The n-of-1 clinical trial: the ultimate strategy for individualizing medicine?
Open accessAbstract
N-of-1 or single subject clinical trials consider an individual patient as the sole unit of observation in a study investigating the efficacy or side-effect profiles of different interventions. The ultimate goal of an n-of-1 trial is to determine the optimal or best intervention for an individual patient using objective data-driven criteria. Such trials can leverage study design and statistical techniques associated with standard population-based clinical trials, including randomization, washout and crossover periods, as well as placebo controls. Despite their obvious appeal and wide use in educational settings, n-of-1 trials have been used sparingly in medical and general clinical settings. We briefly review the history, motivation and design of n-of-1 trials and emphasize the great utility of modern wireless medical monitoring devices in their execution. We ultimately argue that n-of-1 trials demand serious attention among the health research and clinical care communities given the contemporary focus on individualized medicine.
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An individual patient in an RCT could show no improvement, have an adverse reaction to treatment, or benefit from the control (even if the control is shown to be statistically inferior).
“An individual patient in an RCT could show no improvement, have an adverse reaction to treatment, or benefit from the control (even if the control is shown to be statistically inferior) [22].”
From Graded exposure treatment for adolescents with chronic pain (GET Living): Protocol for a randomized controlled trial enhanced with single case experimental design (2019) · cites this paper as [22]
In “Do n-of-1 clinical trials have a role in clinical science?” (page unavailable), the paper describes variable individual responses and the search for a drug with acceptable efficacy and tolerable side effects. “Combining & evaluating multiple n-of-1 trials” also distinguishes responders from nonresponders in population-based trials. These passages support the possibility of no improvement or adverse effects, but they do not say that a patient may benefit from a control shown to be statistically inferior. (LLM, conf=0.83)
Experimental — accuracy not yet measuredIn SCED studies of medicine, a washout period and placebo controls can be factored into phases, reducing bleed-over bias between phases common in psychotherapeutic interventions.
“The advantage of when the intervention is a medicine in a SCED study is that a ‘washout period’ (and also placebo controls) can be factored into the phases of the study, so reducing the bleed‐over bias between phases common in psychotherapeutic interventions (Lillie et al., 2011).”
From Effectiveness of cognitive analytic therapy for bipolar affective disorder: A co‐produced single subject cumulative treatment design with extended follow‐up (A <sup>1</sup> /B/A <sup>2</sup> /C‐FU) (2022) · cites this paper as Lillie et al., 2011
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References 96 · Cited by 706
Research works printed but not linked: 1
- [21]Everitt BS Pickler A Statistical Aspects of The Design of Clinical Trials Imperial College Press London, UK 2004
- Authors
- Lillie, E. O., Patay, B., Diamant, J., Issell, B., Topol, E. J., & Schork, N. J.
- Affiliations
- Scripps Health (US)
- Scripps Research Institute (US)
- Venue
- Personalized Medicine
- Publisher
- Informa UK Limited
- Published
- 2011-03
- Volume
- 8
- Issue
- 2
- Pages
- 161-173
- ISSN
- 1741-0541 (ISSN-L)
- 1744-828X
- PMC
- PMC3118090
- OpenAlex
- W2124211545
- Cited by
- 706
- References
- 96
- Citations by year
- 2026: 42 · 2025: 54 · 2024: 61 · 2023: 56 · 2022: 64 · 2021: 62 · 2020: 69 · 2019: 61 · 2018: 50 · 2017: 55 · 2016: 40 · 2015: 35 · 2014: 32 · 2013: 20 · 2012: 3
- FWCI
- 15.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Personalized Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Price Foundation (Zurich, Switzerland) and Scripps Genomic Medicine (U19 AG023122-05, R01 MH078151-03, N01 MH22005, U01 DA024417-01, P50 MH081755-01, R01 AG030474-02, N01 MH022005, R01 HL089655-02, R01 MH080134-03, U54 CA143906-01, UL1 RR025774-03)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- N-of-1 trials, personalized medicine, crossover design, washout period, placebo comparison, intervention efficacy, adverse effects
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