Life Sciences Domain Expertise

The Situation: A large biopharmaceutical company was experiencing a significant growth in the number and diversity of clinical trials. In addition, the business was enlisting help from more specialized external partners to participate in all aspects of clinical trials. This created increasing challenges with management of clinical samples throughout the sample lifecycle including planning, tracking, inventory, assay development and testing, and results data management. The company was seeking to re-architect their clinical sample management with an optimized approach that would also allow for versatility depending on the needs of a given clinical trial.

The Situation: Initiatives that begin with a product focus often fail. Yet, this happens time and again in the life sciences industry. The clinical operations group of a life sciences company initiated a clinical trial management system (CTMS) project without the participation of several key stakeholder groups. They engaged a CTMS vendor to write their requirements and then selected a solution based on each vendor’s standard demonstrations in which the vendor controlled the environment and the demo content. Shortly thereafter, senior management stopped the project due to insufficient due diligence, limited adherence to IT standards, and lack of confidence in the approach. ResultWorks was asked to assess the project and to create a new strategy for the CTMS effort.

The Situation: Faced with increasing pressure to accelerate delivery of high-quality data for clinical decisions, the clinical data management department of a major pharmaceutical company knew they must radically change how they operated, but was unsure what the desired future state should encompass and unsure how to approach this large undertaking.

The Situation: A global pharmaceutical company recognized that 20% of clinical assay result datasets were consuming 80% of resources in terms of collecting; merging and formatting the results to make them suitable for loading into clinical data repositories. The majority of assays (the “80%”) fall into the established data management process; they are well established mature methods and are available through larger commercial labs. These assay results are typically consolidated through the Central Laboratory vendor and provided to the Sponsor as regular well formatted and sample reconciled data feeds.

The Situation: A mid-sized biotech organization with US and EU sites recognized a need for comprehensive tracking of on-study samples and remote virtual inventory. They desired a commercial technology vendor to provide the solution. The project duration, including finalization of the solution selection recommendation had to be completed within four months, requiring an accelerated approached to the development of vision, requirements, and solution selection.

The Situation: The clinical development unit of a leading, global pharmaceutical company was challenged by its complicated technology landscape comprised of commercial-off-the-shelf transactional systems from multiple vendors, an aging clinical data management and biometrics toolset and platform, and multiple disparate approaches to data integration.

The Situation: Many pharmaceutical companies are increasingly focused on developing strategies that will enable them to realize the benefits of using mobile health and digital biomarker data collection technology on clinical trials. Sponsors are challenged to keep pace with the rate of change amidst the rapid emergence of new devices, solutions, and vendors, to understand what capabilities exist, and to implement those capabilities in an effective, efficient, and compliant manner.

The Situation: After many years of organic growth, this biotechnology company’s expansion in global development initiatives increased many-fold over the previous five years. For a long period, systems were implemented somewhat ad hoc to solve problems of the day. As the business accelerated, more and more human capital was needed to tackle the increasing volume of studies and submissions. This required diligent attention to numerous manual processes with a plethora of spreadsheet trackers, word of mouth communications, data movement via spreadsheets, data re-entry, etc. Business growth inevitably precipitated the need to consider more effective means of managing the increase in development studies and submissions, as well as all of the supporting activities, and in particular, the management of data.