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Utilising AI and big data to predict, diagnose and optimise the effectiveness of medical cannabis on the human brain.

Our Story

RI.MIND GROUP LTD., an Israeli neuro-technology service company, focused on the cannabis and nutraceuticals markets, is currently raising funding for its go-to-market strategy and product expansion.

Our Vision

RI.Mind has set its goal to re-shape the cannabis/nutraceuticals markets by delivering personalized therapeutic solutions, and replacing anecdotal data with Evidence Based Actionable Information to prescribers and users.

Technology

Ri.Mind detects, predicts and monitors the effects of cannabinoid-based products and nutraceuticals on the human brain by identifying neural patterns related to cognitive conditions, pharmaco-kinetics, therapeutic effects and clinical outcomes; thus, enabling data-driven product/ strain selection, intake and optimization of dosage and desired outcome.

The Challenge

Over 1,000 strains of cannabis are being actively cultivated today, all with widely diﬀerent cannabinoid ratios and terpene proﬁles, capable of inducing diﬀerent subjective experiences and medical therapeutic eﬀects. Finding the right strain for a particular patient dealing with a speciﬁc condition can be a daunting talk. To compound the challenge, another key factor in personalizing cannabis care relates to dosing: how much should a patient take to maximize the eﬀectiveness of the treatment while minimizing side eﬀects?

Personalised Medicine

Doctors and HMOs need to personalise the most appropriate cannabis product to each patient and understanding differences between patients.

Repeating Medical Conditions

Patients require ongoing monitoring and patient-care management due to repeating medical conditions

Agriculture As A Drug

Agri-cannabis companies need to: Know the effect of their products on medical conditions Obtain tools for managing product repeatability and diversity Deal with largely unknown results of plant / cannabinoids effects on medical conditions Address adverse medical effects

Data is Key

The Challenges Medicine Faces Today

Data is not collected and cross-referenced along the chain: from producers (farmers) and distributors, to doctors and HMOs, through to end-users (patients), as well as regulators and government agencies (such as FDA). This lack of qualitative and quantitative data creates the following problems:

Major Issues

1

Trial and error

2

Difficulty in Identifying, tracking, and measuring medical cannabis effectiveness

3

Uncertainty about relevant and active ingredients

4

No consistency in strains and quality

5

No effective feedback from patients

6

No tools for doctors, HMOs and regulators

The Solution

Big Data + AI + Machine Learning =

personalised medical cannabis prescriptions per drug, per condition, per patient.

RI.MIND has partnered with Elminda, an emerging biotechnology company dedicated to paving a path to better brain health by integrating big-data repositories AI and machine-learning algorithms with its proprietary BNA platform. BNA is an electro-physiology based functional brain mapping, imaging and monitoring technology for the early detection of potential abnormalities due to aging or incidence, as well as for monitoring the progress and impact of interventions, including lifestyle changes.

Elminda's BNA technology enables the creation of new standards for diagnosis, prediction and identification of conditions such as depression, anxiety, ADHD, Alzheimer, pain, concussion, PTSD, etc. Furthermore, it facilitates measuring the effectiveness of drug usage, condition progress/remission, prediction of drug effectiveness, and the monitoring of patients well-being.

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