Basket protocols are defined as single protocols, approved by relevant research regulatory bodies, that allow for a single intervention to be tested for multiple different disorders or conditions, such as a single drug for different types of cancer. Developers may be right to adhere to convention in delivering confirmatory trials, but, if resources and conditions allow, considerable benefits could be gained from more explorative study designs. Such exploration may be best served by research that can address a greater range of questions of clinical and real world relevance. Similarly, whereas confirmatory trials may choose to constrain eligibility and treatment criteria, pragmatic trials may benefit from broadening them, while maintaining a sensibly high-bar for contraindication-related exclusion criteria. Easy to sample bio-metrics and behavioural sampling could accrue large pools of objective data with potential predictive value. If such studies and data registries are designed with careful consideration of data quality and fitness, pragmatic research could create significant value for various different stakeholders, e.g. scientists, clinicians, regulators, health care systems, payers and investors. As has been the case with medical cannabis, treatment-seeking patients will look for guidance from clinicians who take theirs from scientific evidence. Liberal policy changes occurring prior to the conducting of sufficient research could create similar problems for clinicians as occurred with medical cannabis. Such imperfect clinical scenarios could, however, also represent opportunities for innovative pragmatic and observational research. The creation of electronic data registries, e.g. for prescribers of psilocybin therapy in regions legally permitting access , may be one appealing example,marijuana grow time table enabling the collection of valuable real-world data. Data registries and pragmatic trials will collect data from broad and diverse samples.
Data on use among healthy individuals can be supplemented by data from individuals seeking psychedelic therapy treatment for depression, particularly as safety is being established in this population . An even more ambitious project would be to utilise a protocol to only exclude individuals where there are good reasons to suspect elevated risk and inadequate specialist support. Indeed, future psychedelic therapy clinics in areas supporting legal access and/or operating under a research mandate may support such a scenario. Moreover, utilising digital tools, such as cellphone apps , to track outcomes linked to psychedelic use could generate large data pools that could be mined to inform on such matters as patient screening and treatment optimisation. Whether via data registries annexed to legal-access psychedelic therapy or approved pragmatic research trials, or both, the proposed approaches can serve the agenda of identifying transdiagnostic treatment targets . The RDoC initiative pays selective attention to phenotypes associated with pathology, neglecting parameters associated with wellness, and this may be an oversight. Evidence of reliable and sustained improvements in well-being and lifestyle with psychedelic therapy, as well as the maintenance of psychological wellness , recognition of the bidirectional relationship between psychological and physical health, and awareness of the substantial costs required to implement any human drug study, let alone a clinical trial with a psychedelic, and combined with a need for greater safety data across a diverse demographic, particularly given the liberalising political climate surrounding psychedelics, are all good reasons to justify innovative and pragmatic approaches to researching psychedelic medicine. Collecting large sample sizes will enable better prediction-ofresponse modelling , which will help mitigate risk and inform the potential customisation of care. A multi-site ‘trial’ or centralised registry would help generate and store the large data needed for reliable prediction-of-response modelling, with the added benefit of being able to assess between site discrepancies and consistencies.
Confirmatory trials constrain important treatment parameters such as dosage and frequency of interventions, whereas pragmatic psychedelic trials could exercise flexibility here, particularly given the nascent nature of the treatment model, where practitioners cannot confidently claim to know the best parameters for all individuals and indications. In the context of psychedelic therapy, what dosage, frequency-of-dosing, as well as frequency and nature of post-dosing psychotherapy sessions are optimal, and for which cases, are all key questions that may be best addressed via pragmatic research under a basket protocol – and/or via digital data collection. Upper limits on the number of dosing sessions and lower limits on the intervals between them may be set to reduce the risk of bad practice, but redosing in response to relapse and based on clinical judgement may be permitted, thereby reflecting the conditions of clinical practice post roll-out. Most modern trials of psychedelic therapy have employed just one or two fixed-dose treatment sessions for all participants within relatively small and homogeneous samples, not because of assumptions about best practice, but because of alignment with regulatory traditions and budget constraints. This article argues that carefully designed pragmatic trials implemented under a basket protocol could offer a powerfully progressive model for advancing our understanding of the safety, effectiveness, mechanisms, impact, best-use and pitfalls of a promising but vulnerable new treatment model in psychiatry. Progressive policy changes would likely be needed to actualise the proposed approach – but these are already occurring. For such policy changes to occur, a vision of the societal value of improved mental health care, and how this can be safely and effectively achieved via psychedelic therapy, will need to be well communicated to the public and policy makers. For the time being, DB-RCTs will continue to sway sceptical opinions and aid progress with regulators, who presently base pivotal licensing decisions on data derived from such trials. Our view, however, is that data derived from pragmatic trials may be able to teach us more about how best to deliver the treatment and how it could impact on the lives of a broad cross-section of people. To be clear, the argument here is for the complementary value of pragmatic trials, not for their superiority over DB-RCTs.
At the same time, however, we do challenge, as others have previously, the hierarchical preeminence of DB-RCT derived evidence . Exploration has special value early-on in a learning process; thus, it seems prudent in the context of psychedelic therapy that it be given consideration now, rather than further down the development path, when sub-optimal parameters begin to undergo regulatory ‘lock-in’. Rectifying this matter now may help mitigate risks associated with a too hasty scale-up of access. To achieve this, however, buy-in from multiple stake holders will be needed, including the public, policy makers and those in between, e.g. scientists, clinicians and investors.There are signs that modern psychiatry is ripe for a radical ‘new’ treatment model, and psychedelic therapy offers a multilevel paradigm-challenge. Assumptions challenged by it include those pertaining to: theoretical frameworks in mental health, models of therapeutic action, selection of sufficiently sensitive and specific assessment scales, trial design and clinical practice, plus drug, economic and social policy. Here we propose that pragmatic trials, data registries and electronic data capture will aid advances in psychedelic medicine by catalysing our understanding of best practice, which includes, but is not limited to, identifying and mitigating risks. Pragmatic trials, data registries and digital and biometric data collection can interface well with so-called ‘n = 1 trials’ , where individuals and/or prescribing doctors assess, prospectively, the impact of introducing a time-limited intervention in single-case studies. In contrast to large-scale observational cohort studies that allow for the modelling and prediction of response across wide demographics at the cost of experimental control ,marijuana growing table single-subject designs assess the effectiveness of an intervention experimentally, thus representing a scientifically rigorous alternative to RCTs . When participants serve as their own comparison , confounding variables such as age, gender or socioeconomic status are automatically controlled for, thereby decreasing the number of participants required to determine the likelihood of a causal relationship between intervention and outcome, and ultimately, research costs . Single-case approaches also bear relevance to ‘citizen-science’ initiatives, in which individuals’ willingness to engage in the scientific process is harnessed. For example, individuals may be invited to increase the rigour of their ‘self-experimentation’ by, for example, completing assessments, wearing biometric sensor devices or even engaging in a self-blinding placebo-controlled protocol, as was done recently for psychedelic ‘microdosing’ . As implied by some recent studies of ours , there is appetite for citizen-science-type engagement among users of psychedelics.
Specifically, we foresee value in the use of smartphone apps to collect data pertaining to psychedelic use in a convenient and efficient way . For example, the combination of single-case trial designs and remote digital assessments could enable the collection of scientifically rigorous efficacy data on self-medicative psychedelic use in small or difficult to access patient populations , the potential utility of which is particularly salient considering the significant challenges that COVID-19 has posed on clinical and research psychiatry, including psychedelic trials . Data from n = 1 experiments can be aggregated and analysed using Bayesian statistics and multi-level regression and post-stratification analyses to identify meaningful relationships within potentially rich datasets that could ultimately inform effective future care strategies. Idiographic high-frequency time-series data collected through such methods could enable more ecologically valid and nuanced modelling of change than conventional study designs . Zooming-out, the highlighted approach should not be interpreted as implying relaxed standards of screening or scientific rigour in psychedelic research. We are not, for example, advocating that researchers relax contraindication-based exclusion criteria intended to mitigate risks of adverse responses. Some might feel it premature to propose pragmatic trials for psychedelic therapy, as these are typically reserved for treatments that are already incorporated into clinical practice. However, we believe that it is right to begin such trials now, as policy changes are already afoot and could ‘get ahead of the data’, as occurred with cannabis, for example. There is presently insufficient data on which to recommend specific treatment parameters for specific populations and indications, as well as ‘no go’ criteria at screening, and big data pools would likely change this. Indeed, large-scale datasets from naturalistic sampling could have considerable harm reduction potential, by helping identify those most and least suitable for psychedelic therapy. Progressive policy changes on psychedelic medicine will likely have trickle down effects on research, innovation and investment in psychedelic medicine, particularly in the implicated geographical locations. Given the considerable cost-implications of a multi-site pragmatic research programme, health care payers and/or industry buy-in would likely be required to fund it, and the relevant parties would need to be incentivised to do so. Digital data collection could lessen this burden, however, particularly if individual end-users feel sufficiently incentivised to engage directly, e.g. via inputting data via a phone app . Mainstream, institutional-level funding has still not come into psychedelic science; philanthropy and now commercial investment have been its main drivers. Increasing demand for psychedelic therapy is poised to synergise with an upswell in initiatives to meet this, potentially jeopardising standards of safety and professionalism if corners are cut. In anticipation of and, to some extent, already witnessing the beginning of a ‘hype-cycle’, we believe that innovative, pragmatic and exploratory research can play a vital role, helping safeguard the development of a particularly promising, yet vulnerable, approach to mental health care.In the epidemiological literature, there is growing evidence that certain social risk factors may increase the risk of developing psychosis. Over the last decade, several lines of evidence suggest a possible association between a history of trauma in childhood and later psychosis or psychotic like experiences. A recent meta-analysis indicated that reported exposure to adverse events in childhood is associated with persistence of psychotic experiences, and other studies have suggested that perceived discrimination is a risk factor for psychosis. Additionally, Janssen and colleagues found that perceived discrimination predicted the incidence of delusional ideation in a dose response fashion, even after controlling for various confounds such as depressive symptoms, low self-esteem and neuroticism. Most studies to date investigating trauma and perceived discrimination have focused on established psychotic disorders or non-clinical samples. Although research interest is increasing in the trauma literature among those considered to be at clinical high risk of developing psychosis, little is still known about this relationship, and even less is known about perceived discrimination and those at CHR. A recent meta-analysis reported that childhood trauma is highly prevalent among CHR individuals. Furthermore it has been observed that CHR participants experience their first trauma at an earlier age compared to healthy controls, and that both the incidences of trauma, and the age at which trauma occurred were significant predictors of having a CHR status.