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Our research strategy is based on the discovery and development of new psychedelic and non-psychedelic compounds for medicinal applications. This new pharmaceutical portfolio shows considerable advances over previous natural and synthetic drugs in terms of safety, effectiveness, stability, dose, and adverse effects. We employ natural chemicals as building blocks to create superior second-generation pharmaceuticals, utilizing artificial intelligence and machine learning (AI/ML) to uncover medication advancements in a cost-effective and efficient manner.
The purpose of developing these better second-generation chemicals is to provide patients with safer, more effective medicines while also providing doctors with improved dose control and drug behavior. To create these improved compounds, we examined the enormous number of psychedelics mentioned in the literature and anecdotal accounts to learn how these substances have been used therapeutically and, more importantly, what their faults are.
A detailed molecular examination of each medicine helps us to understand which aspects are responsible for undesired effects and deficiencies. This data is then utilized to create new second-generation molecules with higher performance, putting better management in the hands of physicians.
The current generation of natural psychedelic compounds originated in nature, making them the most suited to the organism's natural habitat. Although these compounds have been proven to be quite effective for therapeutic purposes, they were not designed to be used in a clinical context. As a result, there is a high need for next-generation medications that are more sensitive to the demands of patients and clinicians.