Our Services

From complex data to clear answers.

Quantitative Modelling & Analysis

Potency Analysis Calculating potency estimates and study summary metrics, such as TD50s, BMDs, NOAELs, from individual or aggregated study results, including uncertainty estimates.

Benchmark Dose Modelling Running BMD workflows for continuous and quantal endpoints, including model selection, goodness-of-fit, and clear reporting of results.

Cross-Study Data Integration Pulling together findings from multiple studies or data sources into a coherent quantitative summary, making it easier to compare safety profiles across compounds or time points.

Methodological Consultancy Advice and expert input on the use of quantitative methods where guidance is ambiguous, or still evolving.

Data Management & Exploration

Exploratory Data Analysis Working with preclinical and clinical safety datasets to identify patterns, anomalies, and signals; including adverse event data, biomarker trends, and laboratory findings.

Data Visualisation Producing clear, well-designed reports and visualisations for safety data: dose-response curves, time-course plots, cross-study comparisons, and more.

Historical Control Data Analysis Collating and statistically characterising historical control datasets to give meaningful context when interpreting study results.

Machine Learning & QSAR

QSAR Modelling Building quantitative structure-activity relationship models to predict safety-relevant endpoints from chemical structure, supporting early compound screening and prioritisation.

Machine Learning for Safety Data Applying ML methods to safety datasets; classification of toxic versus non-toxic compounds, identification of structural alerts, or prediction of dose-response behaviour from chemical and biological features.

Model Validation & Applicability Domain Rigorous assessment of model performance and applicability domain, so predictions come with a clear understanding of where they can and can't be trusted.

Tools, Automation & Training

Custom Tool Development Building analytical tools, pipelines, and dashboards to fit a team's specific data and workflows; from one-off scripts to deployed applications.

Pipeline Automation Automating repetitive analyses to reduce manual effort and improve reproducibility across routine safety work.

Method Validation & QC Independent review of existing analytical methods or tool outputs, useful as a check before results feed into important decisions.

Training & Knowledge Transfer Practical training sessions to help internal teams get up to speed on quantitative methods or tools built as part of a project.

AI-Powered Workflow Development Design and implementation of AI-powered tools and agentic workflows to assist analytical tasks, such as literature review, report drafting, or data extraction. Built with auditability and human oversight in mind, so outputs can be reviewed, traced, and trusted in a regulated environment.

Data Integration & Knowledge Systems Development of systems that allow AI tools to work with a company's own data such as internal study results, historical databases, or proprietary reference sets. With an emphasis on keeping sensitive information secure and outputs interpretable by the scientists using them.

Tools, Automation & Training