Hit and Lead Profiling: Identification and Optimization of Drug–like Molecules

The enormous cost incurred when a candidate drug fails in a clinical trial because of poor pharmacological parameters or severe side effects makes it imperative to screen for "safe" drugs in the very early stages of drug development. Various biochemical and other in vitro assays are thus used in conjunction with the analysis of physicochemical properties of the potential drug molecules, enabling an informed selection of drug development candidates before they enter clinical trials.
By addressing both drug efficiency and drug safety, this modern practical reference shows how each individual aspect figures in shaping the key decisions on which the entire drug development process hinges. The result is a complete toolbox for assessing the risk/benefit ratio for any novel compound, using both in vitro and in silico methods.
Following a brief introduction to the necessities of filtering and risk assessment, the two equally important aspects of pharmacological (ADME) and safety (toxicity) profiling are covered in separate parts. The whole of the fourth and final part is devoted to organ–specific toxicity assays for the liver, heart, kidney and blood, as well as profiling for autoimmune reactions.
Invaluable know–how for every medicinal chemist and drug developer.

Spis treści:
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 Su mmary 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 Jerem