As a practice in the life sciences industry, clinical trials are essential for developing new drugs and treatment methods. Healthcare professionals also rely on effective clinical trials to balance the benefits of prescribed medication against its side effects. Medical researchers are using clinical trials as a tool for improving their domain knowledge and refining the medical solutions they create to deliver better patient care. 

That said, clinical trial management is challenging for life sciences companies even in 2024. Here are some of the latest statistics related to clinical trials:

  • 80% of clinical trials are delayed or terminated mainly due to challenges in recruiting participants.
  • Clinical trials are expensive, accounting for 40% of the allocated budget—approximately $7 billion each year—in U.S.-based pharmaceutical companies.
  • The cost of a delayed clinical trial ranges from $600,000 to $8 million per day in launching a new drug.

Here’s a look at the top 5 challenges in clinical trials management – and how to overcome them:

 

  • Patient recruitment

A Thermo Fisher Scientific survey of drug developers found that patient recruitment for clinical trial purposes is their top challenge—at 55%. The survey respondents observe that clinical studies are becoming larger and more complex, thus increasing the competition for existing study centers and patients.

Without timely recruitment of the right patients, drug development is delayed, thus adding to the costs.

To make clinical trials more equitable, the World Health Organization (WHO) recently presented guidelines to improve the quality of clinical trials. The Thermo Fisher survey recommends that drug developers complement clinical trial data with real-world data. 

Additionally, AI technology can leverage operational data (from previous trials) to predict a drug outcome and the success of a clinical trial.

 

  • Data management

An effective clinical trial is also about collecting and managing high-quality and relevant data. Poor data quality or management can lead to costly errors in product research and development.

With the integration of real-world data in clinical research, life sciences companies can deliver direct evidence of their treatment efficacy. Real-world data includes a host of sources such as:

  • Electronic health records
  • Wearables
  • Patient outcome

70% of clinical trial professionals expect AI technology to substantially impact data management. By deploying AI-powered algorithms, life sciences companies can automatically sift through clinical trial data and identify useful patterns. Further, based on historical data, machine learning tools can accurately predict the patient outcome after a clinical trial.

 

  • Growing complexity

After patient recruitment, 51% of drug development companies are concerned about the rising complexity of clinical trials. Effective clinical trials are complex, time-consuming, and expensive (costing millions of dollars). Often, companies struggle to complete their clinical trials on time and within the assigned budget.

Further, in the aftereffect of the COVID-19 pandemic, new drug testing requires:

  • Involvement of hundreds of clinical trial professionals and volunteers.
  • Adherence to complex protocols and regulations.
  • The selection of multiple clinical trial sites.

As clinical trials grow more complex and diverse, more companies are relying on manual spreadsheets to make their decisions. A clinical trial management system (CTMS) can reduce this complexity by:

  • Providing real-time visibility into relevant data.
  • Track financial metrics and working hours to manage time and costs.
  • Reporting the progress of any clinical trial program.

 

  • Regulatory hurdles

Life sciences and pharmaceuticals are among the most regulated industries across the globe. Regulatory compliance is among the leading challenges in clinical trial management. Due to delays in regulatory approvals, companies are spending the majority of their clinical trial budgets on maintaining compliance.

Apart from compliance, global life sciences companies must navigate region-wise regulatory requirements. Additionally, clinical trial teams must consider ethical issues. For instance, they need to inform clinical trial participants of the potential risks and effects – and acquire individual consent to go ahead with the testing.

Effectively, a CTMS tool can address these challenges by:

  • Storing clinical trial information – like consent forms – at every stage of the entire process.
  • Identifying the roles of clinical trial investigators and support staff at the facility.

 

  • Clinical site management

To improve patient recruitment, life sciences companies have increased the diversity of clinical sites. This includes hospitals, private laboratories, medical centers, and more. However, this diversity also adds to the complexity of clinical trial management.

For instance, each clinical site may use a different system to capture and store clinical data, thus making it challenging for companies to maintain real-time visibility. On average, clinical sites use up to 12 systems to record patient data.

Additionally, with the growing volume of clinical trials and recruitment needs, selecting the right site has become crucial. Poor site selection can cause problems like delays and cost escalation.

AI-powered management tools can improve site selection and performance. Further, personalized AI tools can improve patient engagement and retention for future clinical trials.

 

Conclusion

As the global demand for clinical trials increases, life sciences companies are turning digital to address some of its common challenges like patient recruitment and data management. With the continued data explosion across industries, Trinus’ data management services align business objectives with data-driven insights.

As a technology-based solution provider, Trinus has enabled its customers in the life sciences domain with customized solutions in:

  • Digital health and product development
  • Clinical trial management system
  • Laboratory information management
  • Regulatory compliance
  • Enterprise resource planning (ERP)

Are you looking for specific technology expertise in the life sciences sector?  Contact us now.