Projects

Every child responds to cancer therapy differently. Yet today, most treatment decisions still follow standardized pathways that cannot fully capture individual risks. Our project builds an AI-supported clinical decision system that helps pediatric oncologists tailor therapy intensity to each child in real time, reducing toxicity while maintaining cure rates.

This project develops a new class of dual-acting anticancer molecules that chemically fuse the PARP1 inhibitor olaparib with thiodiazole scaffolds. By hitting DNA repair and tumor survival pathways at the same time, these hybrids aim to achieve stronger tumor killing, reduce resistance, and open a path to next-generation targeted therapies for hard-to-treat cancers.

Drawing on principles from target tracking, financial trading algorithms, and neural dynamical modeling, OncoHelper AI forecasts disease trajectories and guides truly precise therapy decisions. Its goal is to help clinicians cure more patients, avoid unnecessary toxicity, and give children with cancer a real chance at long, healthy lives.

This project develops and validates a next-generation zinc supplement built on peptide–zinc complexes derived from chickpea protein hydrolysates. The goal is to offer a sustainable, plant-based formulation that improves zinc absorption, reduces gastrointestinal side effects, and supports both everyday nutrition and clinical care for vulnerable groups, including children, older adults, and oncology patients.