1,600 to $3,400 per study.

Data Security and Accessibility
Investigators rarely follow a consistent data formatting convention even within the same institution, hindering the comparison of data between studies. Furthermore, spreadsheets usually manage only measurement data, while the information about the study conditions (such as method details and animal and drug information), if collected at all, exist in separate files or documents that frequently end up in data islands that are inaccessible to the organization at large.

The average turnover rate for biologists in the life sciences is 15 percent annually, and the critical details of animal studies, models, and project histories that reside primarily in the memory of research personnel often leave the company with them. This alarming problem is resolved with study automation software. ASMSs provide researchers and management with immediate access to study information and results. All study information is centrally located and formatted, enabling researchers to search for particular information and drill down into all current and previously conducted studies and to quickly analyze and compare results between and across studies.

Quality and Integrity
The likelihood of recording, calculation, transposition, and transcriptional errors increases with each manipulation. Since most research studies are not subject to a thorough QA review, undetected errors can be compounded, potentially compromising the integrity of study conclusions. ASMSs facilitate nomenclature enforcement and minimize data recording errors by the use of dropdown menus and device connectivity. The accidental destruction, loss, and theft of notebooks as well as the inadvertent deletion of or changes to datasheets and intentional falsification are serious problems that are largely solved by implementing an ASMS.

In-House System Development
The core competency of biopharmaceutical companies is primarily drug discovery and development, not software development. Successful in-house development of animal study management programs has been virtually nonexistent. One report concluded that just 16 percent of software projects actually succeed, finishing on time and on budget, and almost one-third of projects are cancelled prior to completion. Committing to develop an in-house system is a bit like investing in a black box: It is difficult to forecast the ultimate cost, completion date, resultant functionality, reliability, usability, flexibility, and overall quality of the final product. Several large companies have attempted to build ASMSs with the guidance of experienced scientists, but have not succeeded.

Economic pressures are now driving biopharma to examine and optimize their processes by eliminating redundancies and inefficiencies. The relatively modest investment in software tools to collect and manage animal study information can be justified by the improvements in efficiency, data quality, information accessibility, and the resultant decreases in costs and time to market for new drugs.


Eric Ibsen is chief science officer at Studylog Systems in South San Francisco. E-mail:


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