The Challenge
Assessing Biocompatibility of Emerging Magnetic Nanomaterials
Iron carbide nanoparticles (ICNPs) show outstanding potential for biomedical applications including MRI contrast, magnetic hyperthermia therapy, and controlled drug delivery. Yet their biocompatibility remains a critical concern, and traditional experimental screening is time-consuming and resource-intensive.
A key barrier is the lack of universally accepted descriptors for representing nanoparticle structural features computationally. Standard experimental characterisation captures size, coating, and surface chemistry, but misses the atom-level features that drive biological interactions.
Our Approach
A dual modelling strategy combining experimental features with atomistic enrichment
Curate toxicological data from literature
Collected cytotoxicity data for ICNPs across 10 immortalised cell lines, standardised to 24-hour exposure endpoints with colorimetric viability assays. Built a unified dataset of 186 data points covering diverse core compositions, coatings, and concentrations.
Generate atomistic descriptors with ASCOT
Used the ASCOT toolbox and a modified NanoConstruct to build spherical NP models from iron carbide crystal structures. Generated atom-level descriptors capturing surface and bulk atom features for three iron carbide phases: cementite, hexagonal, and Hägg carbide.
Build and compare two modelling strategies
Developed an evidence-based approach using only experimental features and an atomistic-enriched approach that incorporates computed structural descriptors. Automated ML on the Enalos Cloud Platform evaluated multiple algorithms to identify the best performer.
Validate and explain model predictions
Validated the resulting Random Forest model against OECD principles for QSTR development. Applied SHAP additive values and permutation importance to reveal which nanoparticle characteristics most strongly drive cytotoxicity predictions.
Deploy as cloud web service
Made the final validated model freely available through the Enalos CHIASMA Cloud Platform, and published all curated data through the NanoPharos database for community reuse.