RI.MIND GROUP LTD., an neuro-technology software solution company, focused on various CNS drugs, substances and nutraceuticals markets, has launched its go-to-market and product expansion.
RI.Mind has set its goal to deliver brain-care personalized therapeutic solutions, while replacing anecdotal data with Evidence Based Actionable Information to prescribers and users.
Ri.Mind detects, predicts and monitors the effects of substances on the human brain by identifying neural patterns related to cognitive conditions, pharmaco-kinetics, therapeutic effects and clinical outcomes; thus, enabling data-driven therapeutic usage and selection, intake and optimization of dosage and desired outcome.
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?
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:
Trial and error
Difficulty in Identifying, tracking, and measuring medical cannabis effectiveness
Uncertainty about relevant and active ingredients
No consistency in strains and quality
No effective feedback from patients
No tools for doctors, HMOs and regulators
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.
R & D
13 years of advanced research and development
Investment and grants to date
Largest Data Base
Most rapidly growing proprietary brain functions data set (over 500,000)
Over 60 patents issued or pending
FDA / CE approvals and reimbursed schemes, winner of 2018 Erickson award for excellence in aging research.
USD 28 B
Global medical cannabis market in 2024
— Energias Market Research 2018
Less than 50%
Estimated current success rate in treating
brain-related disorders with
medical cannabis products
USD 216.75 B
Global precision medicine market by 2028
— BIS Research 2019