Clinical trials are an integral component of drug development. They allow researchers to test drugs, diets, medical devices, or digital therapeutic tools – but only with proper data management during each clinical trial process can quality and accuracy be guaranteed.
The eCRF designer allows for creating custom forms based on industry-wide standards for input fields and layout, including programming edit checks.
eCRF Design
CRFs, or Case Report Forms, are digital questionnaires used to collect data on clinical trial participants. CRFs can be filled out piecemeal by a clinical research coordinator, uploaded in bulk from another database such as an imaging system or transferred directly from another system like imaging systems. CRFs contain vital data that biostatisticians will use to draw their analyses regarding study results so it’s essential that CRFs be designed carefully from their inception in order to collect all necessary information for research hypothesis fulfillment.
At the start of any clinical research investigation, it is necessary to create a research hypothesis. This will enable investigators to know exactly which information needs to be gathered in order to support or refute their hypothesis and which data can be discarded. It’s also recommended to develop a statistical Analysis Plan, or SAP, as this will detail how all the collected information will be utilized when final analysis of results takes place.
Once a hypothesis has been established, the next step should be designing an electronic Case Report Form (eCRF). As part of the design process it can be beneficial to include as many collaborators – from clinical research associates and research nurses through site investigators and biostatisticians. Doing this will allow more eyes to spot redundancies or inconsistencies which might skew final study results.
Designing an effective eCRF can be a complex endeavor. Many factors must be considered, including making sure all necessary trial information is captured within it, writing questions in an understandable language, and eliminating duplicated information on different pages of the CRF. Furthermore, how answers will be coded could make all the difference when mapping to SDTM (Study Data Tabulation Model) datasets.
Once an eCRF is designed, it should be thoroughly tested to make sure it operates efficiently. Testing should involve internal and external stakeholders alike; scenarios for testing include staff reading/writing on it, making changes, asking and answering queries and receiving opinions/suggestions from participants.
eTMF Design
Documenting clinical trials can be an intimidating task, yet keeping track of all necessary documents can be even more complex. With increasing amounts of paperwork needed throughout a trial, it becomes even more essential that all necessary files are collected and stored efficiently so as to facilitate easy collaboration and access.
An electronic Trial Master File (eTMF) can come in handy here. A TMF serves as a central repository where all essential clinical trial documents can be stored and managed – typically required by regulatory bodies for review before approval of drugs and medical devices.
The DIA TMF Reference Model is an industry standard structure widely accepted by global regulatory agencies as the preferred means of managing content of TMFs. This model offers standard taxonomies and metadata structures as well as outlining an accepted definition of TMF content using standard nomenclature terms. Furthermore, the TMF Reference Model offers an architecture for document storage at three levels: trial level, country level and site level.
Selecting an eTMF design compatible with the DIA TMF Reference Model is key to ensuring that your team can efficiently collaborate on documents required for submission. Furthermore, an effective eTMF should provide tools such as audit trail, user account controls, archiving regulations and electronic signatures in order to help maintain compliance and reduce burdens on team members.
Real-time visibility into document collection progress is also a must in an eTMF, making it easier for your team to quickly add missing documents and quickly identify which essential ones needing adding. Furthermore, an eTMF should integrate seamlessly with CDMS and CTMS systems in order to provide one source of truth for clinical trial data, making analysis simple while supporting decision making around performance enhancement and efficiency enhancement. A comprehensive training program and support can ensure seamless adoption by your team members resulting in an enhanced trial experience overall.
Smart Contracts
Smart contracts provide an automated solution for several key elements of clinical trials, enabling PIs and clinical research teams to automate multiple tasks related to clinical trials. Smart contracts are programmed into blockchain networks to perform certain functions automatically and can record data that can be trusted and verified by members of the network, without altering it afterwards – vital in ensuring only original information is used; for instance, smart contracts could verify whether an SAE report was filed by an investigator as well as record when patients drop out from trials.
Clinical trials can be complex affairs that involve data management. Current processes tend to take a considerable amount of time and rely on third parties for verification purposes, however. Blockchain technology offers unique software designs that can assist these processes – for instance, smart contracts automate matching participants with trials that suit them thus saving both time and resources.
Smart contracts can also be used to oversee the trial process, making it simpler and faster to ensure it is progressing according to plan. Furthermore, this system will automatically send notifications to participants who match up with trials asking them to authenticate themselves via fingerprint authentication; this increases patient engagement while simultaneously decreasing data requirements, speeding up management.
Smart clinical research organization aren’t just limited to clinical trials; they have applications across various industries as well. For instance, smart contracts can be used automatically settle healthcare payments to eliminate overbilling and fraud, as well as track music ownership and royalty payments, track royalty payments for musicians, automate the processing of insurance claims, track music ownership rights or track music royalty payments.
Management of clinical trials can be complex and expensive due to inaccurate, unstructured and unreliable data used during trials. Blockchain technology offers a solution by offering an alternative means of storing clinical trial data; additionally it enables CTMS with faster access and increased security through auditable environments.
Query Management
As part of any clinical trial, staff will often need to ask queries about the data collected by participants. These queries serve to check for accuracy, compliance with regulatory guidelines and standards, overall study quality and overall study viability. When creating such queries it is imperative that they contain all of the pertinent information that needs to be provided so as to resolve issues quickly; such queries must then be sent out and provided access by all parties that require access.
CDISC defines queries as questions asked about data items collected for clinical trials, designed to uncover any discrepancies or inconsistencies within it that could jeopardise study results if left uncorrected. Historically, queries were created manually during on-site visits when clinical research associates (CRAs) or monitors would manually go through all source documents, case report forms (CRFs) and paperwork to check completion and accuracy – an expensive and inefficient process with ample room for error.
Today, fully validated EDC systems can automatically generate queries when values fall outside their intended range, providing faster and more accurate responses to outlier values. Additionally, these tools document any corrections made for enhanced regulatory compliance.
Be sure to select a CDMS solution with built-in query management capabilities when selecting one for your study. An effective solution should allow automated queries to be activated when values fall outside their intended range or when an investigator enters something which conflicts with clinical protocol regulations.
An effective query management system enables users to save queries as private or share them among team members, saving both time and resources by eliminating manual tracking by an CRA or CTM.
Clinical trials require both time and money investments, making expert-level management plans essential from its inception. A strong DMP will ensure all the work is organized efficiently, with clear responsibilities assigned to every member of your research team. Furthermore, your DMP should evolve along with your study as it progresses and changes; for example if laboratory companies change during your research endeavor requiring updates to accommodate data migration between these labs requiring updates to your DMP in order to integrate both sets of data efficiently into one.
