Company insight
Changing clinical trial feasibility
SGS studies the pitfalls associated with current methodologies of clinical trial feasibility. Olawale Salami, Arash Ghalamkarpour, Elke De Rijck and Barbara Buls highlight how SGS Health Science’s clinical trial feasibility approach supports many sponsors in optimising trial planning.
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n recent years, there has been an upsurge in the number of (bio) pharmaceutical products under development globally, reaching an estimated 7,471 products in 2021, which represents a 2.3-fold increase compared with 2017. This unprecedented expansion in the pipeline of innovative therapeutics and vaccines across a broad spectrum of diseases has in turn increased the number of clinical trials. During the same period, the number of industry-sponsored studies increased by 56%, from 6,307 to 9,870 clinical trials. The number of trial participants has also increased, with over four million healthy subjects and patients in Covid-19 and non-Covid-19 studies in 2020 due to the impact of the pandemic.
For example, approximately 40% of clinical trials in oncology are terminated prematurely. Other authors have estimated that up to 23% of trials cannot follow their patient recruitment as initially planned and fail the study timeline, and about 13% of clinical trial sites do not enrol a single patient in the study. Recruitment failure can seriously impact the product innovation lifecycle, with significant implications in terms of research costs, corporate revenues and delays in access to life-saving innovations. To assess the contribution of recruitment failure to the global toll of clinical trial termination, SGS analysed global trends over five years, from 1 January 2017 to 1 January 1 2022, by evaluating all
“There is increasing recognition of the central role of data-driven feasibility in (bio)pharmaceutical product development.”
A fundamental factor that underpins the successful execution of clinical trials is site quality, and delays in or failure of, trial participant enrolment representing significant risks in product development. Therefore, a critical success criterion of clinical trials is the selection of sites with the requisite capabilities: access to a well- characterised population of potential trial participants, experienced and well- motivated investigators and study staff, and adequate site facilities – all located within countries with a favourable regulatory environment.
Recruitment failure
Premature termination is a common phenomenon in the clinical trial landscape.
Clinical Trials Insight /
www.worldpharmaceuticals.net
terminated interventional Phase 1, 2, and 3 and industry-sponsored studies posted on
ClinicalTrials.gov. A total of 1,156 studies were included. The results show that a majority (42%) of clinical trials over the past five years were terminated due to business or strategic decisions. Furthermore, recruitment delays accounted for 22% of trial terminations globally over the previous five years. Other causes of trial termination were lack of efficacy of the intervention (10%), safety (8%), failure to meet the primary endpoint (8%), futility (3%), Covid-19 related reasons (2%) or FDA request (2%). Less common reasons for early trial termination include Data Safety Monitoring Board (DSMB) and Independent
Data Monitoring Committee (IDMC) recommendations, investigational medicinal product (IMP) issues, poor pharmacokinetic (PK) data, principal investigator (PI) exit, or no reason was specified.
A data-driven approach The integration of data-driven analytics and decision-making into the clinical trial feasibility planning process can help maximise the enrolment potential of clinical trials and mitigate the risks of premature termination. Furthermore, the operational efficiencies gained by optimising the feasibility planning process at the trial or portfolio level may potentially reduce drug development costs.
In recent years, attention has focused on a deeper understanding of the data sources that are critical to increasing the accuracy of trial enrolment planning and risk management. The increasing availability and use of digital real-world data (RWD), including electronic health records (EHRs) and insurance claims, has facilitated the application of advanced analytical tools to identify eligible populations and subpopulations of patients with clinical indications of interest. Newer statistical and machine learning algorithms are being deployed to derive even greater insights from existing data. Furthermore, incorporating data from clinical trial registries like
ClinicalTrials.gov, the EU Clinical Trials Register and Japan UMIN- CTR into feasibility planning, combined with well-curated epidemiology and market size information, supports holistic strategic and business decision-making.
Data-driven trial feasibility Many trials sponsors in the (bio) pharmaceutical industry experience delays
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