Agnieszka Gajewicz

Assistant Professor

University of Gdańsk

Poland

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Agnieszka Gajewicz is an Assistant Professor at the University of Gdansk, Poland. Her research focuses on the development of peptidomimetic compounds as antimicrobial agents, quantitative structure-activity relationships (QSAR) in toxicology, and the environmental impact of nanomaterials. Recent publications include studies on cyanide toxicity, metal bioaccumulation prediction, and the health effects of carbon nanotubes.

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GERMANY

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Anders Baun

Technical University of Denmark

DENMARK

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Agnieszka Gajewicz

Research Interests

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Articles (20)

Role of Structural Modifications in Peptidomimetic Compounds as Potential Antimicrobial Agents against Staphylococcus aureus and Streptococcus pyogenes: Balancing Bioavailability, Safety, and Antimicrobial Activity

Decoding cyanide toxicity: Integrating Quantitative Structure-Toxicity Relationships (QSTR) with species sensitivity distributions and q-RASTR modeling

Dynamic QSAR modeling for predicting in vivo genotoxicity and inflammation induced by nanoparticles and advanced materials: a time-dose-property/response approach

Metal bioaccumulation prediction via QSPR-q-RASPR synergy and cross-species risk analysis

Metal bioaccumulation prediction via QSPR-q-RASPR synergy and cross-species risk analysis

The Impact of Carbon Nanotube Properties on Lung Pathologies and Atherosclerosis Through Acute Inflammation: a New AOP-Anchored in Silico NAM

Bioconcentration potential of ionic liquids: New data on membrane partitioning and its comparison with predictions obtained by COSMOmic

Elucidation of molecular mechanisms involved in tadpole toxicity employing QSTR and q-RASAR approach

Oxide-Perovskites for Automotive Catalysts Biotransform and Induce Multicomponent Clearance and Hazard

Hazard assessment of nanomaterials: how to meet the requirements for (next generation) risk assessment

A machine learning q-RASPR approach for efficient predictions of the specific surface area of perovskites**

Design and synthesis of TiO<sub>2</sub>/Ti<sub>3</sub>C<sub>2</sub> composites for highly efficient photocatalytic removal of acetaminophen: The relationships between synthesis parameters, physicochemical properties, and photocatalytic activity

Quantitative multi-species toxicity modeling: Does a multi-species, machine learning model provide better performance than a single-species model for the evaluation of acute aquatic toxicity by organic pollutants?

A novel quantitative read-across tool designed purposefully to fill the existing gaps in nanosafety data

Towards Computer-Aided Graphene Covered TiO2-Cu/(CuxOy) Composite Design for the Purpose of Photoinduced Hydrogen Evolution

How Do the Different Types of Carrier and Drying Techniques Affect the Changes in Physico-Chemical Properties of Powders from Chokeberry Pomace Extracts?

Chemometric contribution for deeper understanding of thermally-induced changes of polyphenolics and the formation of hydroxymethyl-L-furfural in chokeberry powders

The kernel-weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models

Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: Towards similarity-based machine learning methods

Aquatic toxicity (Pre)screening strategy for structurally diverse chemicals: global or local classification tree models?

Collaborators (6)

Joanna Dołżonek

Justyna Sawicka

Wojciech Lisowski

Anna MICHALSKA-CIECHANOWSKA

Stefan Stolte

Anders Baun

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