Hit And Lead Profiling

The only reference on current methods to generate pharmacokinetic and safety profiles of drug candidates, as well as how they must be balanced against one other for the best selection of candidates for further development.
Following a brief introduction to the necessities of filtering and risk assessment of potential new drug molecules before actual drug development, the two equally important aspects of pharmacological (ADME) and safety (toxicity) profiling are covered in separate parts.
The ADME section covers the profiling of basic physicochemical parameters, such as solubility and permeability, as well as more complex traits, such as the likelihood of drug-drug interactions, metabolic clearance and protein binding properties.
The toxicology part addresses, among others, recent advances in early genetic toxicity testing, bioactivation screening, organ-specific toxicity assays for liver, heart, kidney and blood, as well as profiling for autoimmune reactions.
By addressing both drug efficiency and drug safety, this modern practical reference shows readers how each individual aspect figures in shaping the key decisions on which the entire drug development process hinges. In short, this is a complete toolbox for assessing the risk/benefit ratio for any novel compound during the early drug development stages, using both in vitro and in silico methods.
Both editors are based at one of the leading research-driven pharmaceutical companies, and the authors have been recruited from numerous other global players in the field.
Invaluable know-how for every medicinal chemist and drug developer.

Bernard Faller is currently director in the Metabolism and Pharmacokinetics department at NIBR, Basel, Switzerland. He graduated as a biochemist from the University of Strasbourg, France, where he obtained his PhD in 1991. He then started at Ciba-Geigy as a post-doctoral fellow, becoming head of laboratory in 1995. In 1999 he moved to central technologies and established the foundations of the Novartis biopharmaceutical profiling group that addresses early ADME properties in drug discovery, and two years later became technology program head for physicochemical profiling in the Preclinical Compound Profiling Unit. In 2007 Dr. Faller was named Hero of Chemistry by the ACS for the discovery of Exjade, the first orally-active iron chelator for the treatment of transfusional iron overload.

Laszlo Urban is global head of Preclinical Safety Profiling at the Novartis Institutes for Biomedical Research (NIBR), Cambridge, MA, and previously was the Deputy Head of the Novartis Institute for Medical Sciences in London, UK. He received his MD and PhD in neurophysiology/neuropharmacology in Hungary, and was visiting professor at Duke University between 1987-1989. He joined the Sandoz Institute for Medical Research, London, in 1990, where he was head of pharmacology. Dr. Urban has published over 130 scientific articles, book chapters and patents and has served on the editorial board of several journals, while also serving as President of the European Neuropeptide Club, between 1999 and 2001.

List of Contributors.
Preface.
A Personal Foreword.
Part I.
1 Process Logistics, Testing Strategies and Automation Aspects (Hansjoerg Haas, Robert S. DeWitte, Robert Dunn-Dufault, and Andreas Stelzer).
1.1 Introduction.
1.2 The Process from Raw Ingredients to Data.
1.3 DMPK Testing Strategies: the Process from Data to Decisions.
1.4 New Questions, New Assays and New Technologies Challenge the Process.
1.5 Organizational Models to Scale Up the Process.
1.6 Critical Factors to Improve the Process.
1.7 Materials in ADME/Tox Screening.
1.8 Machines and Equipment in ADME/Tox Screening.
1.9 Software, Data Retrieval, Analysis, Manipulation and Interpretation.
1.10 Environment and Management = Organizational Structure in ADME/Tox Screening.
1.11 Methods in ADME/Tox Screening.
1.12 Conclusions.
References.
2 Prediction of Drug-Likeness and its Integration into the Drug Discovery Process (Ansgar Schuffenhauer and Meir Glick).
2.1 Introduction.
2.2 Computational Prediction of Drug-Likeness.
2.3 What is the Best Practice in Utilizing Drug-Likeness in Drug Discovery?.
2.4 Concluding Discussions.
References.
3 Integrative Risk Assessment (Bernard Faller and Laszlo Urban).
3.1 The Target Compound Profile.
3.2 The Concept of Hierarchical Testing in Primary and Follow-Up Assays.
3.3 Exposure Assays.
3.4 Iterative Assays: Link Between Assays.
3.5 Specific Safety Profiling Assays.
3.6 Data Reporting and Data Mining.
3.7 Integrative Risk Assessment.
References.
Part II.
4 Solubility and Aggregation (William H. Streng).
4.1 Importance of Solubility.
4.2 Factors Influencing Solubility.
4.3 Methods Used to Determine Solubility.
4.4 Approaches to Solubility.
4.5 Solubility in Non-Aqueous Solvents and Co-Solvents.
4.6 Solubility as a Function of pH.
4.7 Effect of Aggregation Upon Solubility.
4.8 Dependence of Dissolution upon Solubility.
4.9 Partitioning and the Effect of Aggregation.
4.10 Solubility in Simulated Biological Fluids.
References.
5 In Silico Tools and In Vitro HTS Approaches to Determine Lipophilicity During the Drug Discovery Process (Sophie Martel, Vincent Gasparik, and Pierre-Alain Carrupt).
5.1 Introduction.
5.2 Virtual Filtering: In Silico Prediction of log P and log D.
5.3 Experimental Filtering: the ADMET Characterization of a Hit Collection.
5.4 Concluding Remarks: Efficacy or Accuracy Dilemma.
References.
6 Membrane Permeability – Measurement and Prediction in Drug Discovery (Kiyohiko Sugano, Lourdes Cucurull-Sanchez, and Joanne Bennett).
6.1 Overview of Membrane Permeation.
6.2 In Vitro Cell Models.
6.3 Artificial Membranes.
6.4 Limitation of In Vitro Assays.
6.5 Computational Approaches/In Silico Modeling.
6.6 Outlook.
References.
7 Drug Metabolism and Reactive Metabolites (Alan P. Watt).
7.1 Introduction to Drug Metabolism.
7.2 Adverse Drug Reactions.
7.3 Bioactivation.
7.4 Reactive Metabolites and Idiosyncratic Toxicity.
7.5 Measurement of Reactive Metabolites.
7.6 Strategies for Minimizing Reactive Metabolite Risk.
7.7 Conclusions.
References.
8 Drug–Drug Interactions: Screening for Liability and Assessment of Risk (Ruth Hyland, R. Scott Obach, Chad Stoner, Michael West, Michael R. Wester, Kuresh Youdim, and Michael Zientek).
8.1 Introduction.
8.2 In Silico Approaches.
8.3 Perpetrators of Drug–Drug Interactions: Enzyme Inhibition.
8.4 Perpetrators of Drug–Drug Interactions: Enzyme Induction.
8.5 Drug–Drug Interactions; Victims of Interaction; Reaction Phenotyping.
8.6 Predictions of Drug–Drug Interactions.
8.7 Summary.
References.
9 Plasma Protein Binding and Volume of Distribution: Determination, Prediction and Use in Early Drug Discovery (Franco Lombardo, R. Scott Obach, and Nigel J. Waters).
9.1 Introduction: Importance of Plasma Protein Binding.
9.2 Impact of Plasma Protein Binding on PK, Exposure, Safety Margins, Potency Screens and Drug–Drug Interaction.
9.3 Methodologies for Measuring Plasma Protein Binding.
9.4 Physicochemical Determinants and In Silico Prediction of Plasma Protein Binding.
9.5 Volume of Distribution: General Considerations and Applications to Experimental Pharmacokinetics and Drug Design.
9.6 Relationship Between Clearance, VDss and Plasma Protein Binding.
9.7 Summary and Conclusions.
References.
10 Putting It All Together (Pamela Berry, Neil Parrott, Micaela Reddy, Pascale David-Pierson, and Thierry Lavé).
10.1 Challenges in Drug Discovery.
10.2 Methodological Aspects.
10.3 Strategic Use of PBPK During Drug Discovery.
10.4 Strategic Use of PK/PD During Drug Discovery.
10.5 Application During Lead Identification.
10.6 Application During Lead Optimization.
10.7 Application During Clinical Lead Selection.
10.8 Limitations with Current Methodology and Approaches.
10.9 Conclusions.
References.
Part III.
11 Genetic Toxicity: In Vitro Approaches for Hit and Lead Profiling (Richard M Walmsley and Nicholas Billinton).
11.1 Introduction.
11.2 Definitions.
11.3 Major Challenges for Early, Predictive Genotoxicity Testing.
11.4 Practical Issues for Genotoxicity Profiling: Vehicle, Dose, Dilution Range and Impurity.
11.5 Computational Approaches to Genotoxicity Assessment: ‘‘In Silico’’ Assessment.
11.6 Genotoxicity Assays for Screening.
11.7 Chromosome Damage and Aberration Assays.
11.8 Using Data from In Vitro Profiling: Confirmatory Tests, Follow-Up Tests, and the Link to Safety Assessment and In Vivo Models.
11.9 Can a Genetic Toxicity Profile Inform In Vivo Testing Strategies?.
11.10 What to Test, When and How?.
11.11 Summary.
References.
12 In Vitro Safety Pharmacology Profiling: an Important Tool to Decrease Attrition (Jacques Hamon and Steven Whitebread).
12.1 What is ‘‘In Vitro Safety Pharmacology Profiling?’’.
12.2 Examples of Drug Failures Due to Secondary Pharmacology.
12.3 Processes.
12.4 Application to Drug Discovery.
12.5 Conclusions and Outlook.
References.
13 Knowledge-Based and Computational Approaches to In Vitro Safety Pharmacology (Josef Scheiber, Andreas Bender, Kamal Azzaoui, and Jeremy Jenkins).
13.1 Introduction.
13.2 ‘‘Meta Analysis’’ of Safety Pharmacology Data: Predicting Compound Promiscuity.
13.3 Prediction of Off-Target Effects of Molecules Based on Chemical Structure.
13.4 Future Directions.
References.
Part IV.
14 Discovery Toxicology Screening: Predictive, In Vitro Cytotoxicity (Peter J. O.Brien).
14.1 Introduction.
14.2 Basis of Need for Discovery Toxicology Screening.
14.3 Obstacles to Discovery Toxicology Screening.
14.4 Need to Coordinate Cytotoxicity Screening with Other Discovery Safety Assessments.
14.5 Discovery Cytotoxicology.
14.6 High Effectiveness of an HCA Cell Model in Predictive Toxicology.
14.7 Future Impact of Cytotoxicity Testing.
References.
15 Predicting Drug-Induced Hepatotoxicity: In Vitro, In Silico and In Vivo Approaches (Jinghai J. Xu, Amit S. Kalgutkar, Yvonne Will, James Dykens, Elizabeth Tengstrand, and Frank Hsieh).
15.1 Introduction.
15.2 Reactive Metabolites.
15.3 Mitochondrial Toxicity.
15.4 Oxidative Stress.
15.5 Inhibition of Bile Salt Efflux Protein and Drug-Induced Cholestasis.
15.6 Biomarkers.
15.7 Conclusions.
References.
16 Should Cardiosafety be Ruled by hERG Inhibition? Early Testing Scenarios and Integrated Risk Assessment (Dimitri Mikhailov, Martin Traebert, Qiang Lu, Steven Whitebread, and William Egan).
16.1 Introduction.
16.2 Role of Ion Channels in Heart Electrophysiology.
16.3 hERG Profiling Assays.
16.4 Computational Models for hERG.
16.5 Integrated Risk Assessment.
16.6 Summary.
References.
17 Hematotoxicity: In Vitro and Ex Vivo Compound Profiling (David Brott and Francois Pognan).
17.1 Introduction.
17.2 Known Compounds with Hematotoxic Potential.
17.3 Tiered Cascade of Testing.
17.4 Triggers for Hematotoxicity Testing.
17.5 Conclusions.
References.
18 Profiling Adverse Immune Effects (Wim H. De Jong, Raymond Pieters, Kirsten A Baken, Rob J. Vandebriel, Jan-Willem Van Der Laan, and Henk Van Loveren).
18.1 Immunotoxicology.
18.2 Non-Animal Approaches for the Determination of Immunotoxicity.
18.3 Summary.
References.
19 In Vitro Phototoxicity Testing: a Procedure Involving Multiple Endpoints (Laurent Marrot and Jean-Roch Meunier).
19.1 Introduction.
19.2 Optical Considerations: Relevant UV Sources and Sunlight Absorption.
19.3 In Silico Methods for Prediction of Phototoxicity – (Q)SAR Models.
19.4 Photoreactivity In Tubo: Prescreening of Compounds Producing ROS Upon Sunlight Exposure.
19.5 Microbiological Models for Photomutagenesis Assessment.
19.6 Photocytotoxicity and Photogenotoxicity in Mammalian Cells: Regulatory Tests and Beyond.
19.7 Reconstructed Skin: a Model for Mimicking Phototoxicity in the Target Organ.
19.8 Conclusions.
References.
Index.