Ryan Chahl
Project Management | Product Management | Business Analysis
Ryan Chahl
Project Management | Product Management | Business Analysis

Clinical Recommendation Information System

Year

2022

Client

36eight Technologies

Background

Cannabis has been used medicinally for thousands of years in many cultures. Up until December 2020, cannabis was in Schedule IV of the United Nations’ Single Convention on Narcotic Drugs, which subjected it to special restrictions; and consequently, modern medicine has not rigorously examined, tested, and clinically validated its safety and efficacy on treating diseases. As cannabis becomes more widely accepted and legalized for medicinal purposes doctors and pharmacists alike are struggling to know how to prescribe it.

Through C/R/I/S (based on underlying select clinical data/knowledge and the use of AI/ML algorithms that determine optimized recommendations), we are able to:

  • Select the most appropriate medical cannabis product from Health Canada licensed facilities
  • Initiate and titrate dosing
  • Check for cannabis-drug interactions
  • Schedule follow-up appointments
  • Manage outcomes

My Role

During my time at 36Eight Technologies I played the role of Product Manager, this meant I had to manage the product roadmap, support the development and quality assurance teams, while ensure any features that were released met the needs of our customers which were pharmacists.

The Application

C/R/I/S uses complex machine learning in order to provide recommendations to pharmacist on which product would best suit the patient. This took into account factors like the medical condition being treated, weight, previous cannabis use, and many other critical patient factors.

The application went beyond recommended the product, it also recommended what dosing schedule the patient should follow in order to achieve an optimal outcome.

C/R/I/S would also support the pharmacist in tracking the progress patients experienced, this feedback would be de-identifed and utilized by the machine learning engine to provide improved recommendations.