Title Details

Contributors xiii

Introduction 1
Alexander Alex C. John Harris and Dennis A. Smith

References 4

1 Attrition in Drug Discovery and Development 5
Scott Boyer Clive Brealey and Andrew M. Davis

1.1 “The Graph” 5

1.2 The Sources of Attrition 7

1.3 Phase II Attrition 9

1.3.1 Target Engagement 11

1.3.2 Clinical Trial Design 11

1.4 Phase III Attrition 12

1.4.1 Safety Attrition in Phase III 14

1.5 Regulation and Attrition 17

1.6 Attrition in Phase IV 19

1.7 First in Class Best in Class and the Role of the Payer 32

1.8 Portfolio Attrition 34

1.9 “Avoiding” Attrition 36

1.9.1 Drug Combinations and New Formulations 36

1.9.2 Biologics versus Small Molecules 37

1.9.3 Small-Molecule Compound Quality 38

1.10 Good Attrition versus Bad Attrition 39

1.11 Summary 40

References 42

2 Compound Attrition at the Preclinical Phase 46
Cornelis E.C.A. Hop

2.1 Introduction: Attrition in Drug Discovery and Development 46

2.2 Target Identification HTS and Lead Optimization 50

2.3 Resurgence of Covalent Inhibitors 55

2.4 In Silico Models to Enhance Lead Optimization 56

2.5 Structure-Based and Property-Based Compound Design in Lead Optimization 59

2.5.1 Risks Associated with Operating in Nondrug-Like Space 62

2.6 Attrition Due to ADME Reasons 64

2.6.1 Metabolism Bioactivation and Attrition 68

2.6.2 PK/PD Modeling in Drug Discovery to Reduce Attrition 69

2.6.3 Human PK Prediction Uncertainties 70

2.7 Attrition Due to Toxicity Reasons 72

2.8 Corporate Culture and Nonscientific Reasons for Attrition 75

2.9 Summary 76

References 76

3 Attrition in Phase I 83
Dennis A. Smith and Thomas A. Baillie

3.1 Introduction 83

3.2 Attrition in Phase I Studies and Paucity of Published Information 84

3.3 Drug Attrition in not FIH Phase I Studies 85

3.4 Attrition in FIH Studies Due to PK 86

3.4.1 Attrition due to Pharmacogenetic Factors 88

3.5 Attenuation of PK failure 90

3.5.1 Preclinical Methods (In Vivo) 90

3.5.2 Preclinical Methods (In Vitro) 91

3.5.3 Phase 0 Microdose Studies in Humans 92

3.5.4 Responding to Unfavorable PK Characteristics 94

3.6 Phase I Oncology Studies 95

3.7 Toleration and Attrition in Phase I Studies 97

3.7.1 Improving the Hepatic Toleration of Compounds 98

3.7.2 Rare Severe Toxicity in Phase I Studies 98

3.8 Target Occupancy and Go/No]Go Decisions to Phase II Start 99

3.9 Conclusions 102

References 102

4 Compound Attrition in Phase II/III 106
Alexander Alex C. John Harris Wilma W. Keighley and Dennis A. Smith

4.1 Introduction 106

4.2 Attrition Rates: How Have they Changed? 107

4.3 Why do Drugs Fail in Phase II/III? Lack of Efficacy or Marginal Efficacy Leading to Likely Commercial
Failure 108

4.4 Toxicity 111

4.5 Organizational Culture 112

4.6 Case Studies for Phase II/III Attrition 112

4.6.1 Torcetrapib 112

4.6.2 Dalcetrapib 113

4.6.3 Onartuzumab 114

4.6.4 Bapineuzumab 115

4.6.5 Gantenerumab 115

4.6.6 Solanezumab 116

4.6.7 Pomaglumetad Methionil (LY]2140023) 116

4.6.8 Dimebon (Latrepirdine) 117

4.6.9 BMS]986094 117

4.6.10 TC]5214 (S]Mecamylamine) 118

4.6.11 Olaparib 118

4.6.12 Tenidap 119

4.6.13 NNC0109]0012 (RA) 120

4.6.14 Omapatrilat 120

4.6.15 Ximelagatran 121

4.7 Summary and Conclusions 122

References 123

5 Postmarketing Attrition 128
Dennis A. Smith

5.1 Introduction 128

5.2 On-Target Pharmacology-Flawed Mechanism 130

5.2.1 Alosetron 130

5.2.2 Cerivastatin 130

5.2.3 Tegaserod 133

5.3 Off-Target Pharmacology Known Receptor: An Issue of Selectivity 135

5.3.1 Fenfluramine and Dexfenfluramine 135

5.3.2 Rapacuronium 136

5.3.3 Astemizole Cisapride Grepafloxacin and Thioridazine 138

5.4 Off-Target Pharmacology Unknown Receptor: Idiosyncratic Toxicology 142

5.4.1 Benoxaprofen 142

5.4.2 Bromfenac 142

5.4.3 Nomifensine 143

5.4.4 Pemoline 144

5.4.5 Remoxipride 144

5.4.6 Temafloxacin 145

5.4.7 Tienilic acid 145

5.4.8 Troglitazone 146

5.4.9 Tolcapone 146

5.4.10 Trovafloxacin 147

5.4.11 Valdecoxib 148

5.4.12 Zomepirac 148

5.5 Conclusions 150

References 151

6 Influence of the Regulatory Environment on Attrition 158
Robert T. Clay

6.1 Introduction 158

6.1.1 How the Regulatory Environment has Changed Over the Last Two Decades 159

6.1.2 Past and Current Regulatory Attitude to Risk Analysis and Risk Management 161

6.2 Discussion 162

6.2.1 What Stops Market Approval? 162

6.2.2 Impact of Black Box Warnings 166

6.2.3 Importance and Impact of Pharmacovigilance 167

6.2.4 Prospects of Market Withdrawals for New Drugs 168

6.2.5 What are the Challenges for the Industry Given the Current Regulatory Environment? 173

6.2.6 Future Challenges for Both Regulators and the Pharmaceutical Industry 174

6.3 Conclusion 175

References 176

7 Experimental Screening Strategies to Reduce Attrition Risk 180
Marie-Claire Peakman Matthew Troutman Rosalia Gonzales and Anne Schmidt

7.1 Introduction 180

7.2 Screening Strategies in Hit Identification 183

7.2.1 Screening Strategies and Biology Space 183

7.2.2 Screening Strategies and Chemical Space 187

7.2.3 High-Throughput Screening Technologies 191

7.2.4 Future Directions for High-Throughput Screening 194

7.3 Screening Strategies in Hit Validation and Lead Optimization 194

7.4 Screening Strategies for Optimizing PK and Safety 197

7.4.1 High-Throughput Optimization of PK/ADME Profiles 198

7.4.2 Early Safety Profiling 202

7.4.3 Future Directions for ADME and Safety in Lead Optimization 204

7.5 Summary 205

References 206

8 Medicinal Chemistry Strategies to Prevent Compound Attrition 215
J. Richard Morphy

8.1 Introduction 215

8.2 Picking the Right Target 216

8.3 Finding Starting Compounds 216

8.4 Compound Optimization 218

8.4.1 Drug-Like Compounds 218

8.4.2 Structure-Based Drug Design 219

8.4.3 The Thermodynamics and Kinetics of Compound Optimization 220

8.4.4 PK 220

8.4.5 Toxicity 222

8.5 Summary 225

References 226

9 Influence of Phenotypic and Target]Based Screening Strategies on Compound Attrition and Project Choice 229
Andrew Bell Wolfgang Fecke and Christine Williams

9.1 Drug Discovery Approaches: A Historical Perspective 229

9.1.1 Phenotypic Screening 229

9.1.2 Target-Based Screening 230

9.1.3 Recent Changes in Drug Discovery Approaches 231

9.2 Current Phenotypic Screens 233

9.2.1 Definition of Phenotypic Screening 233

9.2.2 Recent Anti-infective Projects 233

9.2.3 Recent CNS Projects 235

9.3 Current Targeted Screening 237

9.3.1 Definition of Targeted Screening 237

9.3.2 Recent Anti-infective Projects 237

9.3.3 Recent CNS Projects 239

9.4 Potential Attrition Factors 241

9.4.1 Technical Doability and Hit Identification 241

9.4.2 Compound SAR and Properties 246

9.4.3 Safety 248

9.4.4 Translation to the Clinic 250

9.5 Summary and Future Directions 252

9.5.1 Summary of Impact of Current Approaches 252

9.5.2 Future Directions 254

9.5.3 Conclusion 255

References 255

10 In Silico Approaches to Address Compound Attrition 264
Peter Gedeck Christian Kramer and Richard Lewis

10.1 In Silico Models Help to Alleviate the Process of Finding Both Safe and Efficacious Drugs 264

10.2 Use of In Silico Approaches to Reduce Attrition Risk at the Discovery Stage 265

10.3 Ligand-Based and Structure-Based Models 265

10.4 Data Quality 268

10.5 Predicting Model Errors 270

10.6 Molecular Properties and their Impact on Attrition 272

10.7 Modeling of ADME Properties and their Impact of Reducing Attrition in the Last Two Decades 275

10.8 Approaches to Modeling of Tox 276

10.9 Modeling PK and PD and Dose Prediction 276

10.10 Novel In Silico Approaches to Reduce Attrition Risk 278

10.11 Conclusions 280

References 280

11 Current and Future Strategies for Improving Drug Discovery Efficiency 287
Peter Mbugua Njogu and Kelly Chibale

11.1 General Introduction 287

11.2 Scope 288

11.3 Neglected Diseases 289

11.3.1 Introduction 289

11.3.2 Control of NTDs 290

11.3.3 Drug Discovery Potential of Neglected Diseases 290

11.4 Precompetitive Drug Discovery 292

11.4.1 Introduction 292

11.4.2 Virtual Discovery Organizations 293

11.4.3 Collaborations with Academic Laboratories 295

11.4.4 CoE and Incubators 296

11.4.5 Screening Data and Compound File Sharing 297

11.5 Exploitation of Genomics 297

11.5.1 Introduction 297

11.5.2 Target Identification and Validation 298

11.5.3 Target-Based Drug Discovery 298

11.5.4 Phenotypic Whole-Cell Screening 301

11.5.5 Individualized Therapy and Therapies for Special Patient Populations 302

11.6 Outsourcing Strategies 304

11.6.1 Introduction 304

11.6.2 Research Contracting in Drug Discovery 305

11.7 Multitarget Drug Design and Discovery 305

11.7.1 Introduction 305

11.7.2 Rationale for Multitargeted Drugs 306

11.7.3 Designed Multitarget Compounds for Neglected Diseases 307

11.8 Drug Repositioning and Repurposing 315

11.8.1 Introduction 315

11.8.2 Cell Biology Approach 317

11.8.3 Exploitation of Genome Information 318

11.8.4 Compound Screening Studies 318

11.8.5 Exploitation of Coinfection Drug Efficacy 318

11.8.6 In Silico Computational Technologies 319

11.9 Future Outlook 319

References 319

12 Impact of Investment Strategies Organizational Structure and Corporate Environment on Attrition and Future Investment Strategies to Reduce Attrition 329
Geoff Lawton

12.1 Attrition 329

12.2 Costs 331

12.2.1 The Costs of Creating a New Medicine 331

12.2.2 The Costs of Not Creating a New Medicine 332

12.3 Investment Strategies 334

12.3.1 RoI 334

12.3.2 Investment in a Portfolio of R&D Projects 335

12.3.3 Asset-Centered Investment 335

12.3.4 Sources of Funds 336

12.4 Business Models 337

12.4.1 FIPCO 337

12.4.2 Fully Integrated Pharmaceutical Network (FIPNET) 338

12.4.3 Venture-Funded Biotech 339

12.4.4 Fee-for-Service CRO 339

12.4.5 Hybrids 339

12.4.6 Academic Institute 340

12.4.7 Social Enterprise 341

12.5 Portfolio Management 341

12.5.1 Portfolio Construction 341

12.5.2 Project Progression 343

12.5.3 The Risk Transition Point 343

12.6 People 344

12.6.1 Motivation 344

12.6.2 Culture and Leadership 344

12.6.3 Sustainability 344

12.7 Future 345

12.7.1 Business Structures 345

12.7.2 Skilled Practitioners 347

12.7.3 Partnerships 348

12.7.4 A Personal View of the Future 349

References 351

Index 353 

"Innovative drug discovery can only be partially guided by knowledge from known chemical and pharmacological space, so a level of attrition is therefore inevitable. This refreshingly readable book provides an engaging combination of background historical and current reasons for attrition, combined with a panorama of some of the possible ways to covert “attrition” into the informed risk-taking necessary for innovative drug discovery. The book is very logically presented across the phases of drug discovery out across the technologies an across the phases of drug discovery and thus builds in depth reference source especially for those entering the challenging environment of drug discovery. As the authors point out, converting molecules into drugs remains difficult and engaging in more projects as a way to ensure a minimal level of success is not sustainable, so challenging and understanding better the reasons for attrition are of fundamental importance. The reasons for attrition change over time as some factors, notably AMDE and PK are better understood. But an inability to accurately predict still hampers the industry. This book makes a very useful reference source by highlighting where progress is being made, for example, the AstraZeneca 5Rs approach or the translational data analysis by Pfizer showing three parameters which correlate combined confidence in pharmacology an exposure with confidence in Phase II success. The book then nicely moves the reader on from the improvements in Phase II attrition by asking the critical question, “Why do drugs fail in Phase III if efficacy failures in Phase II are being better managed?” One of the advantages of this book is that it not only provides a well written background review, but that it combines this with examples of where progress it still needed, something of particular importance as regulators increasingly place emphasis on safety profiles. Although the book does make some comments to other modalities, it focuses on small molecule drug discovery, for which the authors take the reader through all stages of drug discovery form target identification to post-marketing attrition with extensive use of informative case studies. These case studies are used to highlight where attrition has been reduced, where improvements are still needed, and for preclinical research in particular where attrition isn’t necessarily bad, but rather a consequence of innovative drug discovery, that is best managed in a structured approach where knowledge can be transferred between projects. As the pharmaceutical industry moves to a more fragmented but networked environment changes in the ways in which knowledge is acquired and transferred between companies will significantly change the ways in which attrition is confronted. This book is therefore an excellent source material that will be of great value to all those embarking in drug discovery in smaller more agile companies. As evidenced in Chapter 2, preclinical research has made significant inroads in managing attrition with structured approaches to ADME profiling and PK/PD modelling. This is picked up and integrated into more detailed discussion later in Chapters 7–10, covering reasons for attrition associated with the various technologies employed in preclinical research. Whilst attrition in preclinical research can be mitigated and to varying extents managed, attrition in clinical studies represent failure of a project or mechanism. Clinical and post-marketing failures continue to limit the overall efficiency of the drug discovery industry. The reasons are many and starting in chapter 3 with Phase I this book systematically reviews the factors influencing attrition in each phase, combined with examples of how some may be reduced. Attrition due to PK and tolerability issues remain the main causes of Phase I attrition, although PK attrition can be attenuated by preclinical in vitro CYP profiling combined with in vivo PK studies. Phase I oncology studies are more susceptible to tolerability problems and in general tolerability issues are a common reason for termination of dose escalation studies across disease areas. The chapter finishes with an interesting discussion on the addition of Target Occupancy readouts in Phase I studies for a range of different target classes. Determining the Target Occupancy required for efficacy significantly improves the probability of a success in subsequent Phase II studies. In the following Chapter, the discussion moves to attrition in Phase II/III studies with a detailed series of well-chosen case studies that highlight that despite improving Phase II success rates, lack of efficacy in some cases compounded by addition toxicological issues remains the main reason for Phase II/III failures. Failure is evenly spread across small molecules, antibodies, and biologics, though some disease areas such as Alzheimer’s disease are more difficult. Well-selected case histories are also used to highlight post-marketing attrition arising from both on- and off-target pharmacologies, where unacceptable benefit– risk scenarios have led to drugs being removed from the market or subject to restricting label restrictions. And as highlighted in Chapter 5 some off-target side effects are only revealed in large (postmarketing) populations which show highlight second target or other side effects. Whilst not perhaps directly as source of attrition, changes in the regulatory environment are presented in Chapter 6 as they have a significant retroactive effect on drug discovery. For example, no project today would be progressed without extensive studies on liability for drug-induced QTc prolongation. Drug withdrawals due to safety are thankfully relatively rare, nevertheless FA and EMA guidance impact significantly on introducing additional parameters in pre-clinical and clinical research that need to be effectively controlled to avoid attrition. Chapter 9 contrasts the different attrition scenarios contained in phenotypic screening and target-based drug discovery projects, using key case studies from anti-infective and CNS projects. The values of each approach and the associated potential attrition factors, such as; complex SAR in phenotypic screening or the disconnection from pharmacological relevance in target-based approaches are compared. Attrition is also affected in each approach by technological factors and implications for data-driven compound optimization and translation into clinical studies. As screening technologies advance the distinction between the two approaches becomes less clear, and for now the combination of both approaches coupled with in silico modelling appears to best method for project progression and mitigation of downstream attrition. As discussed in Chapter 10 of the book, data integration and interpretation via in silico modelling has significantly helped reduce pre-clinical attrition. ADME and toxicity profiling in particular have benefitted from ability to predict compound properties via iterative cycles of in silico modelling. Indeed, knowledge sharing of compound data and properties either by public databases or industry-academic collaborations has proven an effective route to help further reduce attrition. The book closes with two chapters looking to the future and to emerging new approaches to tackle attrition rates that are emerging from pre-competitive collaborative research and new business models and above all the continued need for highly motivated knowledge seeking researchers that make the drug discovery business successful. As highlighted in the conclusion, “if there were no attrition, it would not be research”. Attrition in drug discovery will always be a factor as new targets and new mechanisms are investigated. Attrition is a necessary element of innovation, and through constant improvements in our understanding of the causes of attrition continued reduction of failures due to lack of efficacy and in particular safety issues can be expected."
Prof. Roberto Pellicciari, TES Pharma, Perugia (ChemMedChem, July 2017)