Author

A. M. Afzal

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pharmacology & Toxicology· 2 Cell Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 3 Approach:Bayesian inference· 2 Assay:clinical cohort / trial· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

E. Semenova· 2 shared S. E. Lazic· 2 shared A. Bender· 1 shared A. Hock· 1 shared B. Zhang· 1 shared C. H. G. Allen· 1 shared D. P. Williams· 1 shared F. Svensson· 1 shared

Activity by Year

2020-2020 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersCell Biology

E. Semenova

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Author profile →

3 papers

Recent·Most cited

Flexible fitting of PROTAC concentration-response curves with changepoint Gaussian Processes

E. Semenova, M. L. Guerriero, B. Zhang, A. Hock, P. Hopcroft, G. Kadamur, A. M. Afzal, S. E. Lazic

This paper introduces a Bayesian changepoint Gaussian Processes model to automatically fit PROTAC concentration-response curves, enabling accurate parameter estimation and compound ranking without manual intervention.

bioRxiv · Nov 13, 2020Cell Biology

Systematic analysis of protein targets associated with adverse events of drugs from clinical trials and post-marketing reports

I. A. Smit, A. M. Afzal, C. H. G. Allen, F. Svensson, T. Hanser, A. Bender

This study systematically analyzes links between drug off-target proteins and adverse events using clinical trial and post-marketing data to improve safety profiling.

bioRxiv · Jun 12, 2020Pharmacology & Toxicology

A Bayesian neural network for toxicity prediction

E. Semenova, D. P. Williams, A. M. Afzal, S. E. Lazic

This paper introduces a Bayesian neural network for toxicity prediction, showing it outperforms traditional models in capturing ordinal data uncertainty.

bioRxiv · Apr 28, 2020Pharmacology & Toxicology