In an increasingly complex data environment, pharmaceutical and biotech companies must be able to quickly identify trends and outliers, delve deep into the data and generate meaningful insights. There is also pressure to harness the capabilities of new technologies, including artificial intelligence (AI), in order to improve speed and reduce cost.

Advanced analytics leverages machine learning (ML), statistical modeling, data mining and visualizations to empower organizations to make data-driven decisions. It enables fast, accurate assessment of vast volumes of operational, clinical and RWE data across the full clinical development spectrum. 

Overcoming key pain points

Over the past 10 years, the average complexity of clinical trials has increased significantly. Unstructured data offers the opportunity for rich insights, but its lack of standardization has often made it difficult to analyze. Other common pain points include resource-intensive traditional approaches and failure to gain meaningful insights from ongoing clinical trials in a timely manner and therefore missed opportunity to enhance the chance of clinical research success. 

Access to advanced analytics is assisting in the transformation of efficiency and precision in clinical trials. Enabling access to improved site selection, more effective patient recruitment, and better-informed decision-making throughout the trial lifecycle. Collaboration with a specialist biometrics CRO provides access to the technical expertise and infrastructure needed to harness these tools effectively. These partnerships provide specialist expertise that can help address key challenges, ensure rapid and accurate data integration, and translate complex data into actionable insights. The benefits of such collaborations are streamlined trial processes, shorter timelines, and increased confidence in data-driven outcomes. 

Using advanced analytics across the clinical trial spectrum

Advanced analytics enables us to enhance insight gathering at every stage of clinical development – from data management to operation risk mitigation and medical monitoring to scientific surveillance. The use of advanced analytics has been shown to expediate data review by 50% and increase medical monitoring efficiency by up to 75%.

This success depends on consolidating multiple data sources into a unified data platform which offers visualizations and analytics across clinical data, metadata, and audit trails. Companies must be able to choose specific tools to fit their needs or budget – whether for recruitment forecasting, risk-based quality management (RBQM) or DMC.

The use of a RBQM tool to support critical processes like Risk Assessment, Central Monitoring, Issue Management, Risk Reassessment, Targeted Site Monitoring, and KRI Tracking can accelerate review by up to 50%. It can also drive further efficiencies by assigning risk scores to different clinical sites or activities based on predefined criteria to enable effective prioritization of site visits.

The integration of various unstructured data sources—including Interactive Response Technology (IRT) and electronic diaries (eDiaries)—into intuitive, user-friendly dashboards is transforming the management of clinical trials. These dashboards enable researchers to quickly identify trends, anomalies, and outliers by consolidating diverse datasets into real-time visualizations. This capability enhances data interpretation, drives actionable insights, and supports proactive decision-making, allowing teams to address issues early and optimize clinical trial operations.

Advanced data visualizations provide near real-time updates and allow stakeholders to customize dashboards to align with their specific clinical objectives. This ensures that critical information is both accessible and actionable, accelerating development timelines, improving operational efficiency, and supporting a smoother path to regulatory approval.

By facilitating better visibility, collaboration, and data-driven decision-making across the clinical lifecycle, this approach ultimately leads to improved trial outcomes and enhanced cross-functional alignment.

Overcoming recruitment challenges

Like many organizations, Sponsor X frequently failed to meet the target of administering the first treatment to the last participant within the planned time frame. This was primarily due to an inability to swiftly identify bottlenecks within their studies and formulate effective solutions. 

The creation of a model which provided insights into recruitment efforts and predicted when the last participant would receive treatment granted users invaluable insights into the underlying causes of recruitment challenges – from site-level issues, such as country and site approvals, to recruitment hurdles, like screening failure rates. The integration of a novel Kaplan-Meier model enabled the prediction of participant progression based on their screening duration.

Outcomes for Sponsor X included accelerated trial completion, proactive enrolment management and data-driven decision making. Integrating the Kaplan-Meier model also enabled different countries to optimize their sites based on participants in screening and their probabilities of progression. This precision reduced timelines by 3 weeks, which resulted in significant savings.

Rapid access to advanced analytics

With clinical trial complexity, duration and costs continuing to rise, companies can enhance clinical development through rapid access to high quality data signals and accurate and meaningful advanced analytics, enabling improved decision-making and efficiency. 

One way to achieve this is to use a combination of modular and bespoke options. Companies should have the option to choose between ‘out of the box’ solutions which are ready to use or customizable options which are tailored to their specific trial needs. 

A unified advanced analytics platform should offer users interactive elements to explore and render rich information from a single view, a centralized platform for seamless management across clinical trial phases and a shared suite of tools for collaboration across teams. Together, these elements allow a holistic approach to medical monitoring, clinical operations, safety and RBQM.

Driving actionable insights

Data-driven insights are crucial for clinical trial success. Advanced analytics offer the opportunity to drive more efficient and effective processes and improve decision making. By combining technological innovations with biometric clinical monitoring expertise, we can drive and deliver actionable insights for users and provide sponsors with complete data integration, seamlessly from any source.

Ping-Chung Chang is currently the Head of Business Transformation and China General Manager at Phastar. Ping has been a biostatistician in the clinical industry since early 2002 and has had worked for pharmaceutical, biotech and CRO companies through the years in both US and China. Ping is an experienced leader in regulatory submissions, large global team operations and CRO business management. Through his CRO career, Ping has been heavily involved in optimizing service models with client companies as well as in delivering effective collaborations.