Danielle Newby

B.Sc, PhD

Postdoctoral Researcher

I am an early career dementia researcher with an interdisciplinary background in epidemiology, machine learning and pharmacology. Since April 2016, I have been working as a post-doctorate researcher in the informatics team of the Translational Neuroscience and Dementia Research Group jointly led by Sir Professor Simon Lovestone and Professor Noel Buckley.

My main areas of research within the team involve the analysis of real-world data such as medical electronic health records (EHR) datasets in order to characterise the role of certain diseases, their risk factors and drug treatments with dementia risk and cognitive decline. By understanding these relationships this will provide an evidence base to support public health intervention for dementia prevention.

My previous research positions concentrated on investigating the effects of pharmacological and physical activity interventions on ageing using genetic datasets. This previous experience built on my PhD research where I utilised machine learning and statistical methods to predict oral absorption of pharmacological compounds.

Recent publications

RISK OF PARKINSON'S DISEASE (PD) IN PATIENTS TAKING ADRENERGIC DRUG TREATMENTS
Conference paper

Stacey J. et al, (2018), VALUE IN HEALTH, 21, S329 - S329
Cross-sectional and longitudinal analyses of outdoor air pollution exposure and cognitive function in UK Biobank.
Journal article

Cullen B. et al, (2018), Sci Rep, 8
Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [18F]-Flutemetamol PET Scan Result.
Journal article

Westwood S. et al, (2018), Front Aging Neurosci, 10
Machine learning for predicting lifespan-extending chemical compounds
Journal article

Newby D. et al, (2017), Aging, 9
The influence of insulin resistance on cerebrospinal fluid and plasma biomarkers of Alzheimer's pathology.
Journal article

Westwood S. et al, (2017), Alzheimers Res Ther, 9
Prediction of drug-induced phospholipidosis
Conference paper

Newby D. et al, (2016), TOXICOLOGY LETTERS, 258, S284 - S284
Prediction of drug-induced phospholipidosis
Conference paper

Newby D. et al, (2016), TOXICOLOGY LETTERS, 258, S284 - S284
Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption.
Journal article

Newby D. et al, (2015), Eur J Med Chem, 90, 751 - 765
Comparing multilabel classification methods for provisional biopharmaceutics class prediction.
Journal article

Newby D. et al, (2015), Mol Pharm, 12, 87 - 102
Pre-processing feature selection for improved C&RT models for oral absorption.
Journal article

Newby D. et al, (2013), J Chem Inf Model, 53, 2730 - 2742

More publications