Predictive, LLC develops computational models and software that utilize artificial intelligence to predict the bioactivity and toxicity of chemical products, providing in-silico alternatives to traditional animal testing. This approach reduces the costs and time associated with safety assessments, while improving the relevance of toxicity predictions for human health outcomes.
Funding
$73.9K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional chemical safety assessments rely heavily on animal testing, which is expensive, time-consuming, and often provides limited relevance to human health outcomes. Current methods struggle to efficiently predict the bioactivity and toxicity of complex chemical mixtures.
Solution
Predictive, LLC offers AI-driven computational models and software that predict the bioactivity and toxicity of chemicals, providing in-silico alternatives to animal testing. Their software platform leverages existing toxicology assay databases to predict the toxicity of products and chemical mixtures. This approach aims to improve the efficiency and confidence of toxicology assessments, leading to safer compounds and reduced reliance on animal testing.
Target Audience
The primary customers are pharmaceutical, chemical, and personal care product companies seeking cost-effective and efficient alternatives to traditional animal testing for chemical safety assessments.
Features
- STopTOX: AI-driven computational NAMs (New Approach Methodologies) to replace "6-Pack" assays animal testing for acute systemic and topical toxicity.
- PredMD: Predictor of toxicity for medical devices, supporting NAMs-based chemical safety assessments.
- PreMixT: Predicts different types of mixture toxicity, including synergy of mixture components.
- Utilizes artificial intelligence and machine learning techniques to understand how chemicals affect people.
- Employs standardized experiments performed in past GLP studies to inform early safety decision-making.