Evidence shows that humans have been using cannabis medicinally for thousands of years for the treatment of a huge variety of ailments and illnesses. However, following a significant (although relatively short) period of prohibition during the most important period of scientific and medical development in history, there remains a significant gap in our knowledge regarding the medical potential of the plant.
This lack of scientific knowledge and clinical evidence has led to the current situation we see in the UK, and many other countries around the world, where medical cannabis is technically legal, but prescriptions remain limited. Despite being legalised in 2018, medical cannabis prescriptions in the UK remain low – particularly through the NHS – and cannabis-based medicines are currently only recommended for a very small number of conditions.
In recent years, there has been a massive uptick in medical cannabis research, however, the quality of evidence gathered in many of these studies is often considered insufficient in the opinions of insurers, regulators, and guideline bodies.
Randomised controlled trials (RCTs) are largely considered the gold standard for clinical research; however, there is increasing scepticism about the suitability of these trials for the research of medical cannabis. The authors of a recent article in Therapeutic Innovation & Regulatory Science state that, while “RCTs are necessary and should continue to be the standard against which medical evidence is upheld … their narrow scope can lack ecological validity to real-world circumstances and therefore lack generalisability in more diverse populations.” The barriers of RCTs are also increased in the specific case of cannabis-based medical products (CBMPs).
Meanwhile, there is a real need for the generation of acceptable evidence of the potential benefits and harms of medical cannabis to effectively inform policy and clinical practice. The authors of the same study aimed to assess alternative forms of evidence, including real-world evidence, to address this need.
The Limitations of RCTs in Medical Cannabis Research
Most medical cannabis research is centred on the cannabinoids found in the plant – most commonly CBD and THC. However, in addition to these compounds, there are over 140 other cannabinoids found in the Cannabis Sativa plant, in addition to flavonoids, terpenes, and other products. These compounds can potentially affect the clinical outcomes observed between CBMPs as different profiles and combinations of these compounds may have different effects.
Each cannabis plant develops its own distinct chemical profile, which is influenced by both the genetics and environment in which the plant is grown. Therefore, the results of one RCT clinical trial may not be relevant to all CBMPs. Current evidence reviews often fail to consider this.
Furthermore, the route of administration of CBMPs can also lead to significantly different results. The way in which a CBMP is administered can greatly affect the distribution, biotransformation, and elimination of active compounds. Therefore, the sole use of RCTs will ultimately fail to identify the most appropriate CBMP for each clinical scenario.
Real World Evidence (RWE)
RWE is evidence derived from health data sourced from non-interventional studies, registries, electronic health records and insurance data as opposed to the highly controlled setting of RCTs. The use of such evidence is on the rise, including the utilisation of state-level records (USA) to examine the effect of cannabis laws on opioid misuse and the use of online and self-administered survey tools to analyse national outcomes. There is also a recent focus on collecting evidence from clinical registries and databases with evidence generated from patient-reported outcome measures and long-term pharmacovigilance.
NHS England and NHS improvement in fact recommend the “need for the collection of structured data and the development of methods to further support the generation of new evidence, for patients who cannot enrol into relevant RCTs.” However, consistent use of RWE to aid regulatory decision making is yet to be normalised.
Comparing Real World Evidence and RCTs
Each of these study designs has its own set of advantages and limitations. RWE allows for broader inclusion criteria, meaning it can account for factors such as non-standard dosing, and it is not limited by scope of disease. Furthermore, RWE typically has longer patient follow-up which may identify additional outcomes and rare but important adverse effects that are not detected within the RCT design. This is known as pharmacovigilance and is arguably one of the most important roles of RWE.
RWE is also commonly anonymous, likely having an impact on the validity of some reported outcomes. For example, a recent anonymised study identified that many patients were driving under the influence (72% of patients). These are findings that may not be reported by patients in RCTs due to fear of repercussions, or strict inclusion criteria.
Nonetheless, there are also limitations to RWE, including the quality and provenance of the data stored in electronic medical and insurance records. For example, insurance records typically use coding specific for reimbursement purposes and may not provide all clinically relevant information. Furthermore, RWE can require complex statistical expertise to identify determine valid conclusions.
A lack of randomisation, controlled variables, and internal validity are also limitations to RWE, as this can make it more difficult to derive causative mechanisms behind clinical outcomes. On the other hand, this can also be considered a strength of RWE as this allows for generalisability to true clinical practice.
There is no denying that CBMPs are a complex range of pharmaceuticals that present challenges to traditional pathways of drug development and translation. RWE can be used in conjunction or as an extension to RCTs to aid in the collection of much-needed evidence to progress the approval and prescription of these medicines. However, it remains essential that the right tools and analysis are utilised to effectively unlock these potential insights from these sources.