Semiconductor Electronic Label-Free Assay for Predictive Toxicology.

Area of Science:

• Biomedical Engineering
• Toxicology
• Nanotechnology

Background:

• Animal testing presents logistical challenges for new material toxicity screening.
• In vitro cellular-level screening, particularly secretomic assays, is crucial for prioritizing materials.
• Existing assays like ELISA have limitations in sensitivity, throughput, and speed.

Purpose of the Study:

• To develop a novel, highly sensitive, and rapid assay for predictive toxicology.
• To introduce the semiconductor electronic label-free assay (SELFA) platform for secretomic analysis.
• To evaluate SELFA's performance against standard assays and its utility in nanomaterial safety assessment.

Main Methods:

• Development of a holistic assay platform and procedure named semiconductor electronic label-free assay (SELFA).
• Incorporation of an amplifying nanowire field-effect transistor biosensor within the SELFA platform.
• Deployment of SELFA secretomics for predicting inflammatory potential of engineered nanomaterials.

Main Results:

• SELFA demonstrated superior sensitivity and comparable selectivity to standard enzyme-linked immunosorbent assay (ELISA).
• SELFA offered a significantly shorter turnaround time compared to ELISA.
• In vitro and in vivo validation confirmed SELFA's predictive accuracy for nanomaterial inflammatory potential.

Conclusions:

• SELFA provides a high-sensitivity, label-free method for predictive toxicology.
• The platform offers a viable alternative to traditional methods, potentially reducing animal experimentation.
• This work establishes a foundation for advanced biosensing applications in material safety evaluation.