CannMed Coffee Talk

Applying AI and Machine Learning to Medical Cannabis with Hemant Kumar Bid, PhD

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Dr. Hemant Kumar Bid is a top educator in the field of Biotechnology and Medical cannabis. He serves as Program Director for the Morehouse School of Medicine, using his extensive background in biotechnology research and cannabinoid research to educate graduate students and infuse the industry with science-backed legitimacy.

Recently, Hemant has become deeply engaged with Artificial Intelligence and Machine Learning through his academic, clinical, and program development work. 

During our conversation we discuss:

  • How AI and machine learning are accelerating drug discovery, enabling personalized treatment, and analyzing complex genomic and clinical data.
  • How the Morehouse School of Medicine is updating its biotechnology curriculum to integrate AI/ML 
  • Why the accuracy of AI predictions depends entirely on data quality fed into the models, making standardization, diverse representation, and clean datasets critical for success
  • How AI can help reduce trial-and-error prescribing in favor of personalized care for specific patient conditions, optimized dosing, and potential adverse effects and/or drug interactions.
  • Major challenges that need to be overcome before AI and ML can truely transform medical cannabis treatment. 

    • Thanks to This Episode’s Sponsor: Tikun Olam

    Tikun Olam is the world’s first licensed medical cannabis company. With over 20 years of clinical cannabis research, Tikun Olam has conducted 7 clinical trials and published over two dozen academic journal studies using its heirloom cultivars. Tikun Olam products are designed for specific needs: pain relief, better sleep, digestive comfort, and neurological balance — all standardized for consistent, predictable results. If you’re curious to learn more about their products or research, they even offer a free one-on-one consultation with a licensed nurse.

    Shop online or find a dispensary at tikunolam.com

    Additional Resources

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