Novel methods and technologies for 21st-century clinical trials: a review

Abstract

Importance: New technologies are rapidly reshaping health care. However, their effect on drug development to date generally has been limited.

Objectives: To evaluate disease modeling and simulation, alternative study design, novel objective measures, virtual research visits, and enhanced participant engagement and to examine their potential effects as methods and tools on clinical trials.

Evidence review: We conducted a systematic search of relevant terms on PubMed (disease modeling and clinical trials; adaptive design, clinical trials, and neurology; Internet, clinical trials, and neurology; and telemedicine, clinical trials, and neurology), references of previous publications, and our files. The search encompassed articles published from January 1, 2000, through November 30, 2014, and produced 7976 articles, of which 22 were determined to be relevant and are included in this review.

Findings: Few of these new methods and technologies have been applied to neurology clinical trials. Clinical outcomes, including cognitive and stroke outcomes, increasingly are captured remotely. Other therapeutic areas have successfully implemented many of these tools and technologies, including web-enabled clinical trials.

Conclusions and relevance: Increased use of new tools and approaches in future clinical trials can enhance the design, improve the assessment, and engage participants in the evaluation of novel therapies for neurologic disorders.

Figure 1. Preclinical and Clinical Drug Development Costs

The total cost of research and development cost (in 2000 US dollars) per approved new drug has increased dramatically during the past 3 decades, with the most notable cost increases occurring in the clinical phases. Data are obtained from DiMasi et al.

Figure 2. Disease-Drug Trial Models

Clinical trial modeling and simulation help to optimize trial designs by investigating assumptions and variability of different factors that affect trial performance. Disease progression models quantify changes in disease status over time, typically in the untreated state. Pharmacokinetic models represent the time course of drug disposition in the body. Pharmacodynamic models characterize the exposure-response relationship of the drug. Together, these models are integrated and applied to simulate different trial scenarios (eg, power calculations, dosing strategies, and trial execution) for predictive purposes. Curves represent interaction between both variables.