RBQM Survey Summary Report

ACRO’s 7-year landscape survey examines trends in risk-based approaches in clinical trials

Overview New Studies Adoption What’s Next View the 2024 Report

Overview

Earlier this year, ACRO conducted its seventh consecutive landscape survey of member company CROs. The following report highlights ACRO’s key findings as observed from data reported for 2025. The purpose of the annual survey is to evaluate adoption levels among ACRO member companies in order to improve our understanding of how risk-based quality management is being adopted across the clinical trial industry.

Clinical Research Organizations continue to grow their use of risk-based technologies in clinical trials. In 2019, nearly half of companies were still relying on traditional methods. Now, that figure is down to 10%.

In 2025, nearly all clinical trials (90%) included at least one RBM or RBQM component. This is a significant increase from 2019, when 53% of CROs reported using risk-based approaches.

As clinical trials running in traditional operating models reach their planned completion, the data shows that for new trials CROs are increasingly adopting more efficient risk-based monitoring operating models. Usage of traditional methods was sliced in half between 2019 and 2020, and again from 2020 to 2021.

A Closer Look at the Studies in Our Dataset

The 2025 RBQM landscape survey includes 4,296 outsourced studies from 8 CRO member companies. The organizations involved represent a broad range of biopharmaceutical companies of all sizes; however, half of the studies reported in the group are considered small (defined as <100 participants).

ACRO has witnessed a decline in the number of ongoing studies since beginning this survey in 2019. Several factors could be contributing to this decline.

It may reflect broader geopolitical and economic shifts or changes in how organizations approach outsourcing. Some companies may be bringing work back in-house, while others increasingly adopt the Functional Service Provision (FSP) model or engage with specialty CROs. Notably, neither FSP providers nor specialty CROs are included in this survey.

The following charts are representative of the activities across the clinical trial industry, including the sponsors’ overall adoption of RBQM.

Customer size is defined as: Small = < $1 Billion annual revenue; Mid-size = $1B – $10B; Large = > $10 Billion

RBQM Components in New Studies

ACRO Survey Focuses on New Study Starts in 2025

The surveys held between 2019 and 2024 included ongoing studies to provide a steady baseline of industry uptake of RBQM. Moving forward, ACRO will focus solely on new study starts in its RBQM landscape survey, as this data offers clear insights into how the industry continues to shift its thinking. With the introduction of ICH E6 (R3), exploration of the real-time clinical trial initiative (RTCT), and ever-expanding applications of AI and new technologies, it is important to look at how to move the industry forward.

The following graphs show how RBQM components have been adopted in new study starts each year between 2019 and 2025. The data was collected from ACRO Member CROs as part of the organization’s annual RBQM landscape survey.

Highlights

Roughly half of new studies outsourced to CROs utilize risk assessments, KRIs, centralized monitoring, and remote monitoring.
ACRO’s dataset shows that industry adoption of RBQM components has steadily grown from 2019 to 2025, and we’re still seeing 100% SDR/SDV on most studies.^*
In 2024, there was a small decrease in the use of KRIs and remote monitoring (possibly due to refinement of centralized monitoring strategies), including study specific analyses and more efficient recognition of problems internally. In 2025, KRIs and centralized monitoring bounced back in the other direction. Use of KRIs increased by 7% and use of centralized monitoring increased by 11%.

The 2025 RBQM landscape survey represents 4,296 outsourced studies from 8 CRO member companies. The majority of these studies are considered small, including fewer than 100 participants. Since 2019, ACRO has also seen a downward trend in the number of ongoing studies.

* Differing functional service provider (FSP) models are commonly used by sponsors, and this may be contributing to the high levels of 100% SDR/SDV that we are seeing in our dataset. If a sponsor deploys a FSP strategy and contracts with multiple vendors or CROs on a given study, this may introduce an additional level of risk due to the need for the different vendors to closely coordinate their activities in deployment of a successful RBQM strategy. To mitigate this risk, sponsors may be more inclined to include 100% SDR/SDV as a back-up when outsourcing in this model. ACRO believes that RBQM should be implemented in a holistic end-to-end manner in all outsourcing models, improving monitoring of a trial and data quality.Do we want any descriptive text here?

Adoption Across Sponsor Size, Study Size, and Phase

RBQM Trends According to Sponsor Size

When looking at new study starts, mid-size sponsors had higher adoption rates across the board compared to large or small sponsors. ACRO’s data shows that large sponsors were more likely to conduct their own risk assessments in-house than small or mid-size sponsors, who were more likely to outsource risk assessments to CRO partners. Mid-size sponsors were also more likely to reduce SDR/SDV as compared to small and large sponsors.

In our experience, smaller sponsors are generally more reluctant to invest in centralized monitoring when designing a study, but we believe by doing so, the cost of monitoring could be reduced through reductions in SDR/SDV and on-site monitoring.

How Study Size and Phase Impact Risk-Based Approaches

ACRO’s data shows that small and mid-size studies (defined as 100-999 participants) were less likely to outsource risk assessments. Mid-size and large/mega studies were more likely to implement QTLs, KRIs, centralized monitoring and reduction of SDV as compared to small studies. Mid-size studies were more likely to utilize QTLS and reduction of SDR as compared to small and large/mega studies.

For new study starts, ACRO’s data shows that except for initial and ongoing risk assessments, Phase II and Phase III studies were more likely to include RBQM components as compared to Phase I and IV studies. Phase III studies were more likely to utilize QTLs, KRIs, and centralized monitoring. Phase IV studies were more likely to reduce SDR/SDV.

Given the wide variation in adoption across study size and phase, it is worth considering that certain RBQM components are applied on a fit-for-purpose basis. This would account for the variation we see.

Customer size is defined as: Small = < $1 Billion annual revenue; Mid-size = $1B – $10B; Large = > $10 Billion

What’s at Stake for RBQM?

Clinical trials are high-stakes, making it essential for organizations overseeing and conducting these studies to promptly identify safety signals, data quality deficiencies, and other issues that could compromise patient safety or trial integrity.

The FDA has maintained the importance of risk proportionality, which focuses resources on high-risk areas while avoiding unnecessary efforts in low-risk areas. Centralized monitoring does just that. The use of centralized monitoring enables early detection of issues, improves data quality, increases patient safety, and reduces expending unnecessary resources. Despite this, there is an apparent hesitancy, stemming from risk aversion, lack of trust, and fear of missing events, to move away from traditional trial elements like SDR and SDV.

However, these traditional trial elements, in many cases, pose a greater risk to patient safety and data integrity. Experience suggests that traditional trial elements like 100% SDR/SDV actually leave more room for errors and additional opportunities for mistakes.¹ Failure to focus on critical data and process can cost CROs and sponsors valuable time and money.

Utilizing risk-based strategies not only identifies errors much faster and more consistently than traditional clinical trials, but it also adheres to the concept of risk proportionality promoted by the FDA, allowing data experts to focus their attention and effort on the critical data.

The number of data sources² in clinical studies is ever-expanding due to increased utilization of electronic patient-reported outcomes (ePRO), electronic clinical outcome assessments, (eCOA), wearable devices, etc. According to a 2022 study led by Tufts CSDD in collaboration with a working group of pharmaceutical companies and CROs, there were more than 5.96 million data points in Phase III protocols alone.³ The onsite, manual monitoring methods associated with traditional monitoring are limited in scope and will not be able to keep pace with the number of data sources, data volume and complexity. Advancements in artificial intelligence (AI) are opening new opportunities to maximize accuracy and efficiency in clinical data review. As organizations continue to implement and expand their RBQM approaches, they should take into consideration how AI and Machine Learning (ML) can be leveraged to identify noncritical issues while experts focus on the data that matters.

Through the combined use of AI-supported RBQM strategies, the industry can advance and innovate in a way that will help patients by bringing medicines to market much faster and more cost effectively.

¹ Barnes B, Stansbury N, Brown D, Garson L, Gerard G, Piccoli N, Jendrasek D, May N, Castillo V, Adelfio A, Ramirez N, McSweeney A, Berlien R, Butler PJ. Risk-Based Monitoring in Clinical Trials: Past, Present, and Future. Ther Innov Regul Sci. 2021 Jul;55(4):899-906. doi: 10.1007/s43441-021-00295-8. Epub 2021 Apr 29. PMID: 33914298; PMCID: PMC8082746.

² Society for Clinical Data Management, 2019, The Evolution of Clinical Data Management into Clinical Data Science: A Reflection Paper on the Impact of the Clinical Research Industry Trends on Clinical Data Management , https://scdm.org/wp-content/uploads/2024/03/2019_Evolution-of-CDM-to-CDS-Part-1-Drivers.pdf. Accessed 12 June 2025.

³ Kenneth Getz, Emily Botto, Ana Calduch Arques et al. Insights informing strategies for optimizing the collection of clinical trial data, 14 September 2025, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-7527216/v1]

View and compare the results from our prior RBQM surveys: 2024, 2023.