White Papers

  1. Budget Management And Forecasting For Clinical Trials For Clinical Trials

    Why are budgeting and forecasting for clinical trials so challenging today? From an industry perspective, trial costs, scope, globalization, and complexity continue to rise along with pressures for greater time and cost efficiencies to support expanded pipelines and profits.

  2. Embracing Clinical Trial Technology: The Necessity Of Financial Lifecycle Systems

    The automation of clinical trials has been an ongoing evolution, and one that benefits the collection of trial and study management data. Over the past decade, the industry has eliminated many manual processes, such as the handling of paper case report forms and the time-consuming process of double data entry with electronic data capture.

  3. Enterprise Quality Management Of Clinical Trials

    Although it would be hard to find two people who describe TQM in the same way, important elements that are usually noted include organizational involvement at all levels, customer focus, and results that are measured, analyzed, and reviewed by management both quantitatively and qualitatively. By Kristin Mauri, PMP Senior Director Global Consulting, eHealth Solutions, Bioclinica

  4. Become A High-Performing Clinical Site: Tools For Hospitals, Clinics, And Academic Centers

    This paper will give you the keys to set up a new clinical site, find the right model, pass the sponsors’ feasibility processes, acquire the right technologies, familiarize yourself with rules and regulations, and successfully mitigate risks.

  5. The 3 Pillars Of A Life Science Quality Management System

    As life science companies progress through clinical development towards regulatory submission, if a quality management and process is not laid out from the beginning they face significant risks.

  6. IRT: Improve Quality And Efficiency The Clinical Study Build Process

    Historically, IRT study build processes followed a sequential, waterfall approach that is designed to reduce development rework and cost by ensuring requirements are correct before allocating the larger, more expensive project team. This approach utilizes the design–build–test lifecycle, iterating as needed until all requirements have been validated and approved by the stakeholders via user acceptance testing. These historic (and sometimes even current) approaches to IRT study build introduce extra costs, time, and — most importantly — errors that can affect the ability to launch the study on time or run the study as efficiently as possible. While incremental improvements seen so far in the industry are both welcome and meaningful, it is necessary for a broad change across the industry to fully embrace Agile IRT and the benefits that will ultimately accrue to the sites running studies and their patients.

  7. Leveraging Time-Tested Assets For A Shift In Site Contracting & Patient Enrollment

    The unfailing ability to complete enrollment on time, every time, has been the greatest yet most elusive need among clinical trial managers. While the value of the external patient is becoming more apparent, finding optimum solutions for integrating them into a study’s enrollment strategy is not so obvious. In their struggle to find answers, clinical trial managers experiment with, and try to piece together, services and offerings from a wide and disparate range of sources. The results are as varied as the choices. Now, a new approach to patient enrollment is emerging – one that could change the world of clinical trials.

  8. The 3 Cs You Should Expect From Your Pharma Service Provider

    When asked about the biggest challenges to the pharmaceutical company sponsor-contract service provider relationship, sponsors and service providers offer pretty consistent responses.  

  9. Is it Time To Upgrade To Electronic Drug Accountability?

    It’s no secret that the adoption of new technologies in support of clinical trials moves at a pace considerably slower than other industries. Disruptive technologies in other sectors can change business models almost overnight.

  10. Study Startup: The Last Major Frontier In Automating Clinical Operations

    The industry has stepped up with various cloud-based solutions such as clinical trial management systems (CTMS), electronic data capture (EDC), and the electronic trial master file (eTMF)—all quantum leaps—yet lengthy cycle times, lasting nearly seven years,1 are still commonplace. A key reason is that they do not address the one part of a study’s lifecycle that strongly impacts the overall timeline of clinical trial conduct—study startup (SSU). As more stakeholders acknowledge that better SSU processes are essential for shorter clinical trial timelines, SSU has become the last major frontier in clinical trial automation, the final holdout where spreadsheet methodology still looms large, and where innovation is making a resounding difference.