Enhancing Clinical Trial Efficiency through Simulation-Guided Study Design: A Path to Faster Drug Development and Regulatory Approval

Enhancing Clinical Trial Efficiency through Simulation-Guided Study Design: A Path to Faster Drug Development and Regulatory Approval

Enhancing Clinical Trial Efficiency through Simulation-Guided Study Design: A Path to Faster Drug Development and Regulatory Approval 558 344 Exploristics

Enhancing Clinical Trial Efficiency through Simulation-Guided Study Design: A Path to Faster Drug Development and Regulatory Approval 

It’s well known that clinical trials require significant investments of resource, time and money, with a low probability of success (POS). In “Estimation of Clinical Trial Success Rates and Related Parameters“,  the authors place the overall probability of a drug successfully moving from Phase I to FDA approval at approximately 13.8% (ranging from a POS low of 3.4% for oncology). 

While some factors affecting clinical trial efficiency are unavoidable, many failures could be prevented with better planning and a deeper understanding of biological and drug development principles. 

Trial design is one such ‘planning’ control point in the probability of success. A well-designed study will clearly define the research question, identify a range of variables including patient population, dose selection, optimal assessment schedules, appropriate endpoints, the data required and its collection methodology. 

Failure in planning to fully capture the real uncertainty of multiple study factors often means failure of the overall development. Yet despite this, approx. only 0.005% of a clinical development’s budget is allocated to the planning and design of clinical trials.  

Better insights, better decisions 

Frequently, biostatisticians have not been involved early enough in the clinical trial design process and by the time they are involved, many critical decisions have been made – such as budget, endpoints, study population and number of study sites. 

But even when involved earlier on, many project teams find it hard to process all the available literature, clinical trial data and real-world-data (RWD) in order to make fully optimised decisions. That’s where biosimulation software comes in. 

Simulation-guided study design, through advanced biosimulation tools, can help bridge the gap between traditional trial design approaches and more targeted evidence-baseddesign to ensure that studies will not fail due to unsuitable design, wasting development time and money while incurring unnecessary patient burden. 

Study simulation empowers decisions based on quantitative data-driven insights, indicating the best design from the outset. This means that the study can deliver meaningful results to inform the next stage of development, paving the way for more successful drug approvals and quicker patient access to new treatments.  

Many tools integrate multiple data sources to build realistic synthetic patient populations, allowing researchers to explore various trial scenarios and their potential outcomes.  

This means it is possible to assess the data insights of thousands of designs in silico in just a few hours and evaluate the impact of design choices on the POS in moments. 

The Role of Simulation in Study Design 

Simulation-guided study design tools like KerusCloud transform clinical trial planning by creating virtual environments where trial strategies can be tested and optimized before actual implementation. This cloud-based tool enables researchers to:  

  • Build: Integrate existing and emerging knowledge and data sources from the literature, clinical trial data, real-world data and expert opinion to build realistic synthetic patient populations.
  • Simulate: Sample these virtual populations to generate highly realistic study simulations in minutes for high numbers of scenarios. 
  • Analyse: Explore multiple fixed and adaptive study designs, analysis and decision-making strategies by applying different statistical analyses and decision criteria. 
  • Optimise: Evaluate the suitability of different trial designs and data analysis methods guided by the quantified POS for each approach. 
  • Visualise: View and share simulated outcomes with Probability of Success values using the interactive heatmap to quickly identify the design and analysis strategy most likely to deliver success.

Benefits of Simulation-Guided Study Design 

Simulation tools are pivotal in modern clinical development, providing numerous benefits: 

  • Optimizing Trial Protocols: Determining the most effective ways to collect critical data. 
  • Enhancing Patient Recruitment: Identifying the right patient groups for the study to ensure robust and relevant results. 
  • Reducing Trial Timelines and Costs: Minimizing unnecessary phases and patient numbers through precise planning.
  • Enhancing Regulatory Strategy: Helping design trials that meet regulatory standards for efficacy and safety with minimized risk. 
  • Data-Driven Decisions: Enabling data-backed decisions that enhance the quality and accuracy of trial results. 
  • Stakeholder Confidence: Increasing confidence among stakeholders, including investors and regulatory bodies, by demonstrating thorough, evidence-based trial planning. 

KerusCloud Case Study: Revolutionizing Antibacterial Treatment Development with KerusCloud

The Challenge: A small biotech company was developing a new treatment for C. difficile, a significant cause of infections in healthcare settings, particularly harmful to vulnerable patients. An initial plan required about 1,000 patients, which was unfeasible for the company due to resource limitations.

The Approach: The company utilized KerusCloud to re-evaluate their development strategy. By analyzing data from various sources and creating virtual patient populations, KerusCloud enabled the simulation of multiple study designs.

The Results: The simulations helped the project team identify an optimal study design using only 180 patients instead of 1,000. This new plan was robust enough to support an application for rapid marketing authorization.

The Impact: By adopting KerusCloud’s recommendations, the company reduced its potential time to market by 3-5 years and saved approximately £18M in development costs. Their revised plan was well-received by regulators like the FDA and EMA, substantially accelerating the approval process.

Challenges and Considerations

Despite the clear advantages, integrating simulation-guided study design into standard practices presents challenges:

  • Data Quality and Complexity: Realistic simulations depend on the quality and depth of data used to create virtual models.
  • Expertise Requirements: Effective use of simulation tools requires specialized skills in biostatistics and clinical trial design which not all project teams have in-house.
  • Adoption Barriers: There may be resistance to adopting new technologies, especially from stakeholders accustomed to traditional trial methods.

Researchers and investors can no longer afford to overlook the importance of simulation-guided design tools in enhancing clinical trial efficiency. Simulation software not only helps improve chances of success but can help in quantifying the POS to attract investment, aide resource allocation, risk management, and strategic planning.

The integration of simulation-guided tools like KerusCloud into clinical trial design is transforming the landscape of drug development. By allowing for the virtual testing of trial strategies, these tools not only streamline the development process but also enhance the efficacy of clinical trials, leading to faster regulatory approvals and reduced costs.

Partner with Exploristics’ to transform your trial development through our industry-leading clinical study design platform, KerusCloud, and our team of seasoned biostatistics experts.

Book a Meeting with our expert team to find out how Exploristics can reduce the duration and cost of your clinical trial, increasing your Probability of Success.