Attrition in the Pharmaceutical Industry: Reasons, Implications, and Pathways Forward

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 attrition  Tackles a problem that adds billions of dollars to drug development programs and health care costs  Guides discovery and development scientists through R&D stages, teaching requirements and reasons why drugs can fail  Discusses potential ways forward utilizing new approaches and opportunities to reduce attrition INDICE: Contributors xiii .Introduction 1Alexander Alex, C. John Harris and Dennis A. Smith .References, 4 .1 Attrition in Drug Discovery and Development 5Scott 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 46Cornelis 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 83Dennis 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 106Alexander 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 128Dennis 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 158Robert 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 180Marie ]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 215J. 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 229Andrew 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 264Peter 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 287Peter 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 O utsourcing 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 329Geoff 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

• ISBN: 978-1-118-67967-8
• Editorial: Wiley–Blackwell
• Encuadernacion: Cartoné
• Páginas: 384
• Fecha Publicación: 19/01/2016
• Nº Volúmenes: 1
• Idioma: Inglés