Resources

02 JUL 2026 – PUBLICATION

Building Comprehensive Toxicity Data Libraries of Short-Chain Length PHA-Based Materials for the Development of Machine Learning-Based Predictive Tools

Polyhydroxyalkanoates (PHAs) have emerged as a promising alternative to conventional plastics due to their biodegradable and generally favorable biocompatible profile, allowing their application in medical fields, such as drug delivery systems and surgical implants. However, the toxicity assessment of these materials is complex, time-consuming, and costly. The present study aims to construct comprehensive, standardized data libraries for the cytotoxicity and ecotoxicity of PHAs and to develop and evaluate polymer-specific machine learning models that link polymer composition to toxicological outcomes.
By Filippou, Konstantina, Angelis, Alexandros, SOTIROPOULOS, NIKOLAOS, Kotzabasaki, Marianna, Sarimveis, Haralambos, Maraveas, Chrysanthos
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23 JUN 2026 – PUBLICATION

Machine Learning Prediction of Thermal Properties of PHB/PHBV-Based Materials: A Quantitative Structure–Property Relationship Approach Using an Integrated Polymer Database

Bio-based and biodegradable polymers such as short-chain-length (scl) poly(3-hydroxybutyrate) (PHB) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) are widely adopted in diverse areas such as healthcare, manufacturing, and packaging. However, high production costs and the complexity of tailoring their thermal properties, such as glass transition temperature (Tg), melting temperature (Tm), and crystallization temperature (Tc), hinder further adoption. The current study reported on the development of a raw dataset of PHB and PHBV materials compiled from 572 instances collected from the literature (558 instances) and in-house experiments (14 instances). The dataset encompassed compositional physicochemical parameters, molecular features, and corresponding thermal characteristics.
By SOTIROPOULOS, NIKOLAOS, Mindrinos, Leonidas, Peltier, Jean-David, Filippou, Konstantina, Kotzabasaki, Marianna, Tsigkas, Nikolaos, Maraveas, Chrysanthos
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29 APR 2026 – PUBLICATION

Machine Learning Methods for Mineralization-Based Biodegradation Prediction in Polyhydroxyalkanoate-Based Biopolymers: Insights from Lab-Scale Experiments

The use of bio-based and biodegradable plastic products (BBpPs) ensures the mitigation of environmental effects of fossil-based plastics, especially in humanitarian crises where waste management is challenging. Polyhydroxyalkanoates (PHAs) are promising biodegradable biopolymers that are biocompatible and do not cause microplastic pollution. However, experimental assessment of PHA biodegradation is challenged by its time- and resource-intensiveness. In this study, a comprehensive computational Quantitative Structure–Activity Relationship (QSAR)-based approach was developed to predict biodegradability of short chain length (scl)-PHA-based formulations consisting of various additives and building blocks.
By Kotzabasaki, Marianna, Mindrinos, Leonidas, SOTIROPOULOS, NIKOLAOS, Filippidou, Konstantina, Maraveas, Chrysanthos
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07 APR 2026 – PUBLICATION

A Data-Driven Framework for Predicting PHBV Biodegradation-Induced Weight Loss Based on Laboratory and Real-Environment Condition Tests

Polyhydroxyalkanoates (PHAs) emerge as promising biodegradable polymers for sustainable applications, yet predicting their biodegradation behavior under different environmental conditions remains challenging. In this study, the authors propose a novel data-driven computational framework for predicting biodegradation-induced weight/mass loss in PHA-based materials.
By Mindrinos, Leonidas, Kotzabasaki, Marianna, SOTIROPOULOS, NIKOLAOS, Filippou, Konstantinia, Maraveas, Chrysanthos
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30 APR 2026 – PUBLICATION

Workshop on Safe and Sustainable Bio-Based Polymers: from Design to End-of-Life in Circular Value Chains

This publication brings together the main insights and all presentations from the Workshop on Safe and Sustainable Bio-Based Polymers, organised by the ANIPH, ViSS, and PHAntastic projects as part of the Polymers 2026 International Conference.
By Blaya, Cristina, Fernández Ayuso, Carmen, Ana Crespo Cortés
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29 JAN 2026 – PUBLICATION

Exploring Lemon Industry By-Products for Polyhydroxyalkanoate Production: Comparative Performances of Haloferax mediterranei PHBV vs. Commercial PHBV

This study investigates the valorisation of lemon industry by-products as carbon sources to produce poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) using the halophilic archaeon Haloferax mediterranei. The study demonstrates an efficient PHBV production process based on waste valorisation, yielding a biopolymer with competitive physicochemical properties relative to a commercial standard, and provides integrated solutions to the global challenges of plastic pollution and food waste.
By Salvador García Chumillas, María Nicolás Liza, María Fuensanta Monzó Sánchez, Pablo ManuelMartínez Rubio, José Alejandro Arribas Agüero, Rosa María Martínez-Espinosa, Ramon Pamies
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22 DEC 2025 – PUBLICATION

D2.8 ANIPH Data Libraries

This deliverableforms the main data infrastructure facilitating the building up of the ANIPH Artificial Intelligence (AI) predictive tool (D2.5). In order to fully align with the goals of Task 2.5.1, the Agricultural University of Athens (AUA) developed comprehensive, high-quality datasets encapsulating the physicochemical, processability, (eco)toxicological and biodegradability properties of short-chain length polyhydroxyalkanoates (scl-PHAs).  *This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Kotzabasaki, Marianna, Filippou, Konstantina, Sotiropoulos, Nikos, Maraveas, Chrysanthos
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22 DEC 2025 – PUBLICATION

D2.6 Non-sensitive ICT Platform

Deliverable D2.6 reports the work carried out on the development of the ANIPH Non-Sensitive ICT Platform, composed of two digital tools designed to integrate the SSbD evaluation framework and to provide consumers with a reliable information system.   *This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Ortiz, Jamie, Matamoros Escobedo, Alba, Munares Sánchez, Gabriela
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22 DEC 2025 – PUBLICATION

D2.5 ANIPH AI predictive tool

The deliverable D2.5: “ANIPH AI Predictive Tool” presents the development, validation, and deployment of a suite of machine learning (ML) models designed to predict thermal, rheological, biodegradation, cytotoxicity and ecotoxicity properties of polyhydroxyalkanoate (PHA)-based polymers within the ANIPH project. *This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Angelis, Alexandros, Kotzabasaki, Marianna, Filippou, Konstantina, Maraveas, Chrysanthos
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10 DEC 2025 – PUBLICATION

D2.3 ANIPH SSbD framework

This deliverable presents the Safe and Sustainable by Design (SSbD) framework developed within ANIPH, including design principles and assessment criteria to ensure the safety and sustainability for the two expected use cases (i.e., wound dressings and their respective flexible packaging).*This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Matamoros Escobedo, Alba, Dussault, Èvelyne, Kotzabasaki, Marianna, Anestis, Vasileios, Maraveas, Chrysanthos
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10 DEC 2025 – PUBLICATION

D2.2 ILSs mapping

This deliverable provides a systematic mapping of existing Information and Labelling Systems (ILS) relevant to biobased and biodegradable plastic products (BBpPs), with a focus on their application in medical wound care products and packaging for humanitarian contexts.*This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Passenier, Rick, Lackner, Maximilian, Sharma, Saloni, Mukherjee, Anindya, Matamoros Escobedo, Alba, Dussault, Èvelyne, Pavon Losada, Juan Antonio, Vera, Cristina
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10 DEC 2025 – PUBLICATION

D1.2 Preliminary Data Management Plan and Ethic handbook

The Data Management Plan addresses the complete data lifecycle from initial generation and collection through long-term preservation, implementing FAIR principles to maximise data findability, accessibility, interoperability, and reusability.*This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Matamoros Escobedo, Alba, Vera, Cristina, Ferrando Garcia, Maite
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10 DEC 2025 – PUBLICATION

D1.1 Project management

The objective of this Deliverable is to establish and describe the methodology, procedures, and activities of planning, organizing, securing, monitoring, and managing the resources and work necessary to deliver the specific project goals and objectives in an effective and efficient way.*This deliverable has not yet been officially approved by the European Commission and should be considered a draft. 
By Fernández Ayuso, Carmen
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10 DEC 2025

ANIPH Flyer

A digital version of the ANIPH flyer outlining the project's mission
By Fondazione ICONS
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15 JUL 2025 – IMAGE

ANIPH Roll-up

ANIPH roll-up to showcase the project at public events
By Fondazione ICONS, Sloppy
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