AI-Guided Phytochemical and Drug Synergy Mapping of Peganum harmala and Nigella sativa in Cancer Therapy

Background: Cancer continues to pose a significant health challenge worldwide, characterized by increasing incidence rates and constraints in current treatment options. These limitations arise from issues such as multidrug resistance, systemic toxicity, and inadequate bioavailability.[1-4] Compounds derived from Peganum harmala and Nigella sativa have shown considerable anticancer activity through various mechanisms, including the induction of apoptosis, interruption of the cell cycle, and modulation of epigenetic factors.[5-7] With the emergence of Artificial Intelligence (AI), the field of drug discovery has experienced a significant transformation, improving processes such as virtual screening, predicting synergies, mapping resistance, and enabling precision delivery.[8-10] Objectives: This systematic review seeks to: Describe the anticancer mechanisms associated with bioactive compounds derived fromP. harmala andN. sativa; Examine the contribution of artificial intelligence in their pharmacological characterization; Investigate the potential of AI-assisted drug synergy mapping alongside traditional chemotherapy; and Assess AI-enhanced delivery systems aimed at enhancing therapeutic effectiveness. Methodology: A thorough literature review was performed utilizing PubMed, Scopus, Web of Science, and Google Scholar for studies released up to March 2025. The studies considered for inclusion focused on P. harmala or N. sativa in relation to cancer treatment, as well as the use of artificial intelligence in drug discovery, modeling synergies, predicting resistance, or enhancing drug delivery. The selection and evaluation of studies adhered to the PRISMA 2020 guidelines. Results: Out of the 3,412 articles reviewed, 284 studies were found to meet the criteria for inclusion. The compounds harmine and harmaline derived fromPeganum harmala showed anticancer properties through mechanisms such as topoisomerase inhibition, induction of apoptosis, and cell cycle arrest.[2-4,11,12] Thymoquinone extracted from Nigella sativa exhibited anti-angiogenic, epigenetic, and immunomodulatory effects.[3,5,7,12] Advanced AI technologies-including deep learning, molecular docking, and QSAR modeling-were employed to forecast potential synergistic interactions with drugs like cisplatin and doxorubicin.[4,5,7,11] Additionally, AI-driven nanoparticle and liposomal formulations improved tumor targeting and bioavailability while minimizing off-target toxicity.[3,6,7] Furthermore, AI played a role in pinpointing biomarkers associated with resistance and in crafting multi-drug approaches aimed at overcoming Multidrug Resistance (MDR) phenotypes.[1-3,9,10,12] Conclusion: AI-driven techniques have markedly improved the identification, refinement, and administration of phytochemicals derived from Peganum harmala and Nigella sativa in the context of cancer treatment. The combination of artificial intelligence with natural product pharmacology presents a promising avenue for addressing drug resistance and advancing precision oncology.