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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
JAMA Neurol. Author manuscript; available in PMC 2016 January 11.
Published in final edited form as:
PMCID: PMC4708881

Novel Methods and Technologies for 21st-Century Clinical Trials

A Review
E. Ray Dorsey, MD, MBA
E. Ray Dorsey, Department of Neurology, University of Rochester Medical Center, Rochester, New York; Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, New York;
Charles Venuto, PharmD
Charles Venuto, Department of Neurology, University of Rochester Medical Center, Rochester, New York; Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, New York;
Vinayak Venkataraman, BSE, medical student
Vinayak Venkataraman, Duke University School of Medicine, Durham, North Carolina;
Denzil A. Harris, BA
Denzil A. Harris, Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, New York;
Karl Kieburtz, MD, MPH



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


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.


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.


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.


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.

The cost of successful development of a new compound is rising, with recent estimates exceeding $1 billion.1,2 The primary driver of the rising costs is clinical costs, especially clinical trials, which increased 10-fold from 1991 through 2003 (Figure 1).3 Cash outlays are important, but the primary driver for the rising economic costs of drug development is time.3

Figure 1
Preclinical and Clinical Drug Development Costs

The rising costs have not led to the availability of more drugs.4 The resulting decline in productivity in drug development began in the 1950s and continues.5 Although much of the world follows the Moore law on the doubling of output (eg, computing power) per unit cost every 2 years,6 drug development and clinical trials are moving in the opposite direction. While the productivity of drug development is decreasing, the understanding of the etiopathogenesis of disease and the number of therapeutic targets is rapidly increasing. To capitalize on these opportunities, clinical trials must change.

Fortunately, new methods, tools, and approaches—often enabled by technological advances—are increasingly available to bring clinical trials into the 21st century (Table 1). This review focuses on the following 5 such advances: disease modeling and simulation, alternative trial designs, novel objective outcome measures, virtual research visits, and engagement of research participants. Although not exhaustive, these 5 advances have the potential to decrease the cost and time required to determine whether novel interventions are safe and efficacious.

Table 1
Characteristics of 20th- vs 21st-Century Clinical Trials

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.

Disease Modeling and Simulation to Facilitate Design of Clinical Trials

Clinical trials are complex and dynamic systems that depend on biological, pharmacologic, and trial-related components. Unlike other industries (eg, aerospace) that have costly and rigorous manufacturing practices, clinical trials historically have not used analytic model-based approaches. However, modeling and simulation have increased in the past several years as a means to increase the efficiency of drug development.7,8

Clinical trial simulations test various clinical trial scenarios before commencing a trial and calculate the probability of a specific outcome. These simulations are based on models of disease and drug trials. Disease progression models quantify the natural history of disease (Figure 2). Pharmacokinetic and pharmacodynamic models describe the temporal relationship between dose concentration and effect. Trial design models include specific study design features (eg, entry criteria) and assumptions (eg, adherence to a drug regimen).

Figure 2
Disease-Drug Trial Models

By evaluating the shape and variance of disease progression, models can better estimate the trajectory of disease and identify factors that contribute to variance.9 For example, a nonlinear model describing the progression of amyotrophic lateral sclerosis predicted individuals as having slow or rapid progression based on 4 weeks of initial evaluation. These estimated trajectories can then be used for stratification and enrichment strategies based on progression rate status (ie, fast vs slow) in future trials.10 Quantitative models for Alzheimer disease, bipolar disorder, and Parkinson disease are now available for clinical trial planning purposes from the US Food and Drug Administration (FDA).11

Regulators and industry are now embracing modeling and simulation. For the first time, the FDA has deemed a clinical trial simulation model for Alzheimer disease “fit for purpose” as a quantitative tool for planning future clinical trials related to study design selection and inclusion criteria.11 For example, a disease model describing longitudinal changes in the Cognitive subscale of the Alzheimer Disease Assessment Scale (ADAS-cog) is available to simulate the natural progression of disease as well as progression of the placebo and active treatment arms. This information can be used in simulations to test variables of the study design, such as sample size estimations, power, and bias between competing study designs (eg, crossover vs parallel studies) based on assumptions of a drug having symptomatic or disease-modifying effects.11 Future models are likely to build on and refine the models for Alzheimer disease, Parkinson disease, and other disorders.

Alternative Designs to Speed the Development of Drugs and to Lower Costs

Traditional clinical drug development progresses from “learning” to “confirming”12(p275) and is reflected in successive phases 1, 2, and 3 trials. Although this generalization is overly simplistic, the process highlights some problems. By performing initial safety and pharmacokinetic (phase 1) testing in healthy populations vs those with the disease, investigators may miss important interactions until phase 2. Next, the effort to identify and recruit research participants for phase 2 studies is often duplicated in phase 3. Finally, phase 3 confirmatory trials are often launched without an adequate understanding of responsive subpopulations because phase 2 studies are generally underpowered to identify treatment-response interactions.

More contemporary trial methods exist to address these issues and have been evaluated13 and implemented14 in neurologic conditions. Phase 1 testing, for example, to identify the maximal tolerated dosage, can be performed in individuals with the disease. Specific trial methods, such as the continual reassessment method,15 can include features to control risk, to identify the maximal tolerated dosage more efficiently, and to study dosages closer to that dosage than typical algorithmic 3 + 3 designs.16

Phase 2 studies have also seen the rise of novel trial methods, including nonsuperiority designs, adaptive randomization designs, and integrated phases 2 and 3 studies. An example of a responsive-adaptive trial design is the Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis (I-SPY 2) trial in breast cancer.17 Efficiencies are obtained from simultaneous assessment of multiple neoadjuvant therapies and identification of responsive subpopulations based on clinical, biomarker, or genetic characteristics. As the trial progresses, positive responses are identified, the randomization process directs individuals toward potentially effective therapies, and noneffective therapies are stopped.

Nonsuperiority designs are another approach to eliminating ineffective therapies efficiently. In nonsuperiority studies, the natural history of the disease is known, and interventions that cannot improve on that expectation by a fixed amount (eg, 20%) are considered not worthy of future investigation (ie, nonsuperior).14 Failure to find nonsuperiority does not guarantee future success, but nonsuperiority provides a strong signal to abandon development.

Recruitment is a great time burden and is often duplicated in separate phases 2 and 3 trials. Novel ways to include participants already enrolled in a single trial for phases 2 and 3 purposes would be efficient. Embedding a series of phase 2–like analyses in a large phase 3 confirmatory trial is an example. Assessment of safety could occur after relatively few participants are recruited, and an analysis for nonsuperiority could be conducted later. Both analyses could stop a trial that is unsafe or likely to fail. Neither analysis would be used to stop the trial for efficacy, so the penalty to preserve statistical power is minor.

Novel Objective and Sensitive Clinical Measures to Detect Efficacy Signals More Rapidly

Many measures in neurology clinical trials have significant limitations (Table 1). Consequently, trials, especially for neurodegenerative conditions, require large sample sizes and long durations that have a high risk for failure of efficacy.18 For example, two of the largest clinical trials ever in Huntington disease19,20 and the largest trial in Parkinson disease21 were all recently stopped early for futility.

Although biomarkers, especially imaging, have made considerable progress in the evaluation of outcomes (eg, for multiple sclerosis), they are also critical for confirming engagement of the relevant biological target in phase 2 studies. When applied in phase 2 studies, such measures can determine whether the short-term effects of target engagement reflect predictions from preclinical studies. Absent such assessments, an interventional drug may fail in phase 3 owing to lack of efficacy simply because the target is not engaged as expected.

In addition to assessing biological activity, objective and sensitive outcome measures can augment currently used measures to determine whether an intervention is efficacious.22 Although rating scales (eg, the Unified Parkinson’s Disease Rating Scale23) have been used to gain FDA approval of many drugs, their results are observer dependent and thus subjective.24 Objective measures are in various stages of development to address these shortcomings.25,26 Cross-sectional27 and longitudinal analyses28 of such assessments have demonstrated their ability to objectively quantify functional decline. For example, in Parkinson disease, sophisticated mathematical analysis of voice recordings can track disease progression.29

In addition to their subjectivity, many current outcome measures for amyotrophic lateral sclerosis,26 epilepsy,30 multiple sclerosis, and prodromal periods of disease (eg, Alzheimer disease) are insensitive. For example, approximately 50% of seizures recorded during video electroencephalographic monitoring are unknown to patients and thus cannot be documented in seizure diaries.30 More recent studies have shown that the seizures reported by patients and those that are detected by implantable devices do not match.31,32 Use of sensors, including accelerometers to assess seizures in epilepsy30 and gait in multiple sclerosis,33 is increasing; these sensors may be more sensitive to change than conventional clinical ratings.25

These measures have the additional benefit that they can be assessed frequently and outside the clinic. At present, most clinical trial assessments are performed in the clinic under artificial (although often standardized) conditions at certain study intervals. Such episodic assessments are commonly used even when fluctuations (eg, in Parkinson disease) are key disease features.

Passive remote monitoring will allow increasing detection of events that are currently undetectable. Wearable sensors can now monitor tremor for as long as 10 hours daily.34 Remote measurement of daily computer use can detect mild cognitive impairment,35 and smartphones can map out the geographic area where individuals with Parkinson disease live.36 Potentially more powerful applications are on the horizon.37 For example, implantable devices in individuals with drug-resistant epilepsy increasingly can predict seizures and alert patients.31

Beyond neurology, passive continuous monitoring has progressed to routine use in trials and care in cardiology. Remote monitoring of implantable cardiac devices, such as defibrillators and pacemakers, has led to more rapid detection of potential adverse events,38 greater retention of patients,39 and improved care.40 A new cardiology study41 will use an inserted cardiac monitor to detect potentially occult atrial fibrillation, and the primary outcome measure in an antiarrhythmic trial is the frequency of atrial fibrillation as detected by pacemakers.42 Evaluating new objective measures in neurology alongside traditional clinical measures in observational studies, and, importantly, in early-state clinical (eg, phase 2) trials will be critical to determining their sensitivity and value.

Virtual Research Visits to Increase Reach and to Lower Cost

Owing to increasingly ubiquitous and inexpensive telecommunications technology, telemedicine allows patients to connect to physicians almost anywhere. In research, virtual visits, which can occur by telephone, video, or asynchronous communication platforms, such as texting, can facilitate greater participation, decrease burden on the participants, and reduce variability in assessments. More generally, assessments of clinical outcomes, including for stroke, are increasingly captured by remote means.43 In addition, for research purposes, virtual research visits (eg, web-based surveys, telephone calls, and field research) that do not provide health care are generally not subject to state medical licensing laws that typically define telemedicine as the “delivery of clinical health care services.”44

One major reason for the low rate of participation in clinical trials is the need for frequent in-person visits and the resulting time and travel costs,45 which can be reduced with virtual visits. In a study of Parkinson disease, a single site conducted clinical assessments of 50 individuals in 23 states remotely through web-based video conferencing to verify self-reported diagnoses and conduct standardized assessments of cognition and motor function. Such a study would typically require multiple sites, institutional review board approval, contracts, and considerable time. Instead, this single-site study completed the assessments in less than 3 months. In stroke, where telemedicine has dramatically changed care, similar technology is being used to enroll research participants in stroke trials.46,47

These approaches could be especially powerful for rare conditions for which typical studies involve air travel to research centers. In addition, virtual visits could facilitate participation in clinical trials for populations who, because of disability, cannot participate otherwise. A study of Alzheimer disease found that home visits were the factor most likely to enable greater participation in clinical trials.48 Although virtual visits are unlikely to supplant in-person visits altogether, they could assess the natural history of rare conditions and carriers of specific genetic mutations. Video visits could also augment existing audio calls as interim safety assessments or decrease the number of in-person interim assessments in clinical trials. An upcoming clinical trial of lisinopril in multiple sclerosis will have 10 visits, of which only 2 will be in person (John Holland, BA, AMC Health and Transparency Life Sciences, written communication, August 19, 2014). Virtual visits can also be applied to extend the observation of individuals who have completed a clinical trial, and such an approach has already been applied using the telephone.49

Finally, virtual visits can enable centralized rating of disease states and reduce variability. The feasibility and reliability of remote video assessments has been demonstrated for a wide range of conditions, including stroke, Parkinson disease,50 and Batten disease.51 Centralized rating for many psychiatric assessments can reduce measurement error in clinical trials.52

Greater Participant Engagement to Generate Multiple Secondary Benefits

Perhaps the greatest change in the conduct of future clinical trials will be the role of the research participant. Traditionally, research participants have been viewed and treated as passive subjects on whom procedures were conducted and from whom data were obtained. As such, participants had no role in a study’s design or conduct, and, despite exposing themselves to health risks, they were not informed of study results, including those outcomes with adverse health consequences.53-55 The passive role of study participants is changing to an increasingly active one that includes expanded roles as participant, designer, sponsor, organizer, and investigator.

Clinical trials increasingly are including participant-reported outcomes in addition to those rated by investigators. The National Institutes of Health funded the development and validation of the Patient Reported Outcome Measurement Information System (PROMIS) for general use,56 and the National Institute of Neurological and Communicative Diseases and Stroke funded a neurologic quality-of-life measure (Neuro-QOL), a neurology-specific off-shoot of PROMIS.57 These patient-reported outcomes are increasingly desired by the FDA,58 and their development often reflects considerable input from patients.59

While the role of participants is expanding within trials, greater changes are occurring outside trials. Individuals or families affected by the disease increasingly take roles traditionally left to government, foundations, industry, and researchers. Unwilling to be neglected and frustrated by the slow pace of innovation, patients and their communities are funding, organizing, and even conducting their own clinical trials.60,61 Parents of children with Duchenne muscular dystrophy recently drafted an FDA guidance on clinical trials for children with the disorder.62 Even publicly funded research organizations are providing patients with an unprecedented voice in research. The newly created Patient-Centered Outcomes Research Institute63 explicitly requires that all studies engage participants in the study’s design and conduct. In some cases, the lead investigator is not a traditional researcher but a patient. Such models of citizen-researchers are proliferating globally.64

The expanded role and engagement of research participants is not a threat but an opportunity. Some of medicine’s greatest advances in the 20th century, including a vaccine for poliovirus and effective treatments for human immunodeficiency virus infection, have arisen from the demands and engagement of the public (eg, March of Dimes65) and patients (eg, activists for AIDS66). Greater access to knowledge and people (from investigators to similar patients) is fueling this change. Although unrealistic expectations and lack of familiarity with the research process are potential challenges, the public overwhelmingly supports clinical research67 and is the ultimate beneficiary of its advances. Research participants are a powerful force for change; while these expanded roles are increasing in rare disorders, they have the opportunity to expand to more common disorders (eg, autism) in which patient communities are exceptionally well organized.

Glimpses of the Future

A few innovative studies have implemented virtual clinical trials that encompass several of the methods and technologies described herein (Table 2).68-72 More than a decade ago, the BMJ published the results of a feasibility study of an online randomized clinical trial of glucosamine.73 The investigators conducted a 14-week, Internet-based, placebo-controlled study in 205 individuals with osteoarthritis of the knee. Individuals were recruited online and received a mailed copy of a consent form and medical records release to confirm the diagnosis. Participants also completed online pain assessments and received the study drug by mail. No difference was found between patients in the online study and those in previous investigations.73 The estimated cost of this pioneering study was half that of a traditional study owing to savings of space, labor, and travel. The study limitations included the time required to obtain consent and medical records, the components of the study that were not Internet based.

Table 2
Characteristics of Select Web-Based Clinical Trials

Another more recent 21st-century clinical trial was conducted by members of an online patient community called PatientsLikeMe ( PatientsLikeMe provides a forum for individuals, predominantly those with chronic disorders, to discuss their conditions, report on their treatments, and measure their own symptoms. The community of individuals with amyotrophic lateral sclerosis recently organized itself to conduct a controlled study of lithium.71 The self-reported data on the ALS Functional Rating Scale ( of 149 participants who took lithium for 12 months were compared with data from a matched control population of 447 individuals. After 12 months of treatment, no effect of lithium on disease progression was observed.71 The study design, while clearly limited, offered the advantage of speed (the time from initiation of the study to preliminary results was 9 months), access to widely dispersed patients, and a large pool of control participants. Its limitations, including missing data, losses to inadequate follow-up, and lack of an independent rater, highlight the substantial work that remains.71 Moreover, the value of such approaches should be assessed in interventions that are known to be beneficial.

A third proof-of-concept study was a postmarketing trial. Pfizer Inc sought to evaluate whether it could replicate findings on the efficacy of the extended-release formulation of tolterodine tartrate for the treatment of overactive bladder in an entirely web-based approach to a randomized clinical trial.72 The investigators found that most elements of the virtual study (eTable in the Supplement), including online consent, online identity verification, dispensing of study medication, remote collection of specimens, reporting of efficacy assessments via mobile phones, and offering participants access to their electronic clinical data, worked well. However, the study was concluded prematurely because of low participant enrollment,72 which may have been driven by the absence of trusted clinicians or investigators involved in the recruitment process. Although most of these trials are outside the field of neurology, they provide a guide as to what is possible and what is likely to come.

Future Directions

The methods, tools, and approaches to 21st-century clinical trials are largely disruptive. In The Innovator’s Dilemma, Christensen74 points out that disruptive technologies are generally viewed as inferior and cheap and are treated with skepticism by the establishment. Similarly, these novel approaches to clinical trials will be met with skepticism and will not readily integrate into the currently established processes and values of drug development.74 Many of these approaches (eg, virtual visits) will be perceived as inferior to current criterion standards. Indeed, disruptive approaches and technologies (eg, digital cameras) initially enter the lower end of the market.74 In clinical trials, disease modeling, alternative trial designs, remote assessments, and web-based clinical trials generally have evaluated safe interventions (eg, glucosamine). In addition, like many disruptive approaches, these trials have generated their results at much lower costs than those of conventional trials.70,71,73 Finally, many new entrants, such as PatientsLikeMe and Transparency Life Sciences, a drug development company based on open innovation that uses crowdsourcing and mobile health technology, are leading this disruption.

However, interest in disrupting the current model is not limited to new entrants. Large pharmaceutical firms, notably Eli Lilly and Company69 and Pfizer Inc,72 have invested in developing web-based approaches that include greater participant engagement and remote assessments. The FDA is also willing to support such novel approaches.72 In the end, the status quo of declining productivity of drug development is in no one’s interest. New approaches to drug development and clinical trials are needed. The approaches described herein can enhance the design, improve the assessment, and engage the participants in the development of novel therapies at a time when the potential for therapeutic advances is greater than ever.

Supplementary Material



Funding/Support: This study was supported by the University of Rochester Clinical and Translational Sciences award UL1TR000042 from the National Center for Advancing Translational Sciences of the NIH.

Role of the Funder/Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Dr Dorsey is an advisor to and has stock options in Grand Rounds; is a compensated consultant to Clintrex, Lundbeck, mc10, MedAvante, the National Institute of Neurological Disorders and Stroke (NINDS) of the National Institutes of Health (NIH), and Roche; is an unpaid advisor to SBR Health and Vidyo; receives research support from Auspex Pharmaceuticals, Davis Phinney Foundation, Great Lakes Neurotechnologies, Huntington Study Group, the Michael J. Fox Foundation, the Patient-Centered Outcomes Research Institute, Prana Biotechnology, and Sage Bionetworks; and has filed a patent application related to neurology and telemedicine. Dr Venuto received research grant support from the Michael J. Fox Foundation. Dr Kieburtz is a consultant for Abbott, Acorda, Biogen Idec, Biotie, Biovail, Boehringer Ingelheim, Ceregene, Civitas, Clintrex, Cynapsus, the Department of Veterans Affairs, Eli Lilly and Company, EMD Merck Serono, the FDA, Genzyme, Impax, Intec, Ipsen, Isis, Knopp, Link Medicine, Lundbeck, LZ Therapeutics, Merz, the NINDS, Novartis, Orion, Otsuka, Pharm2B, Phytopharm, Schering-Plough, Siena Biotech, Solvay, Synosia, Synagile, Teva, UCB Pharma, Vaccinex, and Xenoport; received grants or research support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, Neurosearch, Medivation, the Michael J. Fox Foundation, the National Eye Institute, the National Institute on Aging, the NINDS, and Pfizer Inc; and received other support (legal consulting) from Pfizer Inc and Welding Rod Litigation Defendants.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.


Supplemental content at

Author Contributions: Dr Dorsey had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Dorsey, Kieburtz. Acquisition, analysis, or interpretation of data: Dorsey, Venuto, Venkataraman, Harris. Drafting of the manuscript: Dorsey, Venuto, Venkataraman, Kieburtz.

Critical revision of the manuscript for important intellectual content: All authors. Administrative, technical, or material support: Dorsey, Harris, Kieburtz.

Study supervision: Dorsey.

Conflict of Interest Disclosures: No other disclosures were reported.

Additional Contributions: Walter Koroshetz, MD, of the NINDS, provided thoughtful critique and suggestions throughout the process of preparing this manuscript. No compensation was received for this contribution.

Contributor Information

E. Ray Dorsey, Department of Neurology, University of Rochester Medical Center, Rochester, New York. Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, New York.

Charles Venuto, Department of Neurology, University of Rochester Medical Center, Rochester, New York. Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, New York.

Karl Kieburtz, Department of Neurology, University of Rochester Medical Center, Rochester, New York. Center for Human Experimental Therapeutics, University of Rochester Medical Center, Rochester, New York. Clinical and Translational Sciences Institute, University of Rochester Medical Center, Rochester, New York.


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