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Publications

Risk of hydroxychloroquine, alone and in combination with azithromycin in the treatment of Rheumatoid Arthritis: a multi-national, retrospective study

LANE J., (2020), Lancet Rheumatology

Safety of hydroxychloroquine, alone and in combination with azithromycin, in light of rapid wide-spread use for COVID-19: a multinational, network cohort and self-controlled case series study

LANE J. et al, (2020)

Methotrexate and relative risk of dementia amongst patients with rheumatoid arthritis: a multi-national multi-database case-control study.

Newby D. et al, (2020), Alzheimers Res Ther, 12

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

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.

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.

Westwood S. et al, (2018), Front Aging Neurosci, 10

Machine learning for predicting lifespan-extending chemical compounds

Newby D. et al, (2017), Aging, 9

The influence of insulin resistance on cerebrospinal fluid and plasma biomarkers of Alzheimer's pathology.

Westwood S. et al, (2017), Alzheimers Res Ther, 9

Prediction of drug-induced phospholipidosis

Newby D. et al, (2016), TOXICOLOGY LETTERS, 258, S284 - S284

Prediction of drug-induced phospholipidosis

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.

Newby D. et al, (2015), Eur J Med Chem, 90, 751 - 765

Comparing multilabel classification methods for provisional biopharmaceutics class prediction.

Newby D. et al, (2015), Mol Pharm, 12, 87 - 102

Pre-processing feature selection for improved C&RT models for oral absorption.

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

Coping with unbalanced class data sets in oral absorption models.

Newby D. et al, (2013), J Chem Inf Model, 53, 461 - 474

The impact of training set data distributions for modelling of passive intestinal absorption.

Ghafourian T. et al, (2012), Int J Pharm, 436, 711 - 720

Include forthcoming?