Create new account

We were cited

Publications

Books / Proceedings / Conference presentations

We were cited

-------

We were cited:

Doki K, Neuhoff S, Rostami-Hodjegan A, Homma M.Assessing potential drug-drug interactions between dabigatran etexilate and a P-gp inhibitor in renal impairment population using PBPK modeling. CPT: Pharmacometrics and Systems Pharmacology, 2019; doi:10.1002/psp4.12382.

Xie F, Gu J. Computational methods and applications for quantitative systems pharmacology. Quantitative Biology, 2019; doi:https://doi.org/10.1007/s40484-018-0161-6.

Ellison CA et al. Challenges in working towards an internal threshold of toxicological concern (iTTC) for use in the safety assessment of cosmetics: Discussions from the Cosmetics Europe iTTC Working Group workshop. Regulatory Toxicology and Pharmacology, 2019; 103:63-72.

Wang R et al. An integrated characterization of contractile, electrophysiological, and structural cardiotoxicity of Sophora tonkinensis Gapnep. in human pluripotent stem cell-derived cardiomyocytes. Stem Cell Research & Therapy, 2019; 10:20.

Polasek TM et al. What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing. The AAPS Journal, 2019; 21:17.

Chastang A et al. Impact of hospital pharmacist interventions on the combination of citalopram or escitalopram with other QT-prolonging drugs. International Journal of Clinical Pharmacy, 2019; doi:https://doi.org/10.1007/s11096-018-0724-7.

Christophe B, Crumb W. Impact of disease state on arrhythmic event detection by action potential modelling in cardiac safety pharmacology. Journal of Pharmacological and Toxicological Methods, 2019; 96:15-26.

Polasek TM. Virtual twins for precision dosing in clinical drug development. Australasian Biotechnology, 2018; 28:42-43.

Liu S, Zhang R, Lu X. The Impact of Individuals' Attitudes Toward Health Websites on Their Perceived Quality of Health Information: An Empirical Study. Telemedicine and e-Health, 2018; doi:https://doi.org/10.1089/tmj.2018.0217.

Brouillette J, Cyr S, Fiset C. Mechanisms of Arrhythmia and Sudden Cardiac Death in Patients with Human Immunodeficiency Virus Infection. Canadian Journal of Cardiology, 2018; doihttps://doi.org/10.1016/j.cjca.2018.12.015.

Melillo N, Aarons L, Magni P, Darwich AS. Variance based global sensitivity analysis of physiologically based pharmacokinetic absorption models for BCS I–IV drugs. Journal of Pharmacokinetics and Pharmacodynamics, 2018; doi:https://doi.org/10.1007/s10928-018-9615-8.

Kowalska M, Fijałkowski Ł, Nowaczyk A. The Biological Activity Assessment of Potential Drugs Acting on Cardiovascular System Using Lipinski and Veber Rules. Journal of Education, Health and Sport, 2018; doi:http://dx.doi.org/10.5281/zenodo.2066519.

Polasek TM, Rayner CR, Peck RW, Rowland A, Kimko H, Rostami-Hodjegan A. Toward Dynamic Prescribing Information: Codevelopment of Companion Model‐Informed Precision Dosing Tools in Drug Development. Clinical Pharmacology in Drug Development, 2018; doi:https://doi.org/10.1002/cpdd.638.

Su X, Jiang X, Zhang S, Chen M. LSTM Power Mid-Term Power Load Forecasting with Meteorological Factors. In: Zhao Y., Wu TY., Chang TH., Pan JS., Jain L. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. VTCA 2018. Smart Innovation, Systems and Technologies, 2019; vol 128. Springer, Cham.

Corpas-López V et al. A nanodelivered Vorinostat derivative is a promising oral compound for the treatment of visceral leishmaniasis. Pharmacological Research, 2018; doi:https://doi.org/10.1016/j.phrs.2018.11.039.

Conner TM, Reed RC, Zhang T. A Physiologically Based Pharmacokinetic Model for Optimally Profiling Lamotrigine Disposition and Drug–Drug Interactions. European Journal of Drug Metabolism and Pharmacokinetics, 2018; doi:https://doi.org/10.1007/s13318-018-0532-4.

Nothnagel L et al. Predictive PBPK modeling as a tool in the formulation of the drug candidate TMP-001. European Journal of Pharmaceutics and Biopharmaceutics, 2018; doi:https://doi.org/10.1016/j.ejpb.2018.11.012.

Shi J-Y et al. TMFUF: a triple matrix factorization-based unified framework for predicting comprehensive drug-drug interactions of new drugs. BMC Bioinformatics, 2018; doi: 19 (Suppl 14) :411.

Wojkowska-Mach et al. Antibiotic consumption and antimicrobial resistance in Poland; findings and implications. Antimicrobial Resistance & Infection Control, 2018; doi: https://doi.org/10.1186/s13756-018-0428-8.

Vaidhyanathan S et al. Bioequivalence comparison of pediatric Dasatinib formulations and elucidation of absorption mechanisms through integrated PBPK modeling. Journal of Pharmaceutical Sciences, 2018; doi: https://doi.org/10.1016/j.xphs.2018.11.005.

Fernandes FM et al. Assessment of the risk of QT-interval prolongation associated with potential drug-drug interactions in patients admitted to Intensive Care Units. Saudi Pharmaceutical Journal, 2018; doi: https://doi.org/10.1016/j.jsps.2018.11.003.

Svorc P. Chronobiology of Acid-Base Balance under General Anesthesia in Rat Model. IntechOpen, 2018; doi: 10.5772/intechopen.75174.

Bhattacharya P, Saha A, Basak S. Discovery of nano-piperolactam a: A non-steroidal contraceptive lead acting through down-regulation of interleukins. Nanomedicine: Nanotechnology, Biology and Medicine, 2018; doi:https://doi.org/10.1016/j.nano.2018.10.011.

Szafraniec J et al. Molecular Disorder of Bicalutamide-Amorphous Solid Dispersions Obtained by Solvent Methods. Pharmaceutics, 2018; 10:194.

Munawar S et al. Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities. Frontiers in Pharmacology, 2018; 9:1035.

Rhee S-j et al. Physiologically Based Pharmacokinetic Modeling of Fimasartan, Amlodipine, and Hydrochlorothiazide for the Investigation of Drug–Drug Interaction Potentials. Pharmaceutical Research, 2018; 35:236.

Savoji H et al. Cardiovascular disease models: A game changing paradigm in drug discovery and screening. Biomaterials, 2018; doi:https://doi.org/10.1016/j.biomaterials.2018.09.036.

Zakaria ZZ et al. Using Zebrafish for Investigating the Molecular Mechanisms of Drug-Induced Cardiotoxicity. BioMed Research International, 2018; Article ID 1642684.

Pentafragka C, Symillides M, McAllister M, Dressman J, Vertzoni M, Reppas C. The impact of food intake on the luminal environment and performance of oral drug products with a view to in vitro and in silico simulations: a PEARRL review. Journal of Pharmacy and Pharmacology, 2018; doi:https://doi.org/10.1111/jphp.12999.

Izumi-Nakaseko H et al. Application of human induced pluripotent stem cell-derived cardiomyocytes sheets with microelectrode array system to estimate antiarrhythmic properties of multi-ion channel blockers. Journal of Pharmacological Sciences, 2018; 137:372-378.

Goto A et al. Analysis of torsadogenic and pharmacokinetic profile of E-4031 in dogs bridging the gap of information between in vitro proarrhythmia assay and clinical observation in human subjects. Journal of Pharmacological Sciences, 2018; 137(2):237-240.

Guiastrennec B. Sonne DP, Bergstrand M, Vilsbøll T, Knop FK, Karlsson MO. Model- Based Prediction of Plasma Concentration and Enterohepatic Circulation of Total Bile Acids in Humans. CPT: Pharmacometrics & Systems Pharmacology, 2018; doi:10.1002/psp4.12325.

Li Z et al. Assessment of an In Silico Mechanistic Model for Proarrhythmia Risk Prediction Under the CiPA Initiative . Clinical Pharmacology & Therapeutics, 2018; doi:https://doi.org/10.1002/cpt.1184.

Stader F, Siccardi M, Battegay M, Kinvig H, Penny MA, Marzolini C. Repository Describing an Aging Population to Inform Physiologically Based Pharmacokinetic Models Considering Anatomical, Physiological, and Biological Age-Dependent Changes. Clinical Pharmacokinetics, 2018; doi:https://doi.org/10.1007/s40262-018-0709-7.

Shi J-Y, Shang X-Q, Gao K, Zhang S-W, Yiu S-M. An Integrated Local Classification Model of Predicting Drug-Drug Interactions via Dempster-Shafer Theory of Evidence. Scientific Reports, 2018; 8:11829.

Birhanu G. Dexamethasone loaded multi-layer poly-l-lactic acid/pluronic P123 composite electrospun nanofiber scaffolds for bone tissue engineering and drug delivery. Pharmaceutical Development and Technology , 2018; https://doi.org/10.1080/10837450.2018.1481429.

Kedzierska E, Dabkowska L, Krzanowski T, Gibula E, Orzelska-Gorka J, Wujec M. New drugs - from necessity to delivery. Current Issues in Pharmacy and Medical Sciences, 2018; 31:69-75.

Urooj S et al. Assessment of sustained release matrix tablets for quetiapine fumarate: in vitro studies. Acta Poloniae Pharmaceutica - Drug Research, 2018; 75:107-117.

Awad A, Trenfield SJ, Gaisford S, Basit AW. 3D printed medicines: A new branch of digital healthcare. European Journal of Pharmaceutics and Biopharmaceutics, 2018; https://doi.org/10.1016/j.ijpharm.2018.07.024.

Lozoya-Agullo I, González-Álvarez I, Merino-Sanjuán M, Bermejo M, González-Álvarez M. Preclinical Models for Colonic Absorption, Application to Controlled Release Formulation Development. European Journal of Pharmaceutics and Biopharmaceutics, 2018; https://doi.org/10.1016/j.ejpb.2018.07.008.

Hatton GB, Madla CM, Rabbie SC, Basit AW. All disease begins in the gut: Influence of gastrointestinal disorders and surgery on oral drug performance. International Journal of Pharmaceutics, 2018; https://doi.org/10.1016/j.ijpharm.2018.06.054.

Perryman Al, Patel JS, Russo R, Singleton E, Connell N, Ekins S, Freundlich JS. Naïve Bayesian Models for Vero Cell Cytotoxicity. Pharmaceutical Research, 2018; 35:170.

Muszkiewicz A, Liu X, Bueno-Orovio A, Lawson BAJ, Burrage K, Casadei B, Rodriguez B. From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study. American Journal of Physiology-Heart and Circulatory Physiology, 2018; 314:H895-H916.

Hunta S, Yooyativong T, Aunsri N. A Novel Integrated Action Crossing Method for Drug-Drug Interaction Prediction in Non-Communicable Diseases. Computer Methods and Programs in Biomedicine, 2018; doi: https://doi.org/10.1016/j.cmpb.2018.06.013.

Alqahtani S, Bukhari I, Albassam A, Alenazi M. An update on the potential role of intestinal first-pass metabolism for the prediction of drug–drug interactions: the role of PBPK modeling. Expert Opinion on Drug Metabolism & Toxicology, 2018; 14:625-634.

Martinez-Prat L et al. Comparison of Serological Biomarkers in Rheumatoid Arthritis and Their Combination to Improve Diagnostic Performance. Frontiers in Immunology, 2018; 1113.

Ravi G, Gupta Vishal N, Balamuralidhara V. Rivastigmine Tartrate Solid Lipid Nanoparticles Loaded Transdermal Film: An In vivo study. Research Journal of Pharmacy and Technology, 2018; 11:227.

Nguyen PTT et al. Development of a Physiologically Based Pharmacokinetic Model of Ethionamide in the Pediatric Population by Integrating Flavin-Containing Monooxygenase 3 Maturational Changes Over Time. The Journal of Clinical Pharmacology, 2018; https://doi.org/10.1002/jcph.1133.

Yao Y, Toshimoto K, Kim S-J, Yoshikado T Sugiyama Y. Quantitative Analysis of Complex Drug-Drug Interactions between Cerivastatin and Metabolism/Transport Inhibitors Using Physiologically Based Pharmacokinetic Modeling. Drug Metabolism and Disposition, 2018; doi:https://doi.org/10.1124/dmd.117.079210 .

Pellett JD, Dwaraknath S, Nauka E, Dalziel G. Chapter 18 – Accelerated Predictive Stability (APS) Applications: Packaging Strategies for Controlling Dissolution Performance.[in:] Qiu F, and Scrivens G. Accelerated Predictive Stability. Fundamentals and Pharmaceutical Industry Practices. Elsevier Inc, 2018; 383-401.

Yellepeddi V, Rower J, Liu X, Kumar S, Rashid J, Sherwin CMT. State-of-the-Art Review on Physiologically Based Pharmacokinetic Modeling in Pediatric Drug Development. Clinical Pharmacokinetics, 2018; doi:https://doi.org/10.1007/s40262-018-0677-y.

Effinger A, O'Driscoll CM, McAllister M, Fotaki N. Impact of gastrointestinal disease states on oral drug absorption – implications for formulation design – a PEARRL review. Journal of Pharmacy and Pharmacology, 2018; doi:https://doi.org/10.1111/jphp.12928.

Yamazaki S, Loi C-M, Kimoto E, Costales C, Varma MV. Application of Physiologically Based Pharmacokinetic Modeling in Understanding Bosutinib Drug-Drug Interactions: Importance of Intestinal P-Glycoprotein. Drug Metabolism and Disposition, 2018; doi:https://doi.org/10.1124/dmd.118.080424.

Boland JW, Johnson M, Ferreira D, Berry DJ In silico (computed) modelling of doses and dosing regimens associated with morphine levels above international legal driving limits. Palliative Medicine, 2018; doi:https://doi.org/10.1177/0269216318773956.

Galbusera F, Niemeyer F, Seyfried M, Bassani T, Casaroli G, Kienle A, Wilke H-J Exploring the Potential of Generative Adversarial Networks for Synthesizing Radiological Images of the Spine to be Used in In Silico Trials. Frontiers in Bioengineering and Biotechnology, 2018; 6:53.

Rautio J, Meanwell NA, Di L, Hageman MJ The expanding role of prodrugs in contemporary drug design and development. Nature Reviews Drug Discovery, 2018; doi:10.1038/nrd.2018.46.

Cai C, Fang J, Guo P, Wang Q, Hong H, Moslehi J, Cheng F In Silico Pharmacoepidemiologic Evaluation of Drug-Induced Cardiovascular Complications using Combined Classifiers. Journal of Chemical Information and Modeling, 2018; doi:10.1021/acs.jcim.7b0064.

Turner JR et al.Drug‐induced Proarrhythmia and Torsade de Pointes: A Primer for Students and Practitioners of Medicine and Pharmacy. The Journal of Clinical Pharmacology, 2018; doi:10.1002/jcph.1129.

Krupa A, Tabor Z, Tarasiuk J, Strach B, Pociecha K, Wyska E, Wroński S, Łyszczarz E, Jachowicz R. The impact of polymers on 3D microstructure and controlled release of sildenafil citrate from hydrophilic matrices. European Journal of Pharmaceutical Sciences, 2018; In press.

Yu H, Mao K-T, Shi J-Y, Huang H, Chen Z, Dong K, Yiu S-M. Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization. BMC Systems Biology, 2018; 12(Suppl 1): 14.

Zakaria Z, Badhan RKS. The impact of CYP2B6 polymorphisms on the interactions of efavirenz with lumefantrine: Implications for paediatric antimalarial therapy. European Journal of Pharmaceutical Sciences, 2018; 119: 90-101.

Rowland A, van Dyk M, Hopkins AM, Mounzer R, Polasek TM, Rostami‐Hodjegan A, Sorich MJ. Physiologically‐based pharmacokinetic modelling to identify physiological and molecular characteristics driving variability in drug exposure. Clinical Pharmacology and Therapeutics, 2018; doi:https://doi.org/10.1002/cpt.1076.

Hens B, Talattof A, Paixão P, Bermejo M, Tsume Y, Löbenberg R,Amidon GL. Measuring the Impact of Gastrointestinal Variables on the Systemic Outcome of Two Suspensions of Posaconazole by a PBPK Model. The AAPS Journal, 2018; 20:57.

Kordbacheh E, Nazarian S, Sadeghi D, Hajizadeh A. An LTB-entrapped protein in PLGA nanoparticles preserves against enterotoxin of enterotoxigenic Escherichia coli. Iranian Journal of Basic Medical Sciences, 2018; 21: 517-524.

Romero L, Cano J, Gomis-Tena J, Trenor B, Sanz F, Pastor M, Saiz J. In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk. Journal of Chemical Information and Modeling, 2018; doi:10.1021/acs.jcim.7b00440.

Dudefoi W. Titanium dioxide particles in food: characterization, fate in digestive fluids and impact on human gut microbiota (Doctoral dissertation), 2017; Retrieved from www.theses.fr: 2017NANT4019.

Mikkelsen CR, Jornil JR, Andersen LV, Banner J, Hasselstrøm JB. Distribution of Eight QT-Prolonging Drugs and Their Main Metabolites Between Postmortem Cardiac Tissue and Blood Reveals Potential Pitfalls in Toxicological Interpretation. Journal of Analytical Toxicology, 2018; doi:https://doi.org/10.1093/jat/bky018.

Gwozdzinski K, Azarderakhsh S, Imirzalioglu C, Falgenhauer L, Chakraborty T. An improved medium for colistin susceptibility testing. Journal of Clinical Microbiology, 2018; doi:10.1128/JCM.01950-17.

Mortensen HM, Chamberlin J, Joubert B, Angrish M, Sipes N, Lee JS, Euling SY.Leveraging human genetic and adverse outcome pathway (AOP) data to inform susceptibility in human health risk assessment. Mammalian Genome, 2018; doi:https://doi.org/10.1007/s00335-018-9738-7.

Guiastrennec B. Mechanism-based modeling of biological processes involved in oral absorption (Doctoral dissertation), 2018; Retrieved from DiVA Database: diva2:1178146.

Kordbacheh E, Nazarian S, Hajizadeh A, Sadeghi D. Entrapment of LTB protein in alginate nanoparticles protects against Enterotoxigenic Escherichia coli. APMIS, 2018; doi: 10.1111/apm.12815.

Hasani HJ, Ganesan A, Ahmed M, Barakat KH. Effects of protein-protein interactions and ligand binding on the ion permeation in KCNQ1 potassium channel. PLoS ONE, 2018; doi: https://doi.org/10.1371/journal.pone.0191905.

Dan G-A et al. Antiarrhythmic drugs–clinical use and clinical decision making: a consensus document from the European Heart Rhythm Association (EHRA) and European Society of Cardiology (ESC) Working Group on Cardiovascular Pharmacology, endorsed by the Heart Rhythm Society (HRS), Asia-Pacific Heart Rhythm Society (APHRS) and International Society of Cardiovascular Pharmacotherapy (ISCP). EP Europace, 2018; doi:https://doi.org/10.1093/europace/eux373.

Bown HK, Bonn C, Yohe S, Yadav DB, Patapoff TW, Daugherty A, Mrsny RJ. In vitro model for predicting bioavailability of subcutaneously injected monoclonal antibodies. Journal of Controlled Release, 2018; 273: 13-20.

Başçiftçi F, Avuçlu E. An expert system design to diagnose cancer by using a new method reduced rule base. Computer Methods and Programs in Biomedicine, 2018; 157: 113-120.

Alves VM, Braga RC, and Andrade CH. Computational Approaches for Predicting hERG Activity, in Computational Toxicology: Risk Assessment for Chemicals (ed Ekins). John Wiley & Sons, Inc., Hoboken, NJ, USA, 2018; doi: 10.1002/9781119282594.ch3.

Zakaria Z, Badhan R. Development of a Region-Specific Physiologically Based Pharmacokinetic Brain Model to Assess Hippocampus and Frontal Cortex Pharmacokinetics. Pharmaceutics, 2018; 10(1): 14.

Johnson TN, Bonner JJ, Tucker GT, Turner DB, Jamei M. Development and application of a physiologically-based model of paediatric oral drug absorption. European Journal of Pharmaceutical Sciences, 2018; https://doi.org/10.1016/j.ejps.2018.01.009

Conner TM et al. Physiologically based pharmacokinetic modeling of disposition and drug-drug interactions for valproic acid and divalproex. European Journal of Pharmaceutical Sciences, 2018; 111: 465-481.

Castilho ECD, Reis AMM, Borges TL, Siqueira LDC, Miasso AI. Potential drug–drug interactions and polypharmacy in institutionalized elderly patients in a public hospital in BrazilJournal of Psychiatric and Mental Health Nursing, 2018; 25: 3-13.

Biffi A et al.  Antidepressants and the risk of arrhythmia in elderly affected by a previous cardiovascular disease: a real-life investigation from ItalyEuropean Journal of Clinical Pharmacology, 2018; 1(74): 119-129.

Kolanowski TJ, Antos CL, Guan K.  Making human cardiomyocytes up to date: Derivation, maturation state and perspectives. International Journal of Cardiology, 2017; 241: 379-386.

Fonseca JC and López PG.  Effect of compression force on critical quality attributes of immediate release tablets of furosemide. Revista Colombiana de Ciencias Químico - Farmacéuticas, 2017; 46(2): 235-255.

White WB, Hewitt LA, Mehdirad AA.  Impact of the Norepinephrine Prodrug Droxidopa on the QTc Interval in Healthy Individuals. Clinical Pharmacology in Drug Development, 2017; doi:10.1002/cpdd.393

Mallick P.  Utilizing in vitro transporter data in IVIVE-PBPK: an overview. ADMET and DMPK, 2017; 5(4): 201-211.

Muszkiewicz A, Liu X, Bueno-Orovio A, Lawson BAJ, Burrage K, Casadei B, Rodriguez B.  From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study. American Journal of Physiology-Heart and Circulatory Physiology, 2017; doi:https://doi.org/10.1152/ajpheart.00477.2017

van Dyk M, Rowland A.  Physiologically-based pharmacokinetic modeling as an approach to evaluate the effect of covariates and drug-drug interactions on variability in epidermal growth factor receptor kinase inhibitor exposure. Translational Cancer Research, 2017; doi:10.21037/tcr.2017.10.16

Lei CL, Wang K, Clerx M et al. Tailoring Mathematical Models to Stem-Cell Derived Cardiomyocyte Lines Can Improve Predictions of Drug-Induced Changes to Their ElectrophysiologyFrontiers in Physiology, 2017; 8: 986.

Passini E, Britton OJ, Lu HR, Rohrbacher J, Hermans AN, Gallacher DJ, Greig RJH, Bueno-Orovio A, Rodriguez B. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic CardiotoxicityFrontiers in Physiology, 2017; 8: 668.

Poluzzi E, Raschi E, Diemberger I, De Ponti F. Drug-Induced Arrhythmia: Bridging the Gap Between Pathophysiological Knowledge and Clinical PracticeDrug Safety, 2017; 40(6): 461-464.

van Hassselt JGC, Iyengar R. Systems pharmacology-based identification of pharmacogenomic determinants of adverse drug reactions using human iPSC-derived cell linesCurrent Opinion in Systems Biology, 2017; 4: 9-15.

Niederer SA, de Oliveira BL, Curtis MJ. The opportunities and challenges for biophysical modelling of beneficial and adverse drug actions on the heartCurrent Opinion in Systems Biology, 2017; 4: 29-34.

Parikh J, Gurev V, Rice JJ. Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct FeaturesFrontiers in Physiology, 2017; 8: 816.

McMillan B, Gavaghan DJ, Mirams GR. Early afterdepolarisation tendency as a simulated pro-arrhythmic risk indicatorToxicology Research, 2017; 6: 912-921.

Lane JD, Tinker A. Have the Findings from Clinical Risk Prediction and Trials Any Key Messages for Safety Pharmacology?Frontiers in Physiology, 2017; 8: 890.

Hartung T et al. Systems Toxicology: Real World Applications and OpportunitiesChemical Research in Toxicology, 2017; 30(4): 870-882.

Corsi C et al. Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patientsScientific Reports, 2017; 7: 42492.

Rao RT, Scherholz ML, Hartmanshenn C, Bae SA, Androulakis IP. On the analysis of complex biological supply chains: From process systems engineering to quantitative systems pharmacologyComputers & Chemical Engineering, 2017; 107: 100-110.

Li M, Ramos LG. Drug-Induced QT Prolongation And Torsades de PointesPharmacy and Therapeutics, 2017; 42(7): 473-477.

Meid AD et al.  Combinations of QTc-prolonging drugs: towards disentangling pharmacokinetic and pharmacodynamic effects in their potentially additive natureTherapeutic Advances in Psychopharmacology, 2017; 7(12): 251-264.

Benatar A. The Pediatric ElectrocardiogramAnnals of Cardiology and Cardiovascular Diseases, 2017; 2(1): 1009.

Britton OJ, Abi-Gerges N, Page G, Ghetti A, Miller PE, Rodriguez B. Quantitative Comparison of Effects of Dofetilide, Sotalol, Quinidine, and Verapamil between Human Ex vivo Trabeculae and In silico Ventricular Models Incorporating Inter-Individual Action Potential VariabilityFrontiers in Physiology, 2017; 8: 597.

Izumi-Nakaseko H, Nakamura Y, Wada T, Ando K, Kanda Y, Sekino Y, Sugiyama A. Characterization of human iPS cell-derived cardiomyocyte sheets as a model to detect drug-induced conduction disturbanceThe Journal of Toxicological Sciences, 2017; 42(2): 183-192.

Britton OJ, Bueno-Orovio A, Virág L, Varró A, Rodriguez B. The Electrogenic Na+/K+ Pump Is a Key Determinant of Repolarization Abnormality Susceptibility in Human Ventricular Cardiomyocytes: A Population-Based Simulation StudyFrontiers in Physiology, 2017; 8: 278.

Ritchie HE, Oakes DJ, Kennedy D, Polson JW. Early Gestational Hypoxia and Adverse Developmental OutcomesBirth Defects Research, 2017; 109(17): 1358–1376.

Gueta I, Loebstein R, Markovits N, Kamari Y, Halkin H, Livni G, Yarden-Bilavsky H. Voriconazole-induced QT prolongation among hemato-oncologic patients: clinical characteristics and risk factorsEuropean Journal of Clinical Pharmacology, 2017; 73(9): 1181-1185.

Dobchev D, Karelson M. Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?Expert Opinion on Drug Discovery , 2016; 11(7): 627-639.

Soneson C, Robinson MD. iCOBRA: open, reproducible, standardized and live method benchmarkingNature Methods, 2016; 13(4): 283.

Danielsson B, Collin J, Bergman GJ, Borg N, Salmi P, Fastbom J. Antidepressants and antipsychotics classified with torsades de pointes arrhythmia risk and mortality in older adults - a Swedish nationwide studyBritish Journal of Clinical Pharmacology, 2016; 81(4): 773-783.

Kissoyan KAB, Bazzi W, Hadi U, Matar GM. The inhibition of Pseudomonas aeruginosa biofilm formation by micafungin and the enhancement of antimicrobial agent effectiveness in BALB/c miceBiofouling, 2016; 32(7): 779-786.

Gotta V, Yu Z, Cools F, van Ammel K, Gallacher DJ, Visser SAG, Sannajust F, Morissette P, Danhof M, van der Graaf PH. Application of a systems pharmacology model for translational prediction of hERG-mediated QTc prolongationPharmacology Research & Perspectives, 2016; 4(6): e00270.

Cooper BM, Putnam D. Polymers for siRNA Delivery: A Critical Assessment of Current Technology Prospects for Clinical ApplicationACS Biomaterials Science & Engineering, 2016; 2(11): 1837-1850.

Kügler P. Early Afterdepolarizations with Growing Amplitudes via Delayed Subcritical Hopf Bifurcations and Unstable Manifolds of Saddle Foci in Cardiac Action Potential DynamicsPLoS ONE, 2016; 11(3): e0151178.

Lin J, Li H-X, Qin L, Du Z-H, Xia J, Li J-L. A novel mechanism underlies atrazine toxicity in quails (Coturnix Coturnix coturnix): triggering ionic disorder via disruption of ATPasesOncotarget, 2016; 51(7): 83880-83892.

Lin J, Li H-X, Xia J, Li X-N, Jiang X-Q, Zhu S-Y, Ge J, Li J-L. The chemopreventive potential of lycopene against atrazine-induced cardiotoxicity: modulation of ionic homeostasisScientific Reports, 2016; 6: 24855.

Terker AS, Zhang C, Erspamer KJ, Gamba G, Yang C-L, Ellison DH. Unique chloride-sensing properties of WNK4 permit the distal nephron to modulate potassium homeostasisKidney International, 2016; 89(1): 127-134.

Templeton I, Ravenstijn P, Sensenhauser C, Snoeys J. A physiologically based pharmacokinetic modeling approach to predict drug–drug interactions between domperidone and inhibitors of CYP3A4Biopharmaceutics and Drug Disposition, 2016; 37(1): 15-27.

Knight-Schrijver VR, Chelliah V, Cucurull-Sanchez L, Le Novère N. The promises of quantitative systems pharmacology modelling for drug developmentComputational and Structural Biotechnology Journal, 2016; 14: 363-370.

Trayanova NA, Chang KC. How computer simulations of the human heart can improve anti-arrhythmia therapyThe Journal of Physiology, 2016; 594(9): 2483-2502.

Gawehn E, Hiss JA, Schneider G. Deep Learning in Drug DiscoveryMolecular Informatics, 2016; 35(1): 3-14.

Sánchez-López VA, Brennan-Bourdon LM, Rincón-Sánchez AR, Islas-Carbajal MC, Navarro-Ruíz A, Huerta-Olvera SG. Prevalence of Potential Drug-Drug Interactions in Hospitalized Surgical PatientsJournal of Pharmacy and Pharmacology, 2016; 4: 658-666.

Le Guennec J-Y et al. Inter-individual variability and modeling of electrical activity: a possible new approach to explore cardiac safety?Scientific Reports, 2016; Article number: 37948.

Didziapetris R, Lanevskij K. Compilation and physicochemical classification analysis of a diverse hERG inhibition databaseJournal of Computer-Aided Molecular Design, 2016; Article First Online: 25 October 2016.

Turner JR et al. Postmarketing Cardiovascular Safety ConsiderationsTurner JR, Karnad DR, Kothari S (eds): Cardiovascular Safety in Drug Development and Therapeutic Use. Switzerland, Springer, 2017.

Muszkiewicz A et al. Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigmProgress in Biophysics and Molecular Biology, 2016; Vol. 173, Issue 19: 2819-2832.

Dubois VFS et al. Pharmacokinetic–pharmacodynamic modelling of drug-induced QTc interval prolongation in man: prediction from in vitro human ether-à-go-go-related gene binding and functional inhibition assays and conscious dog studiesBritish Journal of Pharmacology, 2016; Vol. 173, Issue 19: 2819-2832.

Patlewicz G, Fitzpatrick JM. Current and Future Perspectives on the Development, Evaluation, and Application of in Silico Approaches for Predicting ToxicityChemical Research in Toxicology, 2016; Vol. 29: 438-451.

Sasaoka S, et al. Time-to-Onset Analysis of Drug-Induced Long QT Syndrome Based on a Spontaneous Reporting System for Adverse Drug Events PLOS One, 2016; Published Online: 10 October 2016.

Izumi-Nakaseko H, et al. Assessment of Safety Margin of an Antipsychotic Drug Haloperidol for Torsade de Pointes Using the Chronic Atrioventricular Block Dogs Cardiovascular Toxicology, 2016; First Online: 13 October 2016.

Korur A, et al. QTc prolongation during peripheral stem cell apheresis in healthy volunteers Journal of Clinical Apheresis, 2016; First Published Online: 20 August 2016.

George CH, et al. Pleiotropic mechanisms of action of perhexiline in heart failureExpert Opinion on Therapeutic Patents, 2016; Vol. 26 Issue 9: 1049-1059.

Orsolini L, et al. An update of safety of clinically used atypical antipsychotics Expert Opinion on Drug Safety, 2016; In press, accepted for publication.

Colatsky T, et al. The Comprehensive in Vitro Proarrhythmia Assay (CiPA) initiative - Update on progress Journal of Pharmacological and Toxicological Methods, 2016; In press, accepted for publication.

Nomura F, et al. Predictive lethal proarrhythmic risk evaluation using a closed-loop-circuit cell network with human induced pluripotent stem cells derived cardiomyocytes Japanese Journal of Applied Physics, 2016; In press, accepted for publication.

Page G, et al. Human ex-vivo action potential model for pro-arrhythmia risk assessment Journal of Pharmaceutical and Toxicological Methods, 2016; In press, accepted for publication.

Trame MN, et al. Systems pharmacology to predict drug safety in drug development European Journal of Pharmaceutical Sciences, 2016; In press, accepted for publication.

Blaauboer BJ, et al. Considering new methodologies in strategies for safety assessment of foods and food ingredients Food and Chemical Toxicology, 2016; 91:19–35.

Fujita H, et al. Sudden Cardiac Death (SCD) Prediction based on Nonlinear Heart Rate Variability Features and SCD Index Applied Soft Computing, 2016: [Epub ahead of print].

Picones A, et al. Contribution of Automated Technologies to Ion Channel Drug Discovery Advances in Protein Chemistry and Structural Biology, 2016: [Epub ahead of print].

Davies MR, et al. Recent developments in using mechanistic cardiac modelling for drug safety evaluation Drug Discovery Today, 2016: 21(6): 924-938.

Gintant G, et al. Evolution of strategies to improve preclinical cardiac safety testing. Nature Reviews Drug Discovery, 2016: [Epub ahead of print].

Chavan S, et al. A k-nearest neighbor classification of hERG K+ channel blockers. Journal of Computer-Aided Molecular Design, 2016; pp 1-8 First online: 10 February 2016.

Bergenholm L, et al. PKPD modelling of PR and QRS intervals in conscious dogs using standard safety pharmacology data. Journal of Pharmacological and Toxicological Methods, 2016; 79: 34–44.

Zhang C, et al. In Silico Prediction of hERG Potassium Channel Blockage by Chemical Category ApproachesToxicological Research, 2016; accepted for publication.

Schyman P, et al. A General Purpose 2D and 3D Similarity Approach to Identify hERG BlockersJChemInfModel, 2016; accepted for publication.

Poulin P. A Paradigm Shift in Pharmacokinetic–Pharmacodynamic (PKPD) Modeling: Rule of Thumb for Estimating Free Drug Level in Tissue Compared with Plasma to Guide Drug DesignJournal of Pharmaceutical Sciences, 2015; Vol.104 No.7: 2359-2368.

Salloum NA, et al. Assessment of combination therapy in BALB/c mice injected with carbapenem-resistant Enterobacteriaceae strainsFrontiers in Microbiology, 2015; Vol. 6:999.

Bentow C, et al. Clinical performance evaluation of a novel, automated chemiluminescent immunoassay, QUANTA Flash CTD Screen Plus. Immunologic Research, 2015; Vol. 61, Issue1, pp: 110-116.

Weir MR, Espaillat R. Clinical perspectives on the rationale for potassium supplementationPostgraduate Medicine, 2015; Vol. 127, No. 5,pp: 539-548.

Youssef AJ, et al. Drug-drug interactions in pharmacologic management of gastroparesisNeurogastroenterology & Motility, 2015; Article first published online: 8 JUN 2015.

Klinck J, et al. Predictors and outcome impact of perioperative serum sodium changes in a high-risk populationBr J Anaesth,  2015; 114 (4): 615-622.

Hardeland R. Melatonin and Circadian Oscillators in Aging - A Dynamic Approach to the Multiply Connected PlayersYashin AI, Jazwinski SM (eds): Aging and Health - A Systems Biology Perspective. Interdiscipl Top Gerontol. Basel, Karger, 2015, vol 40, pp 128-140, 2015.

Stimers JR, et al. Overexpression of the Large-Conductance, Ca2+-Activated K+ (BK) Channel Shortens Action Potential Duration in HL-1 CardiomyocytesPLOSOne, 2015. Published: June 19, 2015.

Feric NT, Radisic M. Maturing human pluripotent stem cell-derived cardiomyocytes in human engineered cardiac tissuesAdvanced Drug Delivery Reviews, 2015. Available online 5 May 2015, In Press [Epub ahead of print]

De Mieri M. et al. hERG Channel Inhibitory Daphnane Diterpenoid Orthoesters and Polycephalones A and B with Unprecedented Skeletons from Gnidia polycephalaJNatProd, 2015. [Epub ahead of print]

Du K. et al. HPLC-Based Activity Profiling for hERG Channel Inhibitors in the South African Medicinal Plant Galenia africanaPlanta Med, 2015 Apr 29. [Epub ahead of print]

Vicente J. et al. Comprehensive T wave Morphology Assessment in a Randomized Clinical Study of Dofetilide, Quinidine, Ranolazine, and VerapamilJAHA, 2015; 13(4).

Katagi J, et al. Why Can dl-Sotalol Prolong the QT Interval In Vivo Despite Its Weak Inhibitory Effect on hERG K+ Channels In Vitro? Electrophysiological and Pharmacokinetic Analysis with the Halothane-Anesthetized Guinea Pig ModelCardiovascular Toxicology, 2015, in press.

Collins TA, et al. Modeling and Simulation Approaches for Cardiovascular Function and Their Role in Safety AssessmentCPT:PSP, 2015, 4e18.

Villoutreix BO, Taboureau O. Computational investigations of hERG channel blockers: New insights and current predictive modelsAdvanced Drug Delivery Reviews, 2015, in press.

Gotta V, et al. Sensitivity of pharmacokinetic–pharmacodynamic analysis for detecting small magnitudes of QTc prolongation in preclinical safety testingJournal of Pharmacological and Toxicological Methods, 2015;72:1-10.

Torres PJ. A Model for Cell Volume RegulationMathematical Models with Singularities. Atlantis Briefs in Differential Equations, 2015; 1:107-112.

Kauthale RR, et al. Assessment of temperature-induced hERG channel blockade variation by drugsJournal of Applied Toxicology, 2014; EarlyView: Accepted 20th August.

Luo F, et al. Molecular docking and molecular dynamics studies on the structure–activity relationship of fluoroquinolone for the HERG channelMolecular BioSystems, 2014;10:2863-2869.

Anwar-Mohamed A, et al. A human ether-á-go-go-related (hERG) ion channel atomistic model generated by long supercomputer molecular dynamics simulations and its use in predicting drug cardiotoxicityToxicology Letters, 2014;230(3):382-392.

Keramati A, et al. Addressing churn prediction problem with Meta-heuristic, Machine learning, Neural Network and data mining techniques: a case study of a telecommunication companyMETAHEURISTICS AND ENGINEERING Proceedings ofthe 15th EU/ME Workshop, Bilecik S¸ eyh Edebali University, 2014 ISBN 978-605-85313- 0-7.

Ferreiro FF, et al. In vivo arrhythmogenicity of the marine biotoxin azaspiracid‑2 in ratsArchives of Toxicology, 2014;88(2):425-434.

Yuan Y. et al. The virtual heart as a platform for screening drug cardiotoxicityBritish Journal of Pharmacology, 2014; accepted for publication.

Danker T, Moeller C. Early identification of hERG liability in drug discovery programs by automated patch clamp. Frontiers in Pharmacology. 2014; 5 Article 203.

Nikolov NG, et al. hERG blocking potential of acids and zwitterions characterized by three thresholds for acidity, size and reactivity Bioorganic & Medicinal Chemistry. 2014;22(21):6004–6013.

Severi, S, Rodriguez B, Zaza A. Computational cardiac electrophysiology is moving towards translation medicine Europace. 2014;16(5):703-704.

Braga, RC et al. Tuning hERG Out: Antitarget QSAR Models for Drug Development Current Topics in Medicinal Chemistry. 2014;14(11):1399-1415.

Torres, PJ. Periodic oscillations of a model for membrane permeability with fluctuating environmental conditions. Journal of Mathematical Biology. 2014;[Epub ahead of a print].

Kaneko T, et al. On-chip in vitro cell-network pre-clinical cardiac toxicity using spatiotemporal human cardiomyocyte measurement on a chip. Scientific Reports. 2014, 4:4670.

Dallmann R, Brown SA, Gachon F. Chronopharmacology: New Insights and Therapeutic Implications. Annual Review of Pharmacology and Toxicology. 2014;54:339-361.

Ekins S. Progress in computational toxicology. Journal of Pharmacological and Toxicological Methods. 2014;69(2):115-140.

Sliwoski G. et al. Computational Methods in Drug Discovery. Pharmacological Reviews. 2014;66(1):334-395.

Czodrowski P. hERG Me Out. JChemInfModel. 2013; 53(9):2240-2251.

Xuan SY, et at. Classification of blocker and non-blocker of hERG potassium ion channel using a support vector machine. Science China Chemistry. 2013; 56(10):1413-1423.

Ferreiro SR, et at. In vivo arrhythmogenicity of the marine biotoxin azaspiracid-2 in rats. Arch Toxicol. 2013; published on line 23 June.

Nunes SS, et at. Biowire: a platform for maturation of human pluripotent stem cell-derived cardiomyocytes. Nature Methods. 2013; 10:781–787.

Wang S, Lia Y, Xua L, Lib D, Hou T. Recent Developments in Computational Prediction of hERG Blockage. Current Topics in Medicinal Chemistry. 2013;13.

Shah RR, Gussak I. Acquired (Drug-Induced) Long and Short QT Syndromes. 2013; in Gussak I and Antzelevitch C. Electrical Diseases of the Heart. Volume 2: Diagnosis and Treatment. London, UK: Springer-Verlag.

Di Veroli  GY, Davies MR, Zhang H, Abi-Gerges N, Boyett MR. High-throughput screening of drug-binding dynamics to HERG improves early drug safety assessment. Am J Physiol Heart Circ Physiol. 2013;304:H104-H117.

Danielsson BR. Maternal Toxicity. Teratogenicity Testing. Methods in Molecular Biology. 2013;947:311-325.

Miyara M et al. Clinical Phenotypes of Patients with Anti-Dfs70/Ledgf Antibodies in A Routine ANA Referral Cohort Clinical and Developmental Immunology. 2013; art. no. 703759.

Swart A, Burlingame RW, Gürtler I, Mahler M. Third generation anti-citrullinated peptide antibody assay is a sensitive marker in rheumatoid factor negative rheumatoid arthritis Clinica Chimica Acta. 2012;414:266-272.

Broccatelli F, Mannhold R, Moriconi A,Giuli S, Carosati E. QSAR modeling and data mining link torsades de pointes risk to the interplay of extent of metabolism, active transport, and hERG liability Molecular Pharmaceutics. 2012;9(8):2290-2301.

Wang S, Li Y, Wang J, Chen L, Zhang L, Yu H, Hou T. ADMET Evaluation in Drug Discovery. 12. Development of Binary Classification Models for Prediction of hERG Potassium Channel Blockage. Molecular Pharmaceutics. 2012;9:996-1010.

Kireeva N, Kuznetsov SL, Bykow AA, Tsivadze AY. Towards in silico identification of the human ether-a-go-go-related gene channel blockers: discriminative vs. generative classification models. SAR and QSAR in Environmental Research. 2012;24(2).

Mirams GR, Davies MR, Cui Y, Kohl P, Noble D. Application of cardiac electrophysiology simulations to pro-arrhythmic safety testing. British Journal of Pharmacology. 2012; 2012;167(5):932-945.

Eichenbaum G, Pugsley MK, Gallacher DJ, Towart R, McIntyre G, Shukla U, Davenport JM, Lu HR, Rohrbacher J, Hillsamer V. Role of Mixed Ion Channel Effects in the Cardiovascular Safety Assessment of the Novel Anti-MRSA Fluoroquinolone JNJ-Q2. British Journal of Pharmacology. 2012;Accepted Articles, Accepted manuscript online: 31 JAN 2012.

Gleeson MP, Modi S, Bender A, Robinson RL, Kirchmair J, Promkatkaew M, Hannongbua S, Glen RC. The Challenges Involved in Modeling Toxicity Data In Silico: A Review. Current Pharmaceutical Design. 2012;18(9):1266-1291.

Tan Y, Chen Y, You Q, Sun H, Li M. Predicting the potency of hERG K+ channel inhibition by combining 3D-QSAR pharmacophore and 2D-QSAR models. Journal of Molecular Modeling. 2011;Published on line 10 June.

Su Z, Gintant G. Preclinical Drug Safety and Cardiac Ion Channel Screening. Heart Rate and Rhythm. 2011;Part 7:627-638.

Schuster AM, Glassmeier G, Bauer CK. Strong activation of erg1 K+ channel isoforms by NS1643 (1,3-bis-(2-hydroxy-5-trifluoromethylphenyl)-urea) in HEK-293 and CHO cells. Molecular Pharmacology. 2011; August 19:available online.

Church MK. Safety and efficacy of bilastine: a new H1-antihistamine for the treatment of allergic rhinoconjunctivitis and urticaria. Expert Opinion on Drug Safety. 2011;10(5):779-793.

Schramm A, Baburin I, Hering S, Hamburger M. HERG channel inhibitors in extracts of coptidis rhizoma. Planta Medica. 2011;77(7):692-697.

Taboureau O, Jørgensen FS. In silico Predictions of hERG Channel Blockers in Drug Discovery: From Ligand-Based and Target-Based Approaches to Systems Chemical Biology. Comb Chem High Throughput Screen. 2011;14(5):375-87.

Marchese Robinson RL, Glen RC, Mitchell JBO. Development and Comparison of hERG Blocker Classifiers: Assessment on Different Datasets Yields Markedly Different Results Molecular Informatics. 2011;30(5):443-458.

Obiol-Pardo C, Gomis-Tena J, Sanz F, Saiz J, Pastor M. A Multiscale Simulation System for the Prediction of Drug-Induced Cardiotoxicity. Journal of Chemical Information and Modeling. 2011;51(2):483-492.

Beyer BK, Chernoff N, Danielsson BR, et al. ILSI/HESI maternal toxicity workshop summary: maternal toxicity and its impact on study design and data interpretation. Birth Defects Research Part B - Developmental and Reproductive Toxicology. 2011;92(1):36-51.

Schmalhofer WA, Swensen AM, Thomas BS, et al. A Pharmacologically Validated, High-Capacity, Functional Thallium Flux Assay for the Human Ether-á-go-go Related Gene Potassium Channel. Assay and Drug Development Technologies. 2010;8(6):714-726

Huang XP, Mangano T, Hufeisen S, Setola V, Roth BL. Identification of human Ether-à-go-go related gene modulators by three screening platforms in an academic drug-discovery setting. Assay and Drug Development Technologies. 2010;8(6):727-42.

Sprous D.G., Palmer R.K., Swanson J.T., Lawless M. QSAR in the pharmaceutical research setting: QSAR models for broad, large problems. Curr. Top. Med. Chem. Current Topics in Medicinal Chemistry. 2010;10(6):619-637.

Sprous D, Palmer K. The T1R2/T1R3 Sweet Receptor and TRPM5 Ion Channel: Taste Targets with Therapeutic Potential. Progress in Molecular Biology and Translational Science. 2010;91:151-208.

Raschi E., De Ponti F., Ceccarini L., Recanatini M. HERG-related drug toxicity and models for predicting hERG liability and QT prolongation. Expert Opinion on Drug Metabolism and Toxicology. 2009;5(9):1005-1021.