Joerg Wichard

Cracow University of Technology — Poland

Computer Science · Physical Sciences

25h-index2.3kcitations61works4.52yr avg
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Research Topics

Computational Drug Discovery Methods(30), Carcinogens and Genotoxicity Assessment(13), Neural Networks and Applications(12), Time Series Analysis and Forecasting(7), Machine Learning in Materials Science(6)

Publications61 total

Large-scale experimental validation of phenotype-guided generative AI for de novo drug discovery
2025Open Access
Data-driven federated learning in drug discovery with knowledge distillation
Nature Machine Intelligence·2025· 16 cited
PretoxTM: a text mining system for extracting treatment-related findings from preclinical toxicology reports
Journal of Cheminformatics·2025· 2 citedOpen Access
Target-Aware Drug Activity Model: A Deep Learning Approach to Virtual HTS
Lecture notes in computer science·2024
Cell morphology-guided <i>de novo</i> hit design by conditioning GANs on phenotypic image features
Digital Discovery·2022· 19 citedOpen Access
In silico approaches in organ toxicity hazard assessment: Current status and future needs in predicting liver toxicity
Computational Toxicology·2021· 41 citedOpen Access
Aspects of transition cow metabolomics—Part I: Effects of a metaphylactic butaphosphan and cyanocobalamin treatment on the metabolome in liver, blood, and urine in cows with different liver metabotypes
Journal of Dairy Science·2021· 22 citedOpen Access
Aspects of transition cow metabolomics—Part III: Alterations in the metabolome of liver and blood throughout the transition period in cows with different liver metabotypes
Journal of Dairy Science·2021· 25 citedOpen Access
Bayer’s in silico ADMET platform: a journey of machine learning over the past two decades
Drug Discovery Today·2020· 206 citedOpen Access
Skin sensitization in silico protocol
Regulatory Toxicology and Pharmacology·2020· 44 citedOpen Access
Exploring the Use of Compound-Induced Transcriptomic Data Generated From Cell Lines to Predict Compound Activity Toward Molecular Targets
Frontiers in Chemistry·2020· 34 citedOpen Access
Cell Morphology-Guided De Novo Hit Design by Conditioning Generative Adversarial Networks on Phenotypic Image Features
2020· 3 citedOpen Access
Cell Morphology-Guided De Novo Hit Design by Conditioning Generative Adversarial Networks on Phenotypic Image Features
2020· 7 citedOpen Access
De novo generation of hit-like molecules from gene expression signatures using artificial intelligence
Nature Communications·2020· 392 citedOpen Access
Genotoxicity Assessment of Drug Metabolites in the Context of MIST and Beyond
Chemical Research in Toxicology·2019· 11 cited
Chemical in vitro bioactivity profiles are not informative about the long-term in vivo endocrine mediated toxicity
Computational Toxicology·2019· 8 cited
Genetic toxicology in silico protocol
Regulatory Toxicology and Pharmacology·2019· 78 citedOpen Access
Principles and procedures for handling out-of-domain and indeterminate results as part of ICH M7 recommended (Q)SAR analyses
Regulatory Toxicology and Pharmacology·2018· 31 citedOpen Access
De Novo Generation of Hit-like Molecules from Gene Expression Signatures Using Artificial Intelligence
2018· 6 citedOpen Access
De Novo Generation of Hit-like Molecules from Gene Expression Signatures Using Artificial Intelligence
2018· 13 citedOpen Access
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Frequent Co-authors

Alexander Amberg(13), Susanne Glowienke(10), Wolfgang Muster(10), Alessandro Brigo(9), Robert A. Jolly(9), Michelle Kenyon(9), Maciej Ogorzałek(9), Glenn J. Myatt(8), Kevin P. Cross(8), Christian Merkwirth(8), David Rouquié(7), Lennart T. Anger(7), Lisa Beilke(7), Laura Custer(7), Krista L. Dobo(7), James Harvey(7), Masamitsu Honma(7), Naomi L. Kruhlak(7), Lidiya Stavitskaya(7), Andrew Teasdale(7)