With a focus on case studies of R&D programs in a variety of disease areas, the book highlights fundamental productivity issues the pharmaceutical industry has been facing and explores potential ways of improving research effectiveness and efficiency.

Takes a comprehensive and holistic approach to the problems and potential solutions to drug compound attritionTackles a problem that adds billions of dollars to drug development programs and health care costsGuides discovery and development scientists through R&D stages, teaching requirements and reasons why drugs can failDiscusses potential ways forward utilizing new approaches and opportunities to reduce attrition

Alexander Alex, Dr. rer. nat., is director of Evenor Consulting and has over 20 years' experience as consultant and as director and research fellow in drug discovery in the pharmaceutical industry.

C. John Harris, PhD, is the director of cjh Consultants and has a successful track record in drug discovery, research management, small company fund-raising and start-ups.

Dennis A. Smith, PhD, is an independent consultant with a long track record in drug discovery and development with an emphasis on metabolism and safety. He has published four books, includingPharmacokinetics and Metabolism in Drug Design (1st and 2nd editions) andReactive Drug Metabolites published by Wiley.

Contributors xiiiIntroduction 1Alexander Alex C. John Harris and Dennis A. SmithReferences 41 Attrition in Drug Discovery and Development 5Scott Boyer Clive Brealey and Andrew M. Davis1.1 The Graph 51.2 The Sources of Attrition 71.3 Phase II Attrition 91.3.1 Target Engagement 111.3.2 Clinical Trial Design 111.4 Phase III Attrition 121.4.1 Safety Attrition in Phase III 141.5 Regulation and Attrition 171.6 Attrition in Phase IV 191.7 First in Class Best in Class and the Role of the Payer 321.8 Portfolio Attrition 341.9 Avoiding Attrition 361.9.1 Drug Combinations and New Formulations 361.9.2 Biologics versus Small Molecules 371.9.3 Small?-Molecule Compound Quality 381.10 Good Attrition versus Bad Attrition 391.11 Summary 40References 422 Compound Attrition at the Preclinical Phase 46Cornelis E.C.A. Hop2.1 Introduction: Attrition in Drug Discovery and Development 462.2 Target Identification HTS and Lead Optimization 502.3 Resurgence of Covalent Inhibitors 552.4 In Silico Models to Enhance Lead Optimization 562.5 Structure?-Based and Property?-Based Compound Design in Lead Optimization 592.5.1 Risks Associated with Operating in Nondrug?-Like Space 622.6 Attrition Due to ADME Reasons 642.6.1 Metabolism Bioactivation and Attrition 682.6.2 PK/PD Modeling in Drug Discovery to Reduce Attrition 692.6.3 Human PK Prediction Uncertainties 702.7 Attrition Due to Toxicity Reasons 722.8 Corporate Culture and Nonscientific Reasons for Attrition 752.9 Summary 76References 763 Attrition in Phase I 83Dennis A. Smith and Thomas A. Baillie3.1 Introduction 833.2 Attrition in Phase I Studies and Paucity of Published Information 843.3 Drug Attrition in not FIH Phase I Studies 853.4 Attrition in FIH Studies Due to PK 863.4.1 Attrition due to Pharmacogenetic Factors 883.5 Attenuation of PK failure 903.5.1 Preclinical Methods (In Vivo) 903.5.2 Preclinical Methods (In Vitro) 913.5.3 Phase 0 Microdose Studies in Humans 923.5.4 Responding to Unfavorable PK Characteristics 943.6 Phase I Oncology Studies 953.7 Toleration and Attrition in Phase I Studies 973.7.1 Improving the Hepatic Toleration of Compounds 983.7.2 Rare Severe Toxicity in Phase I Studies 983.8 Target Occupancy and Go/No?]Go Decisions to Phase II Start 993.9 Conclusions 102References 1024 Compound Attrition in Phase II/III 106Alexander Alex C. John Harris Wilma W. Keighley and Dennis A. Smith4.1 Introduction 1064.2 Attrition Rates: How Have they Changed? 1074.3 Why do Drugs Fail in Phase II/III? Lack of Efficacy or Marginal Efficacy Leading to Likely CommercialFailure 1084.4 Toxicity 1114.5 Organizational Culture 1124.6 Case Studies for Phase II/III Attrition 1124.6.1 Torcetrapib 1124.6.2 Dalcetrapib 1134.6.3 Onartuzumab 1144.6.4 Bapineuzumab 1154.6.5 Gantenerumab 1154.6.6 Solanezumab 1164.6.7 Pomaglumetad Methionil (LY?]2140023) 1164.6.8 Dimebon (Latrepirdine) 1174.6.9 BMS?]986094 1174.6.10 TC?]5214 (S?]Mecamylamine) 1184.6.11 Olaparib 1184.6.12 Tenidap 1194.6.13 NNC0109?]0012 (RA) 1204.6.14 Omapatrilat 1204.6.15 Ximelagatran 1214.7 Summary and Conclusions 122References 1235 Postmarketing Attrition 128Dennis A. Smith5.1 Introduction 1285.2 On?-Target Pharmacology?-Flawed Mechanism 1305.2.1 Alosetron 1305.2.2 Cerivastatin 1305.2.3 Tegaserod 1335.3 Off?-Target Pharmacology Known Receptor: An Issue of Selectivity 1355.3.1 Fenfluramine and Dexfenfluramine 1355.3.2 Rapacuronium 1365.3.3 Astemizole Cisapride Grepafloxacin and Thioridazine 1385.4 Off?-Target Pharmacology Unknown Receptor: Idiosyncratic Toxicology 1425.4.1 Benoxaprofen 1425.4.2 Bromfenac 1425.4.3 Nomifensine 1435.4.4 Pemoline 1445.4.5 Remoxipride 1445.4.6 Temafloxacin 1455.4.7 Tienilic acid 1455.4.8 Troglitazone 1465.4.9 Tolcapone 1465.4.10 Trovafloxacin 1475.4.11 Valdecoxib 1485.4.12 Zomepirac 1485.5 Conclusions 150References 1516 Influence of the Regulatory Environment on Attrition 158Robert T. Clay6.1 Introduction 1586.1.1 How the Regulatory Environment has Changed Over the Last Two Decades 1596.1.2 Past and Current Regulatory Attitude to Risk Analysis and Risk Management 1616.2 Discussion 1626.2.1 What Stops Market Approval? 1626.2.2 Impact of Black Box Warnings 1666.2.3 Importance and Impact of Pharmacovigilance 1676.2.4 Prospects of Market Withdrawals for New Drugs 1686.2.5 What are the Challenges for the Industry Given the Current Regulatory Environment? 1736.2.6 Future Challenges for Both Regulators and the Pharmaceutical Industry 1746.3 Conclusion 175References 1767 Experimental Screening Strategies to Reduce Attrition Risk 180Marie?-Claire Peakman Matthew Troutman Rosalia Gonzales and Anne Schmidt7.1 Introduction 1807.2 Screening Strategies in Hit Identification 1837.2.1 Screening Strategies and Biology Space 1837.2.2 Screening Strategies and Chemical Space 1877.2.3 High?-Throughput Screening Technologies 1917.2.4 Future Directions for High?-Throughput Screening 1947.3 Screening Strategies in Hit Validation and Lead Optimization 1947.4 Screening Strategies for Optimizing PK and Safety 1977.4.1 High?-Throughput Optimization of PK/ADME Profiles 1987.4.2 Early Safety Profiling 2027.4.3 Future Directions for ADME and Safety in Lead Optimization 2047.5 Summary 205References 2068 Medicinal Chemistry Strategies to Prevent Compound Attrition 215J. Richard Morphy8.1 Introduction 2158.2 Picking the Right Target 2168.3 Finding Starting Compounds 2168.4 Compound Optimization 2188.4.1 Drug?-Like Compounds 2188.4.2 Structure?-Based Drug Design 2198.4.3 The Thermodynamics and Kinetics of Compound Optimization 2208.4.4 PK 2208.4.5 Toxicity 2228.5 Summary 225References 2269 Influence of Phenotypic and Target?]Based Screening Strategies on Compound Attrition and Project Choice 229Andrew Bell Wolfgang Fecke and Christine Williams9.1 Drug Discovery Approaches: A Historical Perspective 2299.1.1 Phenotypic Screening 2299.1.2 Target?-Based Screening 2309.1.3 Recent Changes in Drug Discovery Approaches 2319.2 Current Phenotypic Screens 2339.2.1 Definition of Phenotypic Screening 2339.2.2 Recent Anti?-infective Projects 2339.2.3 Recent CNS Projects 2359.3 Current Targeted Screening 2379.3.1 Definition of Targeted Screening 2379.3.2 Recent Anti?-infective Projects 2379.3.3 Recent CNS Projects 2399.4 Potential Attrition Factors 2419.4.1 Technical Doability and Hit Identification 2419.4.2 Compound SAR and Properties 2469.4.3 Safety 2489.4.4 Translation to the Clinic 2509.5 Summary and Future Directions 2529.5.1 Summary of Impact of Current Approaches 2529.5.2 Future Directions 2549.5.3 Conclusion 255References 25510 In Silico Approaches to Address Compound Attrition 264Peter Gedeck Christian Kramer and Richard Lewis10.1 In Silico Models Help to Alleviate the Process of Finding Both Safe and Efficacious Drugs 26410.2 Use of In Silico Approaches to Reduce Attrition Risk at the Discovery Stage 26510.3 Ligand?-Based and Structure?-Based Models 26510.4 Data Quality 26810.5 Predicting Model Errors 27010.6 Molecular Properties and their Impact on Attrition 27210.7 Modeling of ADME Properties and their Impact of Reducing Attrition in the Last Two Decades 27510.8 Approaches to Modeling of Tox 27610.9 Modeling PK and PD and Dose Prediction 27610.10 Novel In Silico Approaches to Reduce Attrition Risk 27810.11 Conclusions 280References 28011 Current and Future Strategies for Improving Drug Discovery Efficiency 287Peter Mbugua Njogu and Kelly Chibale11.1 General Introduction 28711.2 Scope 28811.3 Neglected Diseases 28911.3.1 Introduction 28911.3.2 Control of NTDs 29011.3.3 Drug Discovery Potential of Neglected Diseases 29011.4 Precompetitive Drug Discovery 29211.4.1 Introduction 29211.4.2 Virtual Discovery Organizations 29311.4.3 Collaborations with Academic Laboratories 29511.4.4 CoE and Incubators 29611.4.5 Screening Data and Compound File Sharing 29711.5 Exploitation of Genomics 29711.5.1 Introduction 29711.5.2 Target Identification and Validation 29811.5.3 Target?-Based Drug Discovery 29811.5.4 Phenotypic Whole?-Cell Screening 30111.5.5 Individualized Therapy and Therapies for Special Patient Populations 30211.6 Outsourcing Strategies 30411.6.1 Introduction 30411.6.2 Research Contracting in Drug Discovery 30511.7 Multitarget Drug Design and Discovery 30511.7.1 Introduction 30511.7.2 Rationale for Multitargeted Drugs 30611.7.3 Designed Multitarget Compounds for Neglected Diseases 30711.8 Drug Repositioning and Repurposing 31511.8.1 Introduction 31511.8.2 Cell Biology Approach 31711.8.3 Exploitation of Genome Information 31811.8.4 Compound Screening Studies 31811.8.5 Exploitation of Coinfection Drug Efficacy 31811.8.6 In Silico Computational Technologies 31911.9 Future Outlook 319References 31912 Impact of Investment Strategies Organizational Structure and Corporate Environment on Attrition and Future Investment Strategies to Reduce Attrition 329Geoff Lawton12.1 Attrition 32912.2 Costs 33112.2.1 The Costs of Creating a New Medicine 33112.2.2 The Costs of Not Creating a New Medicine 33212.3 Investment Strategies 33412.3.1 RoI 33412.3.2 Investment in a Portfolio of R&D Projects 33512.3.3 Asset?-Centered Investment 33512.3.4 Sources of Funds 33612.4 Business Models 33712.4.1 FIPCO 33712.4.2 Fully Integrated Pharmaceutical Network (FIPNET) 33812.4.3 Venture?-Funded Biotech 33912.4.4 Fee?-for?-Service CRO 33912.4.5 Hybrids 33912.4.6 Academic Institute 34012.4.7 Social Enterprise 34112.5 Portfolio Management 34112.5.1 Portfolio Construction 34112.5.2 Project Progression 34312.5.3 The Risk Transition Point 34312.6 People 34412.6.1 Motivation 34412.6.2 Culture and Leadership 34412.6.3 Sustainability 34412.7 Future 34512.7.1 Business Structures 34512.7.2 Skilled Practitioners 34712.7.3 Partnerships 34812.7.4 A Personal View of the Future 349References 351Index 353