BSc Neuroscience
MRes Research Methods in Neuroscience
PhD Pharmacoepidemiology|Anticholinergic Drugs (candidate)

info@mysite.com +44-075-186
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Download my research paper on infraslow dynamics
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Title:"Infraslow Dynamics Across Cortical Layers"
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Download my PhD research proposal
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Title:" Investigating associations between anticholinergic burden and mobility
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Formal Education Bio
2019/20
University Of Leicester
MRes Research Methods in (Computational) Neuroscience
2015/19
University College London
BSc Neuroscience
2013/15
Cardiff Sixth Form College
A-level college in Cardiff, Wales UK
2021/25
University Of Bath
PhD (candidate) Pharmacy & Pharmacology
2010/12
Maru-a-Pula School
Gaborone, BOTSWANA

Biography
I am interested in cells with excitable membranes (neurons) as well as pharmacology. The latter can affect the former in a big way.
2021-2025
My PhD research covers geriatric pharmacoepidemiology and pharmacovigilance. I seek to design and build an anticholinergic burden scale that utilizes pharmacokinetic and pharmacodynamic data of drugs and then determine whether the new scale can be correlated with impaired mobility outcomes by using a large patient dataset from the International Resident Assessment Instrument (interRAI) n>15k. Current scales measuring anticholinergic burden are not thorough in their quantification of burden and give rise to a "hit and miss" result with regards their correlation with impaired mobility and or cognition. If you wish to read a summary of my research proposal on this subject matter, you can find a downloadable pdf copy on the left panel.
2019-2020
I conducted a project in computational neuroscience for my MRes program at the University of Leicester. I used extracellular electrophysiological recordings from the visual cortex of 19 mice each recorded over an average of 5.3hrs. The long electrode that was used for this spanned and recorded from all layers of the cortex. Now, 5.3 hrs is a really long time for neurons, so these long recordings where great to pick out any “infraslow” dynamics that may exist in the cortex’s system. There indeed existed some slow oscillating dynamic for the firing rates for example, with the rates increasing and decreasing with depth. To address the "rate vs spike-time" code aspect, I also had to probe if there were any interesting dynamics in the spike count variation of the spike trains…and for this I relied on a statistical quantity called the Fano-factor. Download adjacent PDF to read.
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Education/Qualifications:
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MRes Research Methods, (Computational) Neuroscience (University of Leicester)
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BSc (Hons) Neuroscience (University College London)
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Publications
June 16, 2022
The association between anticholinergic
burden and mobility: A systematic review
and analysis
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Objective/Purpose: This systematic review
aimed to synthesise data from published
studies regarding the association between
anticholinergic burden and mobility.
The studies were critically appraised for the
strength of their evidence.
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February 23, 2019
The posterior parietal lobe; more specifically
the Brodmann area 7a has been implicated in
computing spatial representation and location
of external stimuli and objects. Three different
populations of neurons in this region have been
classified according to the stimulus they
respond to...
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January 03, 2018
Abstract
Chronic cough is defined as cough lasting
more than 8 weeks [26]. This cough condition
evades any diagnoses and no underlying causes
are normally found. This makes the cough both
refractory to conventional therapy and
deleteriously affect the quality of life of patients
with this condition...
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August 19, 2025

Rethinking anticholinergic burden in older adults: innovative approaches to detection and management
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This narrative review synthesizes recent advances in AChB measurement and deprescribing. It critically evaluates established tools like the Anticholinergic Cognitive Burden (ACB) scale and Drug Burden Index (DBI), alongside emerging machine learning – based models such as the ML-AB scale. The review also explores the role of digital health innovations such as clinical decision support systems and wearable technologies in enhancing risk stratification and deprescribing interventions.
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June 11, 2024
Assessing the anticholinergic cognitive burden classification of putative anticholinergic drugs using drug properties.
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Aims
This study evaluated the use of machine learning to leverage drug absorption, distribution, metabolism and excretion (ADME) data together with physicochemical and pharmacological data to develop a novel anticholinergic burden scale and compare its performance to previously published scales.
Methods
Experimental and in silico ADME, physicochemical and pharmacological data were collected for antimuscarinic activity, blood–brain barrier penetration, bioavailability, chemical structure and P-glycoprotein (P-gp) substrate profile. These five drug properties were used to train an unsupervised model to assign anticholinergic burden scores to drugs. The model performance was evaluated through 10-fold cross-validation and compared with the clinical Anticholinergic Cognitive Burden (ACB) scale and nonclinical Anticholinergic Toxicity Scores (ATS) scale, which is based primarily on muscarinic binding
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