Machine Learning in Clinical Trials Operations



The demand for drug and device development is at an all-time high, with over 39,000 new trials launched in 2023, setting a new record. Despite this growth, the industry faces challenges such as rising costs, high staff turnover, and a narrow success window, as many trials fail to reach the market. A deeper look reveals that over 80% of trials are delayed, and 20% of sites fail to recruit even a single patient. Resource managers in clinical trials struggle to reallocate resources effectively from underperforming to high-performing trial sites.

Cost Implications

Monitoring costs, including patient recruitment, onsite and remote monitoring, site management, and project management, account for approximately 90% of clinical trial costs. Many site coordinators, monitors (CRAs), and Resource managers still rely on customized spreadsheets to handle the complexities of global trials, indicating a need for more efficient tools.

Machine Learning in Resource Management

Machine Learning (ML) has revolutionized data collection and analysis of clinical data sets, yet its potential in resource management remains largely untapped. On-Time Trials pioneers this approach with proprietary ML algorithms. These algorithms predict the necessary clinical resources at research sites and Sponsor / CRO organizations at any given time, marking a significant advancement in resource optimization.

On-Time Trials: A SaaS Solution

On-Time Trials, a SaaS platform, integrates advanced machine learning algorithms to forecast patient progression across global sites, enhancing efficiency and accuracy in clinical trials. It empowers research sites to adjust clinical staff according to real-time needs, moving staff from underperforming trials to active recruitment sites. This flexibility applies to both onsite and remote CRAs, enhancing site support and success likelihood at the Sponsor / CRO.

Benefits of On-Time Trials

The key to successful clinical trials lies in efficient patient enrollment and data collection. Many sites and CROs lack dynamic tools for seamless collaboration. On-Time Trials’ advanced ML algorithms ensure that resources are available precisely when needed, akin to how Google Maps or Waze optimizes travel routes. These algorithms allow resource managers to reallocate coordinators and monitors effectively, leading to cost reductions and balanced workloads. As capacity matches demand using our algorithms, sites receive better support, improving both quality and speed of trial.

Data Transparency and Decision Making

On-Time Trials ensures transparency without using Personal Health Information (PHI). It leverages cumulative enrollment data and Case Report Form counts via API, offering clear insights into trial progress against plans. This transparency enables real-time performance sharing with decision-makers at sponsors, CROs, and sites, streamlining decision-making processes. With all trials and sites accessible on a single platform, bottlenecks can be quickly identified, allowing for rapid resource allocation or site disengagement.



Successful Implementation and Impact

On-Time Trials’ ML algorithms have been successfully implemented on a struggling trial, leading to remarkable improvements. With our proprietary algorithms ensuring timely capacity allocation, enrollment increased by 162%. Improved site efficiency in data entry and faster CRA validation further underscored the system’s efficacy.

Conclusion and Summary

In summary, On-Time Trials is transforming clinical trial operations through the integration of Machine Learning algorithms with streamlined principles. This innovative method tackles the significant issues of high costs, delays, and resource mismanagement that are prevalent in the drug and device development industry. By effectively forecasting and optimizing the distribution of resources at trial sites worldwide, On-Time Trials boost efficiency, cut expenses, and enhance trial results. Its capacity to adjust to the ever-changing dynamics of trials, similar to how navigation systems like Google Maps operate, ensures that clinical resources are allocated most effectively. On-Time Trials is establishing a new benchmark for operational excellence in clinical trials. The platform streamlines resource management, promoting improved collaboration and decision-making among sponsors, CROs, and research sites. This leads to an accelerated process of successful drug and device development.

Get Involved with On-Time Trials

Discover how On-Time Trials can revolutionize your clinical trial operations. Don’t miss the opportunity to enhance efficiency, reduce costs, and achieve successful trial outcomes faster. Visit our website to learn more about our groundbreaking platform. Ready to see it in action? Request a demo today and take the first step towards transforming your clinical trial management. Join us in paving the way for a more efficient future in drug and device development. Act now – your next trial success story starts here!