How patient suites are reshaping the future of clinical trials

Anthony Mikulaschek, VP - DP&S Patient Commercial Strategy, IQVIA, suggests that to overcome challenges and reduce the potential for costly errors, clinical trials must implement an integrated data strategy utilising a patient suite

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Developing a successful clinical trial is like laying a foundation — every brick must be placed with precision. Each tool, workflow and touchpoint must align seamlessly to support a reliable structure. Any misalignment introduces risks that can compromise the trial’s integrity and ability to deliver the endpoints required. In today’s increasingly complex research landscape, this foundation is digital.

From patient enrollment to final data capture, each phase of the patient’s clinical trial journey generates vast amounts of data. Capturing this data consistently, accurately and efficiently is crucial. According to the National Institutes of Health, an average 12-month trial involving 2,000 patients can generate up to three million data points. When handled manually, a trial of the same size has the potential to produce nearly 10 million opportunities for error.

Yet, many trials still rely on fragmented systems, outdated workflows and manual processes. These inefficiencies hinder progress and amplify the risk of data inaccuracies. To overcome these challenges and reduce the potential for costly errors, clinical trials must implement an integrated data strategy utilising a patient suite.

When thoughtfully designed and implemented correctly, a patient suite acts as the digital foundation of a clinical trial, streamlining efficient and accurate data capture, supporting regulatory compliance and enhancing the overall patient experience. In return, this reduces the potential for costly delays and boosts the chances of trial success.

The patient journey as the blueprint

A patient’s journey through a clinical trial is more than just a series of check-ins and assessments. It is a continuous stream of critical touchpoints, each generating data that impacts the trial outcome. This data must be captured, analysed, contextualised and readily accessible across the trial’s life cycle.