The Central Role of Experts in AI-Enhanced Toxicology

New computational and AI-based approaches now make it possible to accelerate evidence gathering and analysis supporting toxicological risk assessment while improving consistency and reducing the time and cost of evaluations. Yet, while these technologies offer powerful support, the role of expert toxicologists remains central to ensuring that scientific rigor and interpretive judgment guide every conclusion.

At Onesum, we believe that Artificial Intelligence (AI) is transforming how toxicologists gather, organize, and interpret data. Algorithms can rapidly explore vast scientific datasets, uncover relationships that might escape manual review, and introduce new consistency and structure into the evaluation process. However, the true value of AI in toxicology lies not in automation alone, but in how it enhances expert decision-making.

That’s why, at Onesum, expert review isn’t a final “check” in our workflow; it is the foundation that gives meaning and accountability to every AI-assisted assessment. Our approach combines the speed and scalability of AI with the depth and judgment of human expertise to deliver transparent, reproducible, and scientifically defensible results.

Expert review is embedded throughout the entire process of the toxicological risk assessment. During data exploration and evidence gathering, experts define the scientific question, guide search strategies, and determine which findings are relevant, reliable, and fit for purpose. In data processing and synthesis, AI organizes complex information, spanning chemical properties, biological activities, toxicological endpoints, into structured outputs. Experts then review and refine these results, filtering noise, validating context, and ensuring consistency across diverse evidence streams. As evidence moves toward interpretation and reporting, expert insight takes centre stage. Toxicologists assess AI-derived outputs considering biological plausibility, regulatory context, and data uncertainty, transforming information into rigorous, defensible conclusions.

Through this integrated approach, AI and expert review work hand in hand: AI manages data and scale, while experts provide reasoning, context, and scientific integrity. The result is an assessment process that is both faster and more reliable.

Maintaining the right balance between automation and expertise is key to achieving both efficiency and scientific rigor. Toxicological assessments directly influence decisions that affect human health, where transparency and reliability remain essential. AI helps streamline discovery, while expert review ensures that quality and confidence are preserved throughout the process.

At Onesum, we see AI not as a replacement for expert judgment, but as its amplifier. It allows toxicologists to focus on interpretation rather than information overload, turning vast data into defensible, meaningful scientific conclusions.

Ultimately, it is the expert who ensures that AI-driven toxicological assessments remain grounded in science, bringing context, clarity, and credibility to every conclusion.