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Risk-based Monitoring Tools in Drug Development and Research

By January 13, 2020No Comments
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Conduct Science promotes new generations of tools for science tech transferred from academic institutions including mazes, digital health apps, virtual reality and drones for science. Our news promotes the best new methodologies in science.
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Risk-based Monitoring and Risk-based Monitoring Tools in Research

Risk-based monitoring (RBM) tools are essential in drug development and digital health research. Due to the complexity of medical research (with strict regulatory practices, documentation requirements, and ethical considerations), clinical trial monitoring is needed to ensure protocol compliance, data quality, and participant safety. To help sponsors and researchers overcome possible challenges and financial burdens, regulatory bodies worldwide agree that a risk-based approach in monitoring is crucial. The ICH-GCP guidelines, for instance, states that clinical trial observations and risk-based monitoring tools are mandatory in health research and drug development (Hurley et al., 2016).

Unlike standard burdensome procedures, such as on-site visits and source data verification, risk-based monitoring is highly effective. Risk-based monitoring is an innovative practice which can help researchers reduce the frequency of monitoring and incorporate different assessments in practice (e.g., on-site and remote monitoring). What’s more, it tackles various factors of research, such as high-risk sites, triggered events, data quality, and patients’ well-being.

Risk-based monitoring tools, in particular, allow experts to implement risk-based assessment, tailor their monitoring practices, reduce risks, and optimize clinical outcomes. Note that critical data and risks are often associated with data integrity, novel products, research bodies, study design, and participants’ safety. Risk-based monitoring tools can also support ongoing supervision in real time and improve long-term health benefits. They can help reshape the nature of pharmaceutical drug discovery and digital health.

Risk-based Monitoring Tools in Detail

Researchers worldwide agree that risk-based monitoring can improve drug development and patient outcomes. Risk-based monitoring tools can help researchers implement risk-based monitoring in practice and overcome challenges in software technology. They can improve the conduct, management, and audit of clinical trials at all phases of research. A recent literature review revealed that although there isn’t an existing set of regulations regarding risk-based practices, risk categories are normally defined as low, medium, and high-risk (Hurley et al., 2016). Note that low-risk studies require less data monitoring. Having clear categories and taxonomy can ensure trial accuracy, patients’ safety, and data collection. It’s interesting to mention that Phase I studies are usually flagged as a high-risk category.

The implementation of risk-based monitoring tools should also tackle different types of monitoring in research. Note that centralized monitoring, statistical assessment, reduced monitoring, remote observations, and on-site procedures are among the most effective monitoring techniques (Molloy & Henley, 2016). Interestingly, centralized monitoring is a major component of risk-based monitoring, which reveals numerous advantages over standard assessments.

In addition, Hurley and colleagues (2016) concluded that risk-based monitoring tools could be paper-based, operated as a Service as a System (SaaS) or supported by Excel. Note that with the recent shift in digital health practices, electronic data and digital solutions are becoming more and more popular in medical research. Most of all, experts should embrace the fact that risk assessment is a continuous process and requires real-time analysis to improve drug development and health outcomes.

Taxonomy of Critical Data and Risks in Clinical Trials

For the successful implementation of risk-based monitoring tools, detection of critical data (which can be flagged as a risk) is crucial. The most common risks in medical research are linked to data integrity and ethical regulations. Interestingly, some experts suggest using a ‘traffic light system’ during risk assessments to identify and visualize low, medium, and high risks. One of the most popular taxonomies identifies 12 risks (Jongen et al., 2016), categorized into three groups:

What – Investigational medicinal products (IMP): When it comes to novel products, numerous risks can arise. One of the major unknowns in medical research revolves around the existing knowledge about new treatments in humans. Adverse effects and toxic compounds may be lethal. Since Phase I and Phase II trials pose high risks for participants, new indications and toxicological effects must be tested thoughtfully. Another major risk tackles the nature of the actual treatment. In trials where no medications for potential side effects are available, or where interventions continue without any benefits for participants, risks are high. Let’s not forget that patient safety and well-being come first. The third concern about an experimental product comes down to potential large populations. This is highly relevant for data integrity, and marketing authorization approval as a drug designed for big populations may harm a large number of people. The last challenge in the investigational medicinal products category tackles high-risk drugs. Note that there are three types of risk characteristics which a product may hold: pharmacology, route of administration, and stability. As stated above, new indications, possible side effects, and storage errors must be considered in order to reduce adverse effects and negative outcomes.

By whom – Investigators, site, sponsors: Research is a complex process which involves researchers, sponsors, participants, practitioners, and committees. When it comes to staff and sponsors, professionalism, experience, and reputation become crucial. In fact, these three characteristics may affect data integrity and ethical risks. Normally, commercial organizations and experienced researchers tend to identify risks and ensure data integrity. The reputation of an organization also affects risks and outcomes; it can affect approval decisions and market authorization. Thus, training of staff, good documentation practices, and protocols become vital.

How – Design: A safe drug and professional staff is not enough to guarantee success. The study design becomes crucial. Participants characteristics, for example, may correlate with risks. Trials with a large number of subjects (e.g., Phase III studies) pose both ethical concerns and risk for data integrity. When vulnerable people or participants across emergence settings are enrolled, risks also increase. Another aspect which is associated with high risk is the potentially high burden to participants. Invasive procedures and time-consuming methods, for example, often lead to high risks. The duration of the actual treatment also needs to be considered. Usually, longer treatments correlate with high occurrences of adverse effects. The actual study design is also a crucial factor. Studies with multiple phases, sites, and research bodies – as well as those that employ new assessment tools and complex procedures – pose a high risk for data integrity. Last but not least, the conduct of the study is essential. Any breaches of the protocol must be tackled to prevent possible failures and adverse effects. Good management and documentation practices become fundamental.

Benefits of Risk-based Monitoring Tools

Risk-based monitoring tools are essential in clinical research. They reveal numerous benefits in practice, such as reduced costs, decreased time to approval of a new product, and lower risks. It’s not a secret that drug development is a complex process. It starts with research on a molecular level to support the understanding of the disease. Once a possible target and compounds have been identified, preclinical testing in non-humans can begin; followed by clinical trials in humans, marketing, and patenting (Torjesen, 2015). Unfortunately, stats show that approximately five in 5,000 drugs enter human testing; with only one of these five products being approved. The entire testing process is prone to delays (