Data Analysis Yields Insights Into Medical Cannabis Use, Efficacy

Just about any industry benefits greatly from the proper use and evaluation of data. The tech giants of today are built mostly on data regarding their users, and advertisers rely on that data to more effectively target their efforts. Every major professional sport is undergoing an analytics revolution. Pharmaceutical companies use artificial intelligence (AI) to sort through reams of scientific data to find potentially effective active ingredients to be developed into approved drugs. In the medical cannabis industry, mostly due to the plant’s long history of prohibition, there is a decided lack of data regarding the use and efficacy of cannabis as a treatment for a wide variety of indications.

RYAH Group Inc. (CSE: RYAH) and its wholly-owned subsidiary RYAH Medtech are here to provide just the type of data and analysis needed to move the industry forward. With over 200,000 registered users providing input to the company’s patent-protected, AI-powered database, RYAH is providing unmatched insight into how, why, and how effectively medical cannabis is used.

How to Use the Data

RYAH publishes monthly reports discussing various topics arising from their analysis of the reams of data in its proprietary RYAH Cloud database, offering a glimpse of how the information can be used. The most recent one, from June 2021, takes a look at patients using cannabis to relieve pain. It’s an interesting analysis of who is using which strains to help treat which types of pain.

Over the prior three years or so, 41,260 RYAH-connected patients reported medical cannabis use for the treatment of pain. The company’s analysis of the collected data yielded several insights. Men were more likely than women to treat pain with cannabis. Indicas accounted for about 46% of use, sativas about 33%, and hybrids 21%. CBD-rich strains were generally preferred by all parties involved. The report even breaks down preferred strains by indication, including arthritis, headache/migraine, and inflammation.

The May 2021 report highlights medical cannabis use for the treatment of nausea, wasting syndrome, and cachexia (extreme weight loss and muscle wasting in the late stages of serious diseases like cancer, HIV or AIDS, COPD, kidney disease, and congestive heart failure). RYAH examined reporting from 17,313 such patients over the course of about 3 ½ years. Most of the data came from five states that list these indications as qualifying conditions for the use of medical cannabis. Imagine the amount of data that would be available from a much larger population sample.

Here, RYAH found that indica and indica-dominant strains were by far the preferred strain type, accounting for about 70% of use. The report further breaks down use by specific cultivars. Interestingly, the strains most highly rated for appetite stimulation were not the strains most commonly used by these patients. Women were slightly more likely than men to use cannabis for nausea, while the wasting syndrome and cachexia populations were tilted to men.

Advantages of Data, Macro, and Micro

Small sample size is really the bane of data analysis and can often result in wild assumptions that don’t pan out when tested in larger populations. If 40 people report their experiences in treating pain to their medical provider, that doctor does not have enough information to form generalized recommendations. But if that doctor has access to information from 40,000 patients it’s a different story. RYAH’s database provides that type of scale to all parties involved – patients, doctors, researchers, drug developers, growers, etc.

On the flip side, the company’s personalized app draws information from that large dataset and combines it with each patient’s individual experience to provide specific recommendations for that patient. The whole system is fueled by RYAH’s suite of smart dosing devices, including a patch, inhaler, and pen. The devices allow patients to measure and control their doses, something that is a huge challenge considering the variables and inconsistencies in the chemical makeup of cannabis plants.

Taking the doctor-patient use of RYAH devices one step further, organizations conducting clinical trials are finding value in the company’s offerings. RYAH Smart inhalers are being used in a huge clinical trial based in the UK. A major oncology clinic aims to explore the efficacy and safety of cannabis to treat patients suffering from chronic pain. Over a five year study, the clinic intends to work with tens of thousands of patients. RYAH will supply IoT-controlled Smart Inhalers with a fully customized software solution and direct API data integration with the clinic’s Electronic Health Record system. This means researchers will better protect participant privacy, mitigate the number of variables associated with cannabis consumption, and make scaling the trial relatively simple.

The Upshot

RYAH is providing large amounts of data to a medical cannabis industry in desperate need of just that sort of information. This data is used by patients and doctors to personalize and control treatments, by doctors and researchers to learn about the trends and realities of patient use, by growers to determine which strains are preferred by patients, and by clinical researchers to organize and inform their studies. RYAH recently went public on the Canadian Securities Exchange and is aggressively growing its reach and distribution in lockstep with the explosive growth of the cannabis industry in general. For cannabis, the time is now to establish widespread legitimacy, and data like RYAH’s is crucial to achieving that goal.

This article was published by CFN Enterprises Inc. (OTCQB: CNFN), owner and operator of CFN Media, the industry’s leading agency and digital financial media network dedicated to the burgeoning CBD and legal cannabis industries. Call +1 (833) 420-CNFN for more information.

About Robin Lefferts

Robin Lefferts has been involved in the legal cannabis industry since 2012, sometimes as an active participant and always as an interested observer.