This lecture gives an overview of the state of the cannabis science, the North American markets and our cannabis research. Bridging the gap between analytical chemistry, machine learning, and synthetic chemistry, this compilation of studies explores the multifaceted nature of cannabis compounds. We begin with advancements in extraction techniques, utilizing machine learning to optimize yield predictions in large-scale botanical recovery, specifically focusing on cannabis. This approach significantly enhances the efficiency and precision of extraction processes. We then transitions to molecular analysis, examining the stability and transformation of CBD derivatives, highlighting the need for robust quality control in product development. Additionally, the lecture addresses the critical aspect of safety in cannabis use by exploring innovative strategies for heavy metal testing, demonstrating how pooling methods can reduce testing resources while maintaining safety standards. The lecture will answer the question of how to build the best joint, the implications of joint architecture on cannabis consumption, offering insights into optimizing product efficacy and consumer experience. Overall, this lecture encapsulates the collaborative efforts between academia and innovative research, providing a comprehensive understanding of the complexities and potential of cannabis chemistry.