Computational & Predictive Toxicology
Human-Relevant Safety Data that Meets Modern Regulatory Expectations
Bringing new chemicals and pharmaceuticals to market requires sophisticated safety assessments that increasingly must satisfy requirements to replace animal testing with new assessment methods (NAMs) to evaluate chemical safety. As experienced scientists and practitioners in computational toxicology and regulatory strategy, we provide clear, science-backed approaches to help our clients achieve faster approvals and confident market entry in this rapidly evolving regulatory landscape.
Technical Leaders
M. Andrew Maier, Ph.D., CIH, DABT, Fellow AIHA, Fellow ATS Principal, Toxicology, Health, and Ecological Sciences
Kristian Fried, Ph.D., Dr. rer. nat., DABT, ERT Senior Consultant
Ernest Fung, Ph.D., DABT, ERT Principal, Toxicology, Health, and Ecological Sciences
Morgan Willming, Ph.D., DABT Consultant
Accelerating Innovation in Health Risk Assessment
Integral Consulting and ScitoVation have partnered to revolutionize health risk assessment by combining computational toxicology, AI-driven analytics, exposure modeling, and environmental economics.
Key Benefits to Industry Clients:
- One stop for comprehensive scientific approaches to chemical safety assessment
- Accelerated innovation and increased confidence in outcomes
- Faster, more confident decision-making in health risk assessment
- Integrated tool kits to enable solutions that address data gaps in chemical safety assessments
Knowledge Share
Complementary Use of Read-Across and Other New Approach Methodology Approaches to Address Complex Scientific and Regulatory Challenges
The European Chemicals Agency Develops Comprehensive Toxicokinetics Database
Integral Consulting and ScitoVation Deepen Strategic Partnership, Develop Faster Chemical Safety Decisions, Using Advanced Molecular and Computational Toxicology Tools
Carcinogenicity Mode of Action Evaluations to Change Regulatory Standards
Developing Regulatory Standards for a Group of Organic Acids Based on Read Across and Mode of Action Evaluations
New Approach Methodologies (NAMs)
NAMs offer a modern approach to toxicological safety assessment by integrating exposure and mechanistic data through in vitro and computational models and a focus on human-relevant biology. With changing regulatory guidelines in the United States and abroad, NAMs are becoming the go-to tools for chemical safety assessment. We position you ahead of this regulatory shift with proven frameworks for pharmaceutical development, cancer risk evaluation, and consumer product safety.
Key Capabilities:
We are adept at designing, interpreting, and using an array of NAMs data, including:
- Cell-based assays
- Computational modeling (QSAR, PBPK, AI/ML)
- Omics technologies (transcriptomics, proteomics, metabolomics)
- Adverse Outcome Pathways (AOPs) and mechanism of action assessment
Read Across Analysis
Read across analysis predicts the effects of chemicals with limited data based on data from structurally similar chemicals, offering a powerful tool for filling data gaps without additional testing. Our approach combines chemical similarity assessment with biological activity prediction, providing regulators with the scientific confidence they need while dramatically reducing your testing requirements and timelines.
Example Specialized Applications:
- Gene expression-based read across for novel chemical classes
- Quantitative structural similarity assessment with biological validation
- Regulatory-grade documentation supporting read across conclusions
- Cross-species translation reducing uncertainty in human risk assessment
Physiologically Based Pharmacokinetic (PBPK) Modeling
Physiologically based pharmacokinetic (PBPK) modeling predicts how chemicals behave in the human body, addressing critical gaps where traditional testing is limited and species differences create regulatory uncertainty. With FDA explicitly highlighting PBPK models for first-in-human studies and subgroup identification, our custom models position you for regulatory success while reducing costly late-stage surprises.
Advanced Modeling:
- First-in-human dose prediction for pharmaceutical development
- Species-to-human translation eliminating regulatory uncertainty
- Metabolite prediction preventing late-stage safety discoveries
- Subgroup analysis supporting precision medicine approaches
AI Tools and Analysis
Our AI-powered analysis, enhanced through our ScitoVation partnership, transforms complex data sets into clear regulatory strategies. With FDA and other regulatory agencies exploring the use of AI tools for “learning patterns” and biomarker validation, our approaches provide the computational rigor that modern regulators expect while accelerating your decision-making process.
Example Specialized Applications:
- Pharmaceutical impurity acceptable daily exposure derivation with automated literature analysis
- Gene mutation signature causality assessment for litigation support
- Biomarker validation using machine learning for toxicity prediction
- Mode of action evaluation and hazard classification through AI
FAQs
FDA’s guidelines represent a fundamental shift, recommending certain NAMs for monoclonal antibodies immediately and targeting “animal studies as the exception” within 5 years. Companies adopting NAMs now gain competitive advantages through faster approvals and reduced testing costs, while those waiting face increasing regulatory pressure and delays.
NAMs adoption is disrupting the global animal testing market. FDA’s promise of reduced testing requirements creates an economic incentive for drug developers to adopt NAMs. Companies adopting validated NAMs benefit from significant time and cost savings compared to traditional animal studies, while positioning themselves advantageously as regulatory requirements tighten.
Our strategic alliance combines Integral’s regulatory expertise with ScitoVation’s cutting-edge computational tools, including the upcoming ScitoSim AI platform with validated biomarkers. This partnership provides seamless access to the AI and PBPK capabilities that FDA guidelines specifically highlight as critical for modern drug development and chemical safety assessment.
For many applications, yes – FDA has already emphasized NAMs over animal studies for monoclonal antibodies based on superior human relevance. Our approach strategically combines multiple NAMs to build regulatory confidence, often providing comprehensive predictive data while meeting evolving agency expectations.
Implementation timelines vary based on your specific needs and regulatory pathway, but the strategic advantage of early adoption is clear. With FDA’s aggressive 5-year timeline for widespread NAMs adoption, companies starting now position themselves as regulatory leaders rather than as followers scrambling to catch up.
Our models can meet or exceed current regulatory scientific standards, with comprehensive documentation addressing agency questions proactively. Our established relationships with FDA, EPA, and international regulators, combined with our track record in successful NAMs submissions, ensure your approaches align with reviewer expectations and approval pathways.