At the heart of AI-PPT is a two-stage process that leverages artificial intelligence to drive discovery and development. In the first stage, AI computationally identifies active botanical compounds based on their pharmacokinetic (PK) and pharmacodynamic (PD) properties. Through advanced data mining and machine learning, we analyze large datasets to select the most promising ingredients with optimal absorption, distribution, metabolism, and excretion (ADME) profiles while minimizing toxicity.
In the second stage, these selected compounds undergo rigorous biological testing using cutting-edge molecular techniques. This includes the use of 3D organoid models—cell structures that mimic human organs—and -omics technologies to precisely assess efficacy and safety. By integrating AI with biological research, we can fast-track the development of effective therapies, moving from discovery to market with greater speed and accuracy.