The clinical trial sector witnessed a lot of action in 2016. Pharmaceutical establishments are increasing their focus on this branch of medical study and operations.
From adopting a patient-centric approach, digitizing trial process and systems, revolutionizing point-of-care products and services to making changes in data aggregation and predictive modeling, clinical trial innovation has entered an even more interesting phase this year. In this post, we discuss these transformations.
Reforms in Engagement and Enrollment of Patients
Technological advancement and data are massively changing the landscape of clinical trial. Admission technologies are changing the way medical institutions enroll patients and engage with them. Big data and technologies are leveraging machine learning algorithms and structured questionnaires to increase the qualification rate of admitted patients.
From making sure the patients receive more specific and relevant information to simplifying public listed studies, subject enrollment and qualification is gaining major ground in clinical trial. With a shift from the traditional advertising-based model to the algorithm-based model, the patient recruitment process has become more effective and less expensive, provide better patient access and helps bring patients on board at a time when they are most interested in learning about the studies.
Big Data and Data Aggregation Gains Prominence in Clinical Trials
There is large data aggregation happening in the bio-pharmaceutical industry from numerous clinical systems. The vast volumes of data collected from clinical trial procedures offers immense opportunities to the core pharma and bio-pharmaceutical industry to tap the information for improved clinical trial design, site selection, monitoring insights, and decision making.
One of the landmarks of big data can finally be large-scale and improved drug development and represented advancement in the clinical trial process. Another noticeable development in data aggregation will be the creation and emergence of case studies with data on predictive modeling of clinical outcomes.
Rise in Accuracy of Predictive Modeling
With large data collection and aggregation, the industry has launched various internal data analysis functions for better understanding of clinical operations. From the quality perspective, Pfizer has come up with its first predictive modelling system to study risk during the protocol design and study education phases. Such predictive models will be used for foreseeing factors impacting GCP and quality risk during study design.
Clear Definition of and Focus on Patient Centricity
Patient centricity is becoming important in clinical trial. The FDA has raised concerns and has given deadlines on patient-centric initiatives in clinical trials. The FDA and industries agree that more patient-centric initiatives involve less burdensome studies, optimizing study protocols to enroll more patients, and creating a more engaging and convenient clinical trial environment for patients.
Greater patient involvement implies getting them engaged in designing studies that are focused on generating outcomes that are clinically useful to patients.
Ensuring Quality in Clinical Trials and Effective Monitoring
In the clinical trial territory, we will start seeing the initiation and implementation of higher-quality risk management structures, and risk and performance indicators. Quality, right from the structural level, ensures a strong base for successful risk-based monitoring.
The right analytic quality measures and the improved partnerships within and outside the industries will eventually lead to better risk assessment and mitigation from the designing and planning of clinical trials until its final execution. Overall, we will see a wider industry adoption of RBM (risk-based monitoring) that will lead to implementation of high-quality risk management plans.
Rise of Mobile Health (mHealth) and Wearables in Clinical Trials
Wearables and mHealth have taken huge strides in clinical trials. Mobile devices, wearables, and the rise of online communities are all going to aid the pharma and biotech industries in introducing innovations and advancements in the clinical trial processes and systems.
The FDA recommends the new mHealth initiatives to be in alignment with the new global guidance on Software as a Medical Device (SaMD). Wearables manufacturers and clinical trial sponsors can now use this guidance to establish their own feasibility criteria to assess and design wearables to be used in clinical trials.
The Sleep Apnea Association is conducting its first mobile health study using Apple Research Kit to measure sleep patterns and results in patients through a bring-your-own-device model (BYOD). Other initiatives like the data published on the impact of mHealth on patient engagement and subject dropout will reveal exactly what roles mHealth and wearables will play in clinical trial settings.
Clinical Trial Audits Are Set to Become More Effective
The main purpose of clinical audit is patient safety. Clinical trial audits are all set to get more effective, which means that patient safety is paid utmost attention to, the collected data is accurate, and the trial is executed in lieu with a comprehensive quality management system and risk-based audit plan.
The Clinical Trial Innovation Summit held in Boston earlier this year discussed at length the best practices and case studies for developing risk-based auditing practices, establishing CAPA plans and creating effective audit teams, the positive ripple effects we will witness in clinical trial operations throughout the year.
While the above are going to be the most promising and anticipated moves in clinical trial innovation to look forward to, outsourcing for clinical trials is going to be another trend to watch out for. Third-party vendors will be assigned various diverse and multiple clinical trial activities. Long-term quality relationships will make a marked presence in the field of clinical trial in the times to come.
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Jane Otterson is a Technical Writer at Confirm BioSciences. She specializes in the biotech sector, specifically now as it pertains to drug testing. Jane is passionate about making, sometimes complicated, scientific ideas easy to understand. When she is not writing, she enjoys reading about 3D printed organs, making fun of programs on the SyFy channel and playing various board games with family and friends. Follow her on Twitter – @jane_otterson.