RTI Health Solutions: The CRO for Emerging Pharmaceutical and Biotechnology Companies
Whether you need support for a specific aspect of your study or a complete solution, we can help you with a comprehensive suite of clinical development services.
Within-Subject Clinical Trials
Randomized controlled trials (RCTs) have long been the gold standard for generating the evidence needed for most regulatory approvals. However, the large sample size required, extensive timeframes needed to complete a trial and high associated costs can make it a challenge to get your drug, medical device or diagnostic off the ground.
Our expert researchers have developed novel techniques that can help you save time and money early in your clinical development cycle. Within-subject clinical trials utilize small sample sizes and leverage data collected from an individual multiple times over a short period of time. Innovative methods for rigorous data analysis are then applied, giving you results faster than traditional approaches. This can be ideal for a number of scenarios including:
- Pilot studies for assessing efficacy of new assets
- Efficient and less expensive designs for early go/no-go decisions
- Evaluating treatments for rare diseases
- Drug dosage determination
- Hard-to-reach or small populations
- Emerging illnesses
Closely examining information gathered from a single patient is a long-established practice. Data from these N-of-1 studies—or case studies—has traditionally been used to help inform clinicians’ treatment choices for individual patients. Now, with the addition of rigorous data analysis, the information collected in within-subject clinical trials can provide results that you can use to understand the safety and efficacy of your product in a wider population. These techniques can also be applied to larger sample sizes to improve the generalizability of the results.
Advanced Analytic Techniques
Providing you with insights that you can confidently act upon is our top priority. Our experts employ a number of proven techniques for within-subject clinical trial data analysis to ensure the validity of your results.
- Growth modeling, including latent growth models
- Other analyses for repeated-measures designs