The future position of CTMS in the market will be dictated by how these technologies leverage key opportunities created by changes in the technology landscape, as well as changes in the way the industry executes clinical trials. The main factors that will contribute to the future positioning of CTMS include:
• capitalizing on analytics •
improving and driving the workflow
• consolidating master data; and •
becoming the central, integrated management solution.
The Impact of Analytics on CTMS Functionality Considerable value can be added to optimize decision-making and making the process more strategic by implementing data analytics tools. CTMS becomes more than just a project or trial management environment when clinical and performance data can be used to help predict the success of a trial, understand the feasibility of the trial design, or even change the parameters of a protocol or study design. The ultimate result is a more successful and efficient clinical trial. Cost reductions can be achieved by modifying various parameters including the number of patients recruited in a trial, the number of trials executed, and the number of sites used—all of which can drive a cost reduction of ~30 % in trial expenditures.
Analytics will prove even more valuable for clinical trial execution where the value of external data, including electronic health records (EHRs), and payer and other pharmaco-economic data, can contribute to the protocol design and feasibility analysis of a trial. In analyzing the data from previous trials, these findings could be applied to make decisions regarding future trials, thus increasing the chances of success.
To meet future requirements, as described above, CTMS needs to take advantage of all existing data, not just CTMS data. The insights deduced can assist in making decisions about clinical trials before they commence. This is considered predictive analytics or predictive feasibility analytics.
Information about a clinical trial, such as: the type of trial; the therapeutic area; country of conduct; patient numbers; and details of what the exclusion/inclusion criteria are, can be determined by advanced CTMS capable of mining data from previous trials to determine the current trial feasibility and the chances of meeting overall deadlines. At the fundamental level, a CTMS needs to evolve to a point where it is not just the execution center but also a core to leverage data to perform predictive analysis and improve the overall design of the trials from the start.
Lastly, CTMS can become a central hub that enables adaptive trials. Providing the dashboards required to make the rapid decisions that shape and guide the path of adaptive trials design requires access to key data from clinical systems, rapid analytics, effective visualization, and future modeling of the expected changes. This capability is currently being managed through ad hoc tools, and a packaged, consistent solution would allow the adaptive trial model to be scaled appropriately within an individual company.
The Role of CTMS in Improving Workflow The strength of CTMS lies in addressing shortfalls in the operational side of clinical research. This can include site performance tracking and management, resource and supply chain management, and regulatory document management. It can be argued that non-clinical
workflow inefficiencies have as much impact on the cost of clinical research as working with paper case-report forms (CRFs).
CTMS can excel in its ability to calculate performance metrics and subsequently support rapid business decisions. Performance data can be utilized to aid in constructing proposals that offer the sponsor a truer picture of what can be achieved within agreed timescales. If an organization can observe its performance in certain tasks—or how effectively it carries out tasks in a certain location—this data can be harnessed to optimize workflow, thereby creating a predictive, rather than a reactive, system. This use of data can have positive implications for optimizing decision-making processes and, ultimately, benefiting the contract research organization (CRO)/sponsor relationship.
One area that can be harmonized—and is on the way to being so within biopharmaceutical—is the definition of models in which the execution or engagement of the information provided by a site is being standardized. By incorporating a global registration of sites across clients and sponsors the model would be vastly simplified. By simplifying the clinical trial model a site should be able to perform trials more easily as opposed to going through the significant effort seen currently.
To achieve the best levels of performance, CTMS will also need to play an increasingly significant part in driving high-performance clinical trial execution. The central position of the CTMS in the overall information cycle is further complicated by the wide range of stakeholders involved in CTMS implementation. Although it can be noted that study management must drive the implementation, the study management group must collect and consider input from other groups such as data management, finance, and contract management. CTMS that is built on open architecture and facilitates data exchange with third-party applications can bring significant cost savings to biopharmaceutical companies and CROs.
Consolidating Master Data
Most biopharmaceutical companies utilizing CTMS are looking at master data management opportunities, where key, non-transactional data, such as investigator names and addresses that are often recorded in multiple places, are handled once and unnecessary repetition is therefore avoided. Master data management allows for key data to be stored in a higher quality format across multiple systems while a centrally-managed approach allows for significantly better control over the key data.
The ability to handle large quantities of changing core data will be a vital element to optimizing the clinical trial process. Master data management strategies can ensure that key data are consistent, definitive, and of high quality. The benefits of a master data management solution can be realized by utilizing technology to bring all of the key data together in an integrated fashion.
Currently, data is now coming directly from source systems and standardized, which vastly improves the data quality. In the past, key data, such as an investigator’s professional details, were entered manually and biopharmaceutical companies could have several different variations of an investigator’s name recorded even though they were the same person. Its central position in data flow makes CTMS ideally suited to drive master data management processes and utilize the master data to support quicker decision-making.
THE POWER OF CTMS—INTEGRATION, INTEROPERABILITY, AND COLLABORATION
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