Using surrogate passive sampler devices and predictive machine learning algorithms to replace invertebrate use in micropollutant bioconcentration testing

Dr Leon Barron, Analytical & Environmental Sciences Division, King's College London
Dr Anthony Edge, Agilent Technologies UK Ltd.

Project Description

The aim of this project is to develop and apply novel passive sampler devices and in silico machine learning tools to potentially replace the use of invertebrate animals for polar micropollutant bioconcentration studies. Passive sampler devices (PSDs) are often used to monitor longer term occurrence of micropollutants, and mainly hydrophobic organic chemicals (HOCs), in the aquatic environment. PSDs are generally composed of a polymeric sorbent housed within a porous container and collect solutes over time by passive diffusion. Accumulation of chemicals on the sorbent represents a time-integrated record of exposure over that period. For polar organic chemicals (POCs), their ionisability and polarity makes uptake modelling significantly more challenging. However, there exists an exciting opportunity in this project to develop and apply recently successful predictive approaches at King’s to prioritise testing or remove the need to use model organisms entirely. This represents an excellent way to prioritise risk assessment for selected emerging POCs to biota for which no knowledge or standard reference materials exist. The candidate will use liquid chromatography-mass spectrometry (LC-MS) to characterise uptake rates for a range of pharmaceuticals, personal care products, pesticides and herbicides on several sorbents provided by Agilent across a range of environmental pH, salinity and temperatures. Following this, the student will determine the bioconcentration factor (BCF) of large numbers of POCs in Gammarus pulex, an environmentally relevant invertebrate organism exposed to such contaminants across the EU. The student will integrate these two datasets together using machine learning tools for BCF prediction followed by mechanistic assessment. There will also be the opportunity for the final PSD prototype to be deployed within the Thames River to determine the types of compounds present and prediction of BCF.


This highly interdisciplinary project will provide the student with comprehensive training in a broad range of scientific and transferable skills relevant to the biosciences. The student will be housed in the Analytical & Environmental Sciences Division at the KCL Waterloo campus, which is ranked 6th in the UK for 4* and 3* submissions in REF2014 (under Public Health, Health Services and Primary Care). It is a vibrant, diverse and inclusive research environment. The project will be led by Dr. Leon Barron within the Environmental & Forensic Chemistry research group which is fully equipped with state of the art analytical technologies including LC-MS, GC-MS and HRMS, as well as a dedicated temperature-controlled facility for continuous flow exposures for biota/PSD testing and a talented team of researchers all working on similar areas in support of this work. As part of this project, the student will spend a minimum of three months at Agilent Technologies UK, Ltd., a global leader in life sciences, analytical instrumentation/diagnostics and applied chemical markets. Agilent focuses on six key markets: food, environmental/forensics, pharmaceutical, chemical/energy, diagnostics and research. Agilent provide fast, accurate and sensitive methods for monitoring contaminants affecting quality of life including POCs in the environment. Its state-of-the-art R&D facilities in Shropshire house 13 R&D staff and four research labs to include development of polymer and silica particles for chromatographic and clinical/diagnostic applications. Training at Agilent will involve materials chemistry (including synthesis/application of solid phase extraction/sorbent formats) and analysis (LC-MS). They will learn what single sorbent formats and/or combinations will recover the widest range of POC residues and is critical to inform the mechanistic understanding of uptake data. The student will also be trained in Agilent’s business and potential aspects related to the research.


The student will be expected to present at national/international conferences as well as author peer-reviewed journal articles on their research. Good communication skills are essential. Candidates with a minimum upper second class honours undergraduate degree and/or postgraduate qualification in analytical chemistry, chemistry or environmental science are highly desirable, and especially those with experience of separation science and/or mass spectrometry.

Application

Interested applicants are encouraged to contact Dr Leon Barron (leon.barron@kcl.ac.uk) in advance of the deadline.

Closing date is 19th January. Please ensure that you read the Guidelines before submitting an application. Your application and supporting documents should be sent in a single email to LIDo.Admissions@ucl.ac.uk

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