All Stories

  1. Is deep learning having any impact on ADME/Tox?
  2. Machine learning in drug discovery
  3. New targets for HIV drug discovery
  4. Comparing different machine learning models for HIV whole cell and reverse transcriptase
  5. Investigating drug of abuse immunoassay cross reactivity of vilazodone and metabolites.
  6. Industrializing enzyme replacement therapy development
  7. Machine learning for Ebola drug discovery
  8. Using machine learning for S. Aureus drug discovery
  9. Halogen Substitution Influences Ketamine Metabolism by Cytochrome P450 2B6: In Vitro and Computational Approaches
  10. An inhibitor for Mtb KasA that binds the active site twice
  11. Repurposing for neglected diseases
  12. A rapid method for estimation of the efficacy of potential antimicrobials in humans and animals by agar diffusion assay
  13. Characterization of new, efficient Mycobacterium tuberculosis topoisomerase-I inhibitors and their interaction with human ABC multidrug transporters
  14. Pyronaridine shows in vitro synergy with rifampicin against M. tuberculosis.
  15. Comparing Machine learning methods with Estrogen receptor data
  16. Families are changing rare disease research (for the better)
  17. Public Cytotoxicity Bayesian models
  18. Organic Cation Transporter 2 machine learning models
  19. A review on Zika drug discovery.
  20. Comparing Machine learning methods with Tuberculosis in vitro data
  21. A review using PubMed of drug repurposing
  22. Computational Toxicology
  23. Gaps and opportunities in MPS/ML for small rare disease companies to address
  24. Cheminformatics in a Clinical Setting
  25. Open Science Data Repository for Toxicology
  26. Developing Next Generation Tools for Computational Toxicology
  27. Accessible Machine Learning Approaches for Toxicology
  28. Data mining HTS data using machine learning
  29. Finding an old drug that works against ebola
  30. Does deep learning work with in vitro drug discovery datasets
  31. Molecular dynamics simulations of the Zika virus NS3 helicase.
  32. Applying a machine learning model for metabolic stability
  33. Online networking, data sharing and research activity distribution tools for scientists
  34. Sharing Models for Cost Effectiveness
  35. Multi targeting PyrG and PanK in TB
  36. The anti HIV drug inhibits the α7-Nicotinic acetylcholine receptor
  37. Funding TB research
  38. TB Topo I machine learning
  39. Summary of EU funded TB drug discovery
  40. Economies of scale for rare disease R&D
  41. Machine learning models identify molecules active against the Ebola virus in vitro
  42. How our approach for Sanfilippo syndrome could be a prototype for industrializing rare disease drug discovery and development
  43. Development of new antibiotics for treatment of drug resistant Tuberculosis
  44. CDD for MM4TB
  45. OpenZika
  46. TB drug discovery
  47. Green chemistry mobile apps
  48. Anyone can translate ideas to therapies
  49. Deep learning and Pharmaceutical R&D
  50. Illustrating and homology modeling the proteins of the Zika virus
  51. Predicting antitubercular activity in the mouse model
  52. MATE1 structure activity relationships
  53. Finding Mtb ThyX inhibitors
  54. Modeling the proteins in the Zika virus
  55. Semi quantitative open source Bayesian models
  56. Can Open Drug Discovery efforts contribute to a cure for the Zika Virus?
  57. a small company for Sanfilippo syndrome
  58. MPSIIID enzyme replacement therapy
  59. Identifying Ebola virus inhibitors using machine learning
  60. Small molecule bioactivity databases
  61. Small companies focused on rare and neglected diseases
  62. understanding error with different dispensing tools
  63. understanding error with different dispensing tools
  64. machine learning to predict synergy
  65. Mtb pharmacophores and drug discovery
  66. Identifying Ebola virus inhibitors using machine learning
  67. Kelch Domain of Gigaxonin Interacts with Intermediate Filament Proteins Affected in Giant Axonal Neuropathy
  68. Mouse Liver Microsomes models
  69. simple proxies for enthalpy and entropy
  70. Mobile transporter models
  71. Addressing the next viral outbreak
  72. Thiophenecarboxamide Derivatives Activated by EthA Kill Mycobacterium tuberculosis by Inhibiting the CTP Synthetase PyrG
  73. Green electronic lab notebook
  74. Identifying new compounds for Chagas disease
  75. Creating open source Bayesian models with a big dataset
  76. Using open source Bayesian models for drug discovery
  77. Optimizing the metabolic stability of an antitubercular
  78. Computational drug-drug interaction prediction
  79. Fragment-like inhibitors of InhA
  80. Publishing chemistry data in a way that allows computers to actually use it
  81. Repurposing Approved drugs for Ebola
  82. How do we fight the next pathogen we discover?
  83. A review of Charcot-Marie-Tooth research
  84. drugs for Ebola
  85. small molecules active against Ebola
  86. Databases for stem cell research
  87. How to start a company focused on a rare disease
  88. Quantitative NTCP pharmacophore
  89. NTCP Substrate pharmacophore
  90. Topo I inhibitors for TB
  91. Rules for licensing data and computational models
  92. pharmacophore for compounds active against Ebola
  93. Associated challenges with the divergent expansions of public and commercial sources of molecules
  94. Antibiotic drug conjugate
  95. pharmacophore for compounds active against Ebola
  96. Introduction to collection
  97. Collaboration for rare diseases
  98. Modeling the decisions of a medicinal chemist
  99. gaps in TB research
  100. Live Tweeting at Science conferences
  101. Major overhaul of the TB Mobile app and description of ECFP_6/FCFP_6 fingerprints in CDK project
  102. Bigger datasets for TB machine learning
  103. 2D similarity and steroid hormone immunoassays
  104. Can drug discovery become more effective using open data and prediction tools?
  105. Bath salts and molecular similarity
  106. Recommendations for CMT and GAN
  107. Recommendations for CMT and GAN
  108. cases studies for CDD software
  109. Predicting the efficiency of chemical compounds against the Tuberculosis bacterium
  110. Recommendations for CMT and GAN
  111. Recommendations for CMT and GAN
  112. A TB Topo I inhibitor
  113. Using Open Science Approaches to Find a Cure for Tuberculosis
  114. Computational Toxicology
  115. Bayesian models with IDRI
  116. Champions for rare diseases - an app idea
  117. Sanfilippo registry
  118. Roles of rare disease parents / patients in drug discovery
  119. combining datasets for TB machine learning models
  120. Hit to lead and Machine learning
  121. Gaps in neglected disease research
  122. Using molecular features to generate predictive models for Nuclear Receptors
  123. combining TB activity and cytotoxicity data for machine learning
  124. Dispensing processes profoundly influence estimates of biological activity of compounds
  125. Modeling trypanosomal diseases
  126. TB mobile for target prediction
  127. Sharing precompetitive data and models may accelerate drug discovery
  128. Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery
  129. NTCP pharmacophore and bayesian models
  130. Using a mobile app to raise awareness of Sanfilippo Syndrome type C
  131. Novel diaryl ureas with efficacy in a mouse model of malaria
  132. Virtual screening for antimalarials
  133. Transporters on Arachnoid barrier cells
  134. Using Mobile Technologies for Cheminformatics Applications
  135. Challenges associated with obtaining chemical structures of repurposing candidates from an online DB
  136. Models for TB drug discovery
  137. CDD database overview
  138. How Mobile Devices and Apps for Green Chemistry can bring value to scientists
  139. Simple Rules are needed for Licensing Data and Models for Open Drug Discovery
  140. using computational models for transporters
  141. Can more be done with hERG data? The correlation of hERG block and QT prolongation
  142. Advantages and utility of native human cardiac myocytes in compound screening
  143. Correction to “Identification and Validation of Novel Human Pregnane X Receptor Activators among Prescribed Drugs via Ligand-Based Virtual Screening”
  144. Delivering an app on a mobile platform to enable collaboration in open drug discovery
  145. Using mobile apps for the application of cheminformatics - making it intuitive
  146. What it will take to ensure that we build high quality public databases of chemical compounds
  147. Startegies for rare disease drug discovery
  148. Cheminformatics and pathways analysis for Mtb
  149. Experimental and Computational approaches for MATE1 and MATE2-K
  150. drug discovery bottlenecks
  151. drug discovery bottlenecks
  152. hOCTN2 substrate pharmacophore
  153. Predicting drug-drug interactions in vitro and in silico
  154. Software for RNA research
  155. Activation of CiVDR/PXR
  156. Databases for computational toxicology
  157. in silico models in drug discovery
  158. PXR models
  159. Mobile apps for chemistry
  160. Quality of public chemistry databases
  161. Business models
  162. new uses for old drugs
  163. collaborative technologies for research
  164. Collaborations in chemistry
  165. Standards for Collaborative Computational Technologies
  166. Challenges for collaborative computational technologies
  167. Using the cloud for collaborative drug discovery
  168. repositioning approved drugs
  169. TB whole cell models for aerobic activity
  170. evolution of LXR, FXR, VDR, PXR and CAR
  171. Computational tools for TB drug discovery
  172. Identification of hPXR Modulators via SAR-Based Virtual Screening
  173. mimicing essential metabolites
  174. A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human
  175. The evolution of farnesoid X, vitamin D, and pregnane X receptors: insights from the green-spotted pufferfish (Tetraodon nigriviridis) and other non-mammalian species
  176. Identification and Validation of Novel Human Pregnane X Receptor Activators among Prescribed Drugs via Ligand-Based Virtual Screening
  177. When pharmaceutical companies publish large datasets: an abundance of riches or fool's gold?
  178. Why we should be vigilant: Drug cytotoxicity observed with in vitro transporter inhibition studies
  179. Quantitative Structure Activity Relationship for Inhibition of Human Organic Cation/Carnitine Transporter
  180. A Predictive Ligand-Based Bayesian Model for Human Drug-Induced Liver Injury
  181. Using Open Source Computational Tools for Predicting Human Metabolic Stability and Additional Absorption, Distribution, Metabolism, Excretion, and Toxicity Properties
  182. Chemical Space: Missing Pieces in Cheminformatics
  183. Time for Cooperation in Health Economics among the Modelling Community
  184. Two farnesoid X receptor alpha isoforms in Japanese medaka (Oryzias latipes) are differentially activated in vitro
  185. Evaluation of Computational Docking to Identify Pregnane X Receptor Agonists in the ToxCast Database
  186. Evolving molecules using multi-objective optimization: applying to ADME/Tox
  187. ChemInform Abstract: Three-Dimensional Quantitative Structure-Permeability Relationship Analysis for a Series of Inhibitors of Rhinovirus Replication.
  188. Multiobjective Optimization for Drug Discovery
  189. Systems Biology: Applications in Drug Discovery
  190. Troubleshooting computational methods in drug discovery
  191. Integrated in Silico−in Vitro Strategy for Addressing Cytochrome P450 3A4 Time-Dependent Inhibition
  192. Reaching Out to Collaborators: Crowdsourcing for Pharmaceutical Research
  193. Examining public datasets of antimalarial “hits” and drugs
  194. Precompetitive preclinical ADME/Tox data: set it free on the web to facilitate computational model building and assist drug development
  195. Targeting Drug Transporters – Combining In Silico and In Vitro Approaches to Predict In Vivo
  196. A collaborative database and computational models for tuberculosis drug discovery
  197. Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis
  198. Chemical target and pathway toxicity mechanisms defined in primary human cell systems
  199. Challenges Predicting Ligand-Receptor Interactions of Promiscuous Proteins: The Nuclear Receptor PXR
  200. Competitive collaboration in the pharmaceutical and biotechnology industry
  201. Drug Transporter Pharmacophores
  202. A Systems Biology View of Drug Transporters
  203. Computer- Aided Decision Making from Drug Discovery to Pharmacoeconomics
  204. Immunoassays for Tricyclic Antidepressants
  205. Computational Models for Drug Inhibition of the Human Apical Sodium-Dependent Bile Acid Transporter
  206. Computational mapping tools for drug discovery
  207. Predicting Inhibitors of Acetylcholinesterase by Regression and Classification Machine Learning Approaches with Combinations of Molecular Descriptors
  208. Molecular Similarity Methods for Predicting Cross-Reactivity With Therapeutic Drug Monitoring Immunoassays
  209. Chemoinformatic Methods for Predicting Interference in Drug of Abuse/Toxicology Immunoassays
  210. Novel Inhibitors of Human Organic Cation/Carnitine Transporter (hOCTN2) via Computational Modeling and In Vitro Testing
  211. Elucidating the ‘Jekyll and Hyde’ Nature of PXR: The Case for Discovering Antagonists or Allosteric Antagonists
  212. Understanding nuclear receptors using computational methods
  213. Using molecular similarity to highlight the challenges of routine immunoassay-based drug of abuse/toxicology screening in emergency medicine
  214. Novel web-based tools combining chemistry informatics, biology and social networks for drug discovery
  215. The importance of discerning shape in molecular pharmacology
  216. The Major Human Pregnane X Receptor (PXR) Splice Variant, PXR.2, Exhibits Significantly Diminished Ligand-Activated Transcriptional Regulation
  217. Hybrid Scoring and Classification Using Shape-Based Approaches to Predict Human PXR Activators
  218. A Turning Point For Blood–Brain Barrier Modeling
  219. Hybrid Scoring and Classification Approaches to Predict Human Pregnane X Receptor Activators
  220. Drug Efficacy, Safety, and Biologics Discovery
  221. A retrospective randomized study of asthma control in the US: results of the CHARIOT study
  222. Bacterial Peptide Recognition and Immune Activation Facilitated by Human Peptide TransporterPEPT2
  223. Halogenated ligands and their interactions with amino acids: Implications for structure–activity and structure–toxicity relationships
  224. Intrinsic Disorder in Nuclear Hormone Receptors
  225. Computational Discovery of Novel Low Micromolar Human Pregnane X Receptor Antagonists
  226. Machine Learning Methods and Docking for Predicting Human Pregnane X Receptor Activation
  227. Molecular Characterization of CYP2B6 Substrates
  228. A Comprehensive in Vitro and in Silico Analysis of Antibiotics That Activate Pregnane X Receptor and Induce CYP3A4 in Liver and Intestine
  229. Shape Signatures: New Descriptors for Predicting Cardiotoxicity In Silico
  230. Ligand specificity and evolution of liver X receptors
  231. Mammalian Proteome and Toxicant Network Analysis
  232. New Predictive Models for Blood–Brain Barrier Permeability of Drug-like Molecules
  233. Evolution of the bile salt nuclear receptor FXR in vertebrates
  234. Evolution of pharmacologic specificity in the pregnane X receptor
  235. Design, Synthesis, Cytoselective Toxicity, Structure–Activity Relationships, and Pharmacophore of Thiazolidinone Derivatives Targeting Drug-Resistant Lung Cancer Cells
  236. Combined Computational Metabolite Prediction and Automated Structure-Based Analysis of Mass Spectrometric Data
  237. Future directions for drug transporter modelling
  238. Improving the drug selection and development process for combination devices
  239. Computational Models to Assign Biopharmaceutics Drug Disposition Classification from Molecular Structure
  240. In silico pharmacology for drug discovery: applications to targets and beyond
  241. In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
  243. Human Pregnane X Receptor Antagonists and Agonists Define Molecular Requirements for Different Binding Sites
  244. Computational Toxicology
  245. Computational Approaches That Predict Metabolic Intermediate Complex Formation with CYP3A4 (+b5)
  246. Methods for Predicting Human Drug Metabolism
  247. Three-Dimensional Quantitative Structure-Activity Relationship Analysis of Human CYP51 Inhibitors
  248. Classification of Metabolites with Kernel-Partial Least Squares (K-PLS)
  249. Pharmacophore-based discovery of ligands for drug transporters
  250. Application of data mining approaches to drug delivery
  251. Rapid Identification of P-glycoprotein Substrates and Inhibitors
  252. Insights for Human Ether-a-Go-Go-Related Gene Potassium Channel Inhibition Using Recursive Partitioning and Kohonen and Sammon Mapping Techniques
  253. Pharmacophores for Human ADME/Tox‐Related Proteins
  254. Computer Applications in Pharmaceutical Research and Development
  255. Computer Methods for Predicting Drug Metabolism
  256. Systems Approaches for Pharmaceutical Research and Development
  257. Effects of Antipsychotic Drugs on Ito, INa, Isus, IK1, and hERG: QT Prolongation, Structure Activity Relationship, and Network Analysis
  258. Systems-ADME/Tox: Resources and network approaches
  259. Algorithms for network analysis in systems-ADME/Tox using the MetaCore and MetaDrug platforms
  261. Reengineering the pharmaceutical industry by crash-testing molecules
  262. Computational prediction of human drug metabolism
  263. A novel method for generation of signature networks as biomarkers from complex high throughput data
  264. Comprehensive Computational Assessment of ADME Properties Using Mapping Techniques
  265. Comparative Pharmacophore Modeling of Organic Anion Transporting Polypeptides: A Meta-Analysis of Rat Oatp1a1 and Human OATP1B1
  266. In Vitro and Pharmacophore-Based Discovery of Novel hPEPT1 Inhibitors
  267. Techniques: Application of systems biology to absorption, distribution, metabolism, excretion and toxicity
  268. Systems Biology: Applications in Drug Discovery
  269. Molecular Determinants of Substrate/Inhibitor Binding to the Human and Rabbit Renal Organic Cation Transporters hOCT2 and rbOCT2
  271. PXR and the regulation of apoA1 and HDL-cholesterol in rodents
  272. Development of Computational Models for Enzymes, Transporters, Channels, and Receptors Relevant to ADME/Tox
  275. Predicting undesirable drug interactions with promiscuous proteins in silico
  276. Prediction of Human Drug Metabolizing Enzyme Induction
  278. In silico approaches to predicting drug metabolism, toxicology and beyond
  279. In vitro and pharmacophore insights into CYP3A enzymes
  280. Influence of Molecular Structure on Substrate Binding to the Human Organic Cation Transporter, hOCT1
  281. Integrating computer-based de novo drug design and multidimensional filtering for desirable drugs
  282. Three-Dimensional Quantitative Structure Activity Relationship for Cyp2d6 Substrates
  283. Optimizing Higher Throughput Methods to Assess Drug-Drug Interactions for CYP1A2, CYP2C9, CYP2C19, CYP2D6, rCYP2D6, and CYP3A4 In Vitro Using a Single Point IC50
  284. Quantitative Structure Activity Relationships for the Glucuronidation of Simple Phenols by Expressed Human UGT1A6 and UGT1A9
  285. Three-Dimensional Quantitative Structure-Activity Relationships of Inhibitors of P-Glycoprotein
  286. Application of Three-Dimensional Quantitative Structure-Activity Relationships of P-Glycoprotein Inhibitors and Substrates
  287. Three-Dimensional Quantitative Structure-Activity Relationship for Inhibition of Human Ether-a-Go-Go-Related Gene Potassium Channel
  288. Pharmacophore modeling of cytochromes P450
  289. Modeling of active transport systems
  290. The PXR crystal structure: the end of the beginning
  292. In silico ADME/Tox: the state of the art
  293. A Pharmacophore for Human Pregnane X Receptor Ligands
  294. Three-Dimensional Quantitative Structure-Permeability Relationship Analysis for a Series of Inhibitors of Rhinovirus Replication
  295. Application of in silico approaches to predicting drug–drug interactions
  296. Progress in predicting human ADME parameters in silico
  297. Present and future in vitro approaches for drug metabolism
  298. Characterization of transgenic mouse strains using six human hepatic cytochrome P450 probe substrates
  299. Molecular Cloning, Expression, and Characterization of CYP2D17 from Cynomolgus Monkey Liver
  300. In Vitro Metabolism
  302. Examination of purported probes of human CYP2B6
  303. Past, Present, and Future Applications of Precision-Cut Liver Slices for in Vitro Xenobiotic Metabolism
  304. Chapter 12. Ligand-Based Modeling of Toxicity
  305. Applications of QSAR to Enzymes Involved in Toxicology
  306. Toxicity Pathways and Models: Mining for Potential Side Effects
  307. Pathway Mapping Tools for Analysis of High Content Data
  308. Applications of QSAR Methods to Ion Channels
  309. Future Perspectives of Biological Engineering in Pharmaceutical Research: The Paradigm of Modeling, Mining, Manipulation, and Measurements
  310. Novel Applications of Kernel–Partial Least Squares to Modeling a Comprehensive Array of Properties for Drug Discovery
  311. Science AMA series: I co-founded two companies focused on rare and neglected diseases, I'm Sean Ekins, Ask Me Anything!