Five predictions for the future of decentralized clinical trials

The message was clear from industry leaders last year – today’s clinical trials need decentralized solutions. More complexity means intensive data capture and continuous flows are essential, and vital strategic decisions rely on real-time data analysis and intelligence. Existing point and unified solutions cannot fully meet the challenges and adapt to this dynamic world of decentralized trials, digital transformation, and data science.

Whether virtually or in-person, leaders emphasized that a holistic clinical technology platform is essential to enable decentralized clinical trials (DCT) today. Based upon the organization, clinical portfolio, and outsourcing model, DCT will look like many different things across the clinical trials landscape.

1. The role of data managers will evolve through the availability of innovative technology solutions to speed trial data flow and analyses

As data managers evolve to become data scientists, there will be people who are experienced in the world of traditional clinical data management. However, without a broader base of technology skills in their arsenal, they will be left behind as the rapid pace of clinical development continues, requiring real-time analytics. A crucial node in the process, their responsibility is to stitch all the data together – a responsibility made more complex by the variety of data sources such as real-world evidence, wearables, imaging, biomarker labs and electronic patient reported outcomes (ePRO)/electronic clinical outcome assessment (eCOA). They need a platform that supports the range of technical skills in the user base, allowing them to leverage workflows and see various insights without the need for any additional programming skills or having to operate through a variety of different tools and systems. With greater support from sophisticated analytical software, data managers will be empowered to create a new paradigm in trial efficiency and effectiveness.

2. There should be a single source of truth

The industry has a long history of bolting on bits and pieces, trying to do something new with old tools that are not up to the task, with data remaining separate or adding time and risk to map and translate between systems. A holistic platform is required. One that can capture the range of different data types that are needed, whether that be from traditional clinical trial data or more innovative data points such as wearables. Integrating disparate data from third parties – for example Python or R – can be made seamless with the right technology. Sponsors require one single source of truth to analyze, process and visualize data, in real time, to enable teams to run DCTs seamlessly and ensure clean, accurate data they can trust.

3. Artificial intelligence will lead us to the future

Adoption of AI is happening throughout many industries, and within pharmaceutical and clinical trials, it is proving itself as a valuable tool for a range of data driven processes. The incorporation of AI algorithms to interpret trial data instantaneously is very promising and has great potential to revolutionize data analysis and drive the even faster identification and development of new therapies. An example of this are recent AI systems that are based on a principle called deep learning. Rather than looking for tumor features defined in advance by a programmer, researchers give the systems a large data set comprising thousands of real-world examples of lung CT scans, some with cancer and some without. It is then up to the systems to figure out for themselves what a tumor is. From this, the machines learn for themselves what a lung cancer nodule looks like. The results of that analysis can then be assessed, deciding whether results need to be analyzed further by human experts, depending on the risk profile of the client, all in one cohesive platform. There is an opportunity for a technology that allows trial data to be explored as insights and that can be used by anyone regardless of technical ability.

4. Risk-based monitoring (RBM) takes center stage

The safety and quality of clinical trials are a high priority – by identifying, assessing, monitoring, and mitigating the risks that affect the quality or safety of a study, you can improve patient safety whilst lowering the attendant risk profile. To run efficient DCTs, RBM strategies must be adopted, using a technology that offers up to the minute visualizations, alerts, and notifications. A platform is needed that can also create workflows, such as a safety workflow or medical monitoring, and that has threshold trigger actions when certain data points are reached. Sponsors will achieve their goals of minimizing the risk of trials through using a technology that was built to enable DCTs.

5. Disparate data will become more clear

With centralized studies, the range of data sources has been manageable and easily controlled through current processes. However, with DCTs, there are more data types, more volume, and most, if not all, would be eSource data e.g., direct data capture, ePRO, eCOA, central labs – both structured and unstructured. DCT technologies need to have consistency across the data sources by mapping it into one central system, allowing for easier centralized change management, for instance with protocol amendments. As with all clinical trials, ensuring that disparate data can be easily integrated and is immediately available to users for review to aid fast decision making is critical for the clinical program, compliance, and safety of patients. With the right technology in place, sponsors can realize their goals of running flexible, successful trials with more patients, using decentralized methods.

Step forward

Moving clinical trials forward in our new digital reality is not about loosely linked point solutions or so-called unified solutions. It is now vital to have a data strategy built around technology platforms that can truly support both current and future health needs.

If you’re interested in knowing more, you can watch our on-demand webinar: ’Clinical trials in 3D: a case study in DCT implementation’, or if you want to hear more about encapsia’s capabilities, contact us.

Après l’âge de 40 ans, la dysfonction érectile chez l’homme n’est pas considérée comme une maladie mais comme un état physiologique. Les causes de l’infertilité masculine peuvent inclure des maladies du système endocrinien, un processus infectieux commun ou des troubles de la circulation pelvienne. Lors du diagnostic des causes du problème, le médecin traitant prend en compte l’ensemble des facteurs auxquels l’homme n’a pas prêté attention auparavant : Absence d’érection pendant l’intimité . Le traitement fait appel à des méthodes conservatrices et chirurgicales. Le traitement conservateur vise à améliorer la qualité de la vie sexuelle de l’homme et à augmenter le taux de testostérone dans le sang, qui est connu pour être responsable de la fonction sexuelle, Acheter Viagra.