Ai-accelerated discovery of heme decolorization chemistries and materials
An AI-native materials-informatics platform that accelerates discovery of effective heme/hemoglobin decolorization chemistries under mild, blood-relevant conditions. The solution combines predictive modelling with lab-scale prototyping to deliver validated leads, samples, and a reusable model, targeting applications in absorbent hygiene and stain-removal products.
Overview
Polymerize offers an AI-accelerated discovery platform for identifying chemistries and materials that decolorize heme and hemoglobin under mild, blood-relevant conditions. The solution targets a clearly defined barrier: cutting visible heme colour in high-protein, catalase-rich environments while ensuring controlled activation and dry-storage stability. This capability is relevant to absorbent hygiene products and any application requiring discreet, effective blood-stain management.
The platform combines an AI-native materials-informatics engine with a lab-scale prototyping and testing network, enabling end-to-end predict, formulate, and characterise loops. Rather than relying on manual trial-and-error, the system models candidate oxidative, reductive, and complexation chemistries, reactive polymers, and selective adsorbents—including their effect on brown and green by-product hues—then runs active-learning design of experiments to efficiently search a large combinatorial space and shortlist the most promising agents.
Technical specifications
Key capabilities:
- AI-native materials-informatics platform with 35+ domain-guided models trained on polymers, chemicals, and advanced materials
- Active-learning DoE to accelerate discovery across large combinatorial chemistry spaces
- Lab-scale prototyping network for preparing and screening candidate formulations
- Co-optimisation of encapsulation and immobilisation for dry-storage stability and controlled activation
- Validation against blood/menstrual simulants measuring colour reduction, by-product control, and safety-relevant properties
Proven performance: In a water-based paints programme, the platform modelled 50+ ingredients against 15+ properties (including optical/colour targets) and halved model error from 16% to 8%. A production-ready phase-change material with encapsulation was delivered over 65% faster than traditional R&D.
Technology readiness level
The platform is commercially deployed and validated across industries including automotive, specialty chemicals, coatings, and packaging, with SOC 2 and ISO 27001 security compliance. For the specific heme decolorization application, a structured multi-phase program spans approximately 13–19 weeks: scoping (2 weeks), discovery modelling with active-learning DoE (3–5 weeks), lab prototyping and screening (5–8 weeks), and down-selection to 1–2 validated leads with clear mechanisms, samples, and a reusable predictive model ready for pilot evaluation.
About Polymerize
Polymerize is an AI-native platform specifically engineered to transform materials research and development. It operates as a system of intelligence that integrates a unified data foundation, domain-specific AI models, and explainable insights to accelerate the discovery, development, and scaling of new materials. By digitizing experimental workflows, the platform replaces manual, spreadsheet-based processes with a centralized, data-driven backbone. The solution features over 35 domain-guided models trained on polymers, chemicals, and advanced materials, which allow R&D teams to predict material properties, optimize formulations, and gain scientific explanations for AI-driven recommendations.
The platform serves global R&D teams across industries such as automotive, specialty chemicals, coatings, and packaging, helping them reduce failed experiments and shorten go-to-market timelines. By capturing and leveraging institutional knowledge, Polymerize enables organizations to turn years of trial-and-error into targeted innovation, ensuring that data from past experiments informs future research. Customers use the platform to achieve significant ROI through increased discovery speed and streamlined operational forecasting, with security compliance standards like SOC 2 and ISO 27001 integrated to protect sensitive intellectual property. Founded in 2020 and headquartered in Singapore, the company maintains a global presence with offices and strategic collaborations spanning Asia, Europe, and the United States.
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