Details

Drug Discovery Toxicology


Drug Discovery Toxicology

From Target Assessment to Translational Biomarkers
1. Aufl.

von: Yvonne Will, J. Eric McDuffie, Andrew J. Olaharski, Brandon D. Jeffy

171,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 16.03.2016
ISBN/EAN: 9781119053323
Sprache: englisch
Anzahl Seiten: 584

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Beschreibungen

<p>As a guide for pharmaceutical professionals to the issues and practices of drug discovery toxicology, this book integrates and reviews the strategy and application of tools and methods at each step of the drug discovery process.</p> <p>• Guides researchers as to what drug safety experiments are both practical and useful<br />• Covers a variety of key topics – safety lead optimization, in vitro-in vivo translation, organ toxicology, ADME, animal models, biomarkers, and –omics tools<br />• Describes what experiments are possible and useful and offers a view into the future, indicating key areas to watch for new predictive methods<br />• Features contributions from firsthand industry experience, giving readers insight into the strategy and execution of predictive toxicology practices</p>
<p><b>LIST OF CONTRIBUTORS xxi</b></p> <p><b>FOREWORD xxv</b></p> <p><b>PART I INTRODUCTION 1</b></p> <p><b>1 Emerging Technologies and their Role in Regulatory Review 3<br /> </b><i>Thomas J. Colatsky</i></p> <p>1.1 Introduction 3</p> <p>1.2 safety assessment in Drug Development and Review 4</p> <p>1.3 The Role of New Technologies in Regulatory Safety Assessment 6</p> <p>1.4 Conclusions 8</p> <p>References 8</p> <p><b>PART II SAFETY LEAD OPTIMIZATION STRATEGIES 13</b></p> <p><b>2 Small</b><b>‐</b><b>Molecule Safety Lead Optimization 15<br /> </b><i>Donna M. Dambach</i></p> <p>2.1 Background and Objectives of Safety Lead Optimization Approaches 15</p> <p>2.2 Target Safety Assessments: Evaluation of Undesired Pharmacology and Therapeutic Area Considerations 16</p> <p>2.3 Implementing Lead Optimization Strategies for Small Molecules 16</p> <p>2.4 Conclusions 23</p> <p>References 23</p> <p><b>3 Safety Assessment Strategies and Predictive Safety of Biopharmaceuticals and Antibody Drug Conjugates 27<br /> </b><i>Michelle J. Horner, Mary Jane Hinrichs and Nicholas Buss</i></p> <p>3.1 Background and Objectives 27</p> <p>3.2 Target Safety Assessments: Strategies to Understand Target Biology and Associated Liabilities 28</p> <p>3.3 Strategic Approaches for Biopharmaceuticals and ADCs 29</p> <p>3.4 Predictive Safety Tools for Large Molecules 33</p> <p>3.5 Strategies for Species Selection 34</p> <p>3.6 Strategy for Dose‐Ranging Studies for Safety Evaluation of Biopharmaceuticals 35</p> <p>3.7 Conclusions 35</p> <p>References 36</p> <p><b>4 Discovery and Development Strategies for Small Interfering Rnas 39<br /> </b><i>Scott A. Barros and Gregory Hinkle</i></p> <p>4.1 Background 39</p> <p>4.2 Target Assessments 40</p> <p>4.3 siRNA Design and Screening Strategies 41</p> <p>4.4 Safety Lead Optimization of siRNA 45</p> <p>4.5 Integration of Lead Optimization Data for Candidate Selection and Development 48</p> <p>4.6 Conclusions 49</p> <p>References 49</p> <p><b>PART III BASIS FOR </b><b><i>IN VITRO–IN VIVO </i></b><b>PK TRANSLATION 53</b></p> <p><b>5 Physicochemistry and the Off</b><b>‐</b><b>Target Effects of Drug Molecules 55<br /> </b><i>Dennis A. Smith</i></p> <p>5.1 Lipohilicity, Polar Surface Area, and Lipoidal Permeability 55</p> <p>5.2 Physicochemistry and Basic ADME Properties for High Lipoidal Permeability Drugs 56</p> <p>5.3 Relationship between Volume of Distribution (<b><i>V</i></b>d) and Target Access for Passively Distributed Drugs 58</p> <p>5.4 Basicity, Lipophilicity, and Volume of Distribution as a Predictor of Toxicity (T): Adding The T to ADMET 59</p> <p>5.5 Basicity and Lipophilicity as a Predictor of Toxicity (T): Separating the D from T in ADMET 60</p> <p>5.6 Lipophilicity and PSA as a Predictor of Toxicity (T): Adding the T to ADMET 60</p> <p>5.7 Metabolism and Physicochemical Properties 61</p> <p>5.8 Concentration of Compounds by Transporters 61</p> <p>5.9 Inhibition of Excretion Pumps 63</p> <p>5.10 Conclusions 64</p> <p>References 65</p> <p><b>6 The Need for Human Exposure Projection in the Interpretation of Preclinical </b><b><i>In Vitro </i></b><b>and </b><b><i>In Vivo </i></b><b>ADME Tox Data 67<br /> </b><i>Patrick Poulin</i></p> <p>6.1 Introduction 67</p> <p>6.2 Methodology Used for Human PK Projection in Drug Discovery 67</p> <p>6.3 Summary of the Take‐Home Messages from the Pharmaceutical Research and Manufacturers of America Cpcdc Initiative on Predictive Models of Human PK from 2011 72</p> <p>Abbreviations 77</p> <p>References 77</p> <p><b>7 A DME Properties Leading to Toxicity 82<br /> </b><i>Katya Tsaioun</i></p> <p>7.1 Introduction 82</p> <p>7.2 The Science of ADME 83</p> <p>7.3 The ADME Optimization Strategy 83</p> <p>7.4 Conclusions and Future Directions 89</p> <p>References 90</p> <p><b>PART IV Predicting Organ Toxicity 93</b></p> <p><b>8 Liver 95<br /> </b><i>J. Gerry Kenna, Mikael Persson, Scott Q. Siler, Ke Yu, Chuchu Hu, Minjun Chen, Joshua Xu, Weida Tong, Yvonne Will and Michael D. Aleo</i></p> <p>8.1 Introduction 95</p> <p>8.2 DILI Mechanisms and Susceptibility 96</p> <p>8.3 Common Mechanisms that Contribute to DILI 98</p> <p>8.4 Models Systems Used to Study DILI 108</p> <p>8.5 <i>In Silico </i>Models 114</p> <p>8.6 Systems Pharmacology and DILI 118</p> <p>8.7 Summary 119</p> <p>References 121</p> <p><b>9 Cardiac 130<br /> </b><i>David J. Gallacher, Gary Gintant, Najah Abi</i><i>‐</i><i>Gerges, Mark R. Davies, Hua Rong Lu, Kimberley M. Hoagland, Georg Rast, Brian D. Guth, Hugo M. Vargas and Robert L. Hamlin</i></p> <p>9.1 General Introduction 130</p> <p>9.2 Classical <i>In Vitro/Ex Vivo </i>Assessment of Cardiac Electrophysiologic Effects 133</p> <p>9.3 Cardiac Ion Channels and <i>In Silico </i>Prediction 137</p> <p>9.4 From Animal <i>Ex Vivo/In Vitro </i>Models to Human Stem Cell‐Derived Cms for Cardiac Safety Testing 140</p> <p>9.5 <i>In Vivo </i>Telemetry Capabilities and Preclinical Drug Development 141</p> <p>9.6 Assessment of Myocardial Contractility in Preclinical Models 144</p> <p>9.7 Assessment of Large Versus Small Molecules in CV SP 147</p> <p>9.8 Patients do not Necessarily Respond to Drugs and Devices as do Genetically Identical, Young Mature, Healthy Mice! 148</p> <p>References 152</p> <p><b>10 Predictive </b><b><i>In Vitro </i></b><b>Models for Assessment of Nephrotoxicity and Drug–Drug Interactions </b><b><i>In Vitro </i></b>160<br /> <i>Lawrence H. Lash</i></p> <p>10.1 Introduction 160</p> <p>10.2 Biological Processes and Toxic Responses of the Kidneys that are Normally Measured in Toxicology Research and Drug Development Studies 163</p> <p>10.3 Primary Cultures of hPT Cells 164</p> <p>10.4 Toxicology Studies in hPT Primary Cell Cultures 166</p> <p>10.5 Critical Studies for Drug Discovery in hpt Primary Cell Cultures 168</p> <p>10.6 S ummary and Conclusions 168</p> <p>References 170</p> <p><b>11 Predicting Organ Toxicity </b><b><i>In Vitro</i></b><b>: Bone Marrow 172<br /> </b><i>Ivan Rich and Andrew J. Olaharski</i></p> <p>11.1 Introduction 172</p> <p>11.2 Biology of the Hematopoietic System 172</p> <p>11.3 Hemotoxicity 173</p> <p>11.4 Measuring Hemotoxicity 173</p> <p>11.5 The Next Generation of Assays 175</p> <p>11.6 Proliferation or Differentiation? 175</p> <p>11.7 Measuring and Predicting Hemotoxicity <i>In Vitro </i>176</p> <p>11.8 Detecting Stem and Progenitor Cell Downstream Events 177</p> <p>11.9 Bone Marrow Toxicity Testing During Drug Development 177</p> <p>11.10 Paradigm for <i>In Vitro </i>Hemotoxicity Testing 178</p> <p>11.11 Predicting Starting Doses for Animal and Human Clinical Trials 179</p> <p>11.12 Future Trends 179</p> <p>11.13 Conclusions 180</p> <p>References 180</p> <p><b>12 Predicting Organ Toxicity </b><b><i>In Vitro</i></b><b>: Dermal Toxicity 182<br /> </b><i>Patrick J. Hayden, Michael Bachelor, Mitchell Klausner and Helena Kandárová</i></p> <p>12.1 Introduction 182</p> <p>12.2 Overview of Drug‐Induced Adverse Cutaneous Reactions 182</p> <p>12.3 Overview of <i>In Vitro </i>Skin Models with Relevance to Preclinical Drug Development 183</p> <p>12.4 Specific Applications of <i>In Vitro </i>Skin Models and Predictive <i>In Vitro </i>Assays Relevant to Pharmaceutical Development 184</p> <p>12.5 Mechanism‐Based Cutaneous Adverse Effects 187</p> <p>12.6 Summary 188</p> <p>References 189</p> <p><b>13 </b><b><i>In Vitro </i></b><b>Methods in Immunotoxicity Assessment 193<br /> </b><i>Xu Zhu and Ellen Evans</i></p> <p>13.1 Introduction and Perspectives on <i>In Vitro </i>Immunotoxicity Screening 193</p> <p>13.2 Overview of the Immune System 194</p> <p>13.3 Examples of <i>In Vitro </i>Approaches 196</p> <p>13.4 Conclusions 198</p> <p>References 199</p> <p><b>14 Strategies and Assays for Minimizing Risk of Ocular Toxicity during Early Development of Systemically Administered Drugs 201<br /> </b><i>Chris J. Somps, Paul Butler, Jay H. Fortner, Keri E. Cannon and Wenhu Huang</i></p> <p>14.1 Introduction 201</p> <p>14.2 <i>In Silico </i>and <i>In Vitro </i>Tools and Strategies 201</p> <p>14.3 Higher‐Throughput <i>In Vivo </i>Tools and Strategies 202</p> <p>14.4 S trategies, Gaps, and Emerging Technologies 208</p> <p>14.5 Summary 210</p> <p>References 210</p> <p><b>15 Predicting Organ Toxicity </b><b><i>In Vivo</i></b><b>—Central Nervous System 214<br /> </b><i>Greet Teuns and Alison Easter</i></p> <p>15.1 Introduction 214</p> <p>15.2 Models for Assessment of CNS ADRs 214</p> <p>15.3 S eizure Liability Testing 216</p> <p>15.4 Drug Abuse Liability Testing 218</p> <p>15.5 General Conclusions 222</p> <p>15.5.1 <i>In Vitro </i>222</p> <p>15.5.2 <i>In Vivo </i>223</p> <p>Abbreviations 223</p> <p>References 224</p> <p><b>16 Biomarkers, Cell Models, and </b><b><i>In Vitro </i></b><b>Assays for Gastrointestinal Toxicology 227<br /> </b><i>Allison Vitsky and Gina M. Yanochko</i></p> <p>16.1 Introduction 227</p> <p>16.2 A natomic and Physiologic Considerations 228</p> <p>16.3 GI Biomarkers 229</p> <p>16.4 Cell Models of the GI Tract 231</p> <p>16.5 Cell‐Based <i>In Vitro </i>Assays for Screening and Mechanistic Investigations to Gi Toxicity 235</p> <p>16.6 Summary/Conclusions/Challenges 236</p> <p>References 236</p> <p><b>17 Preclinical Safety Assessment of Drug Candidate</b><b>‐</b><b>Induced Pancreatic Toxicity: From an Applied Perspective 242<br /> </b><i>Karrie A. Brenneman, Shashi K. Ramaiah and Lauren M. Gauthier</i></p> <p>17.1 Drug‐Induced Pancreatic Toxicity 242</p> <p>17.2 Preclinical Evaluation of Pancreatic Toxicity 245</p> <p>17.3 Preclinical Pancreatic Toxicity Assessment: <i>In Vivo </i>247</p> <p>17.4 Pancreatic Biomarkers 249</p> <p>17.5 Preclinical Pancreatic Toxicity Assessment: <i>In Vitro </i>253</p> <p>17.6 Summary and Conclusions 257</p> <p>Acknowledgments 258</p> <p>References 258</p> <p><b>PART V A DDRESSING THE FALSE NEGATIVE SPACE—INCREASING</b></p> <p><b>PREDICTIVITY 261</b></p> <p><b>18 Animal Models of Disease for Future Toxicity Predictions 263<br /> </b><i>Sherry J. Morgan and Chandikumar S. Elangbam</i></p> <p>18.1 Introduction 263</p> <p>18.2 Hepatic Disease Models 264</p> <p>18.3 Cardiovascular Disease Models 268</p> <p>18.4 Nervous System Disease Models 270</p> <p>18.5 Gastrointestinal Injury Models 273</p> <p>18.6 Renal Injury Models 279</p> <p>18.7 Respiratory Disease Models 282</p> <p>18.8 Conclusion 285</p> <p>References 287</p> <p><b>19 The Use of Genetically Modified Animals in Discovery Toxicology 298<br /> </b><i>Dolores Diaz and Jonathan M. Maher</i></p> <p>19.1 Introduction 298</p> <p>19.2 Large‐Scale Gene Targeting and Phenotyping Efforts 299</p> <p>19.3 Use of Genetically Modified Animal Models in Discovery Toxicology 300</p> <p>19.4 The Use of Genetically Modified Animals in Pharmacokinetic and Metabolism Studies 303</p> <p>19.5 Conclusions 309</p> <p>References 309</p> <p><b>20 Mouse Population-Based Toxicology for Personalized Medicine and Improved Safety Prediction 314<br /> </b><i>Alison H. Harrill</i></p> <p>20.1 Introduction 314</p> <p>20.2 Pharmacogenetics and Population Variability 314</p> <p>20.3 Rodent Populations Enable a Population‐Based Approaches to Toxicology 316</p> <p>20.4 Applications for Pharmaceutical Safety Science 320</p> <p>20.5 Study Design Considerations for Genomic Mapping 322</p> <p>20.6 Summary 326</p> <p>References 326</p> <p><b>PART VI STEM CELLS IN TOXICOLOGY 331</b></p> <p><b>21 Application of Pluripotent Stem Cells in Drug</b><b>‐</b><b>Induced Liver Injury Safety Assessment 333<br /> </b><i>Christopher S. Pridgeon, Fang Zhang, James A. Heslop, Charlotte M.L. Nugues, Neil R. Kitteringham, B. Kevin Park and Christopher E.P. Goldring</i></p> <p>21.1 The Liver, Hepatocytes, and Drug‐Induced Liver Injury 333</p> <p>21.2 Current Models of Dili 334</p> <p>21.3 Uses of iPSC HLCs 338</p> <p>21.4 Challenges of Using ipscs and New Directions for Improvement 339</p> <p>21.5 Alternate Uses of HLCs in Toxicity Assessment 341</p> <p>References 342</p> <p><b>22 Human Pluripotent Stem Cell</b><b>‐</b><b>Derived Cardiomyocytes: A New Paradigm in Predictive Pharmacology and Toxicology 346<br /> </b><i>Praveen Shukla, Priyanka Garg and Joseph C. Wu</i></p> <p>22.1 Introduction 346</p> <p>22.2 A dvent of hPSCs: Reprogramming and Cardiac Differentiation 347</p> <p>22.3 iPSC‐Based Disease Modeling and Drug Testing 349</p> <p>22.4 Traditional Target‐Centric Drug Discovery Paradigm 354</p> <p>22.5 iPSC‐Based Drug Discovery Paradigm 354</p> <p>22.6 Limitations and Challenges 358</p> <p>22.7 Conclusions and Future Perspective 359</p> <p>Acknowledgments 360</p> <p>References 360</p> <p><b>23 Stem Cell</b><b>‐</b><b>Derived Renal Cells and Predictive Renal </b><b><i>In Vitro </i></b><b>Models 365<br /> </b><i>Jacqueline Kai Chin Chuah, Yue Ning Lam, Peng Huang and Daniele Zink</i></p> <p>23.1 Introduction 365</p> <p>23.2 Protocols for the Differentiation of Pluripotent Stem Cells into Cells of the Renal Lineage 367</p> <p>23.3 Renal <i>In Vitro </i>Models for Drug Safety Screening 376</p> <p>23.4 Achievements and Future Directions 378</p> <p>Acknowledgments 379</p> <p>Notes 379</p> <p>References 379</p> <p><b>PART VII CURRENT STATUS OF PRECLINICAL </b><b><i>IN VIVO </i></b><b>TOXICITY BIOMARKERS 385</b></p> <p><b>24 Predictive Cardiac Hypertrophy Biomarkers in Nonclinical Studies 387<br /> </b><i>Steven K. Engle</i></p> <p>24.1 Introduction to Biomarkers 387</p> <p>24.2 Cardiovascular Toxicity 387</p> <p>24.3 Cardiac Hypertrophy 388</p> <p>24.4 Diagnosis of Cardiac Hypertrophy 389</p> <p>24.5 Biomarkers of Cardiac Hypertrophy 389</p> <p>24.6 Case Studies 392</p> <p>24.7 Conclusion 392</p> <p>References 393</p> <p><b>25 Vascular Injury Biomarkers 397<br /> </b><i>Tanja S. Zabka and Kaïdre Bendjama</i></p> <p>25.1 Historical Context of Drug‐Induced Vascular Injury and Drug Development 397</p> <p>25.2 Current State of Divi Biomarkers 398</p> <p>25.3 Current Status and Future of <i>In Vitro </i>Systems to Investigate Divi 402</p> <p>25.4 Incorporation of <i>In Vitro </i>and <i>In Vivo </i>Tools in Preclinical Drug Development 403</p> <p>25.5 Divi Case Study 403</p> <p>References 403</p> <p><b>26 Novel Translational Biomarkers of Skeletal Muscle Injury 407<br /> </b><i>Peter M. Burch and Warren E. Glaab</i></p> <p>26.1 Introduction 407</p> <p>26.2 Overview of Drug‐Induced Skeletal Muscle Injury 407</p> <p>26.3 Novel Biomarkers of Drug‐Induced Skeletal Muscle Injury 409</p> <p>26.4 Regulatory Endorsement 411</p> <p>26.5 Gaps and Future Directions 411</p> <p>26.6 Conclusions 412</p> <p>References 412</p> <p><b>27 Translational Mechanistic Biomarkers and Models for Predicting Drug</b><b>‐</b><b>Induced Liver Injury : Clinical to </b><b><i>In Vitro </i></b><b>Perspectives 416<br /> </b><i>Daniel J. Antoine</i></p> <p>27.1 Introduction 416</p> <p>27.2 Drug‐Induced Toxicity and the Liver 417</p> <p>27.3 Current Status of Biomarkers for the Assessment of DILI 418</p> <p>27.4 Novel Investigational Biomarkers for DILI 419</p> <p>27.5 <i>In Vitro </i>Models and the Prediction of Human Dili 422</p> <p>27.6 Conclusions and Future Perspectives 423</p> <p>References 424</p> <p><b>PART VIII Kidney Injury Biomarkers 429</b></p> <p><b>28 Assessing and Predicting Drug</b><b>‐</b><b>Induced Kidney Injury, Functional Change, and Safety in Preclinical Studies in Rats 431<br /> </b><i>Yafei Chen</i></p> <p>28.1 Introduction 431</p> <p>28.2 Kidney Functional Biomarkers (Glomerular Filtration and Tubular Reabsorption) 433</p> <p>28.3 Novel Kidney Tissue Injury Biomarkers 435</p> <p>28.4 Novel Biomarkers of Kidney Tissue Stress Response 436</p> <p>28.5 Application of an Integrated Rat Platform (Automated Blood Sampling and Telemetry, Abst) for Kidney Function and Injury Assessment 437</p> <p>References 439</p> <p><b>29 Canine Kidney Safety Protein Biomarkers 443<br /> </b><i>Manisha Sonee</i></p> <p>29.1 Introduction 443</p> <p>29.2 Novel Canine Renal Protein Biomarkers 443</p> <p>29.3 Evaluations of Novel Canine Renal Protein Biomarker Performance 444</p> <p>29.4 Conclusion 444</p> <p>References 445</p> <p><b>30 Traditional Kidney Safety Protein Biomarkers and Next</b><b>‐</b><b>Generation Drug</b><b>‐</b><b>Induced Kidney Injury Biomarkers in Nonhuman Primates 446<br /> </b><i>Jean</i><i>‐</i><i>Charles Gautier and Xiaobing Zhou</i></p> <p>30.1 Introduction 446</p> <p>30.2 Evaluations of Novel Nhp Renal Protein Biomarker Performance 447</p> <p>30.3 New Horizons: Urinary MicroRNAs and Nephrotoxicity in Nhps 447</p> <p>References 447</p> <p><b>31 Rat Kidney MicroRNA Atlas 448<br /> </b><i>Aaron T. Smith</i></p> <p>31.1 Introduction 448</p> <p>31.2 Key Findings 448</p> <p>References 449</p> <p><b>32 MicroRNAs as Next</b><b>‐</b><b>Generation Kidney Tubular Injury Biomarkers in Rats 450<br /> </b><i>Heidrun Ellinger</i><i>‐</i><i>Ziegelbauer and Rounak Nassirpour</i></p> <p>32.1 Introduction 450</p> <p>32.2 Rat Tubular miRNAs 450</p> <p>32.3 Conclusions 451</p> <p>References 451</p> <p><b>33 MicroRNAs as Novel Glomerular Injury Biomarkers in Rats 452<br /> </b><i>Rachel Church</i></p> <p>33.1 Introduction 452</p> <p>33.2 Rat Glomerular miRNAs 452</p> <p>References 453</p> <p><b>34 Integrating Novel Imaging Technologies to Investigate Drug</b><b>‐</b><b>Induced Kidney Toxicity 454<br /> </b><i>Bettina Wilm and Neal C. Burton</i></p> <p>34.1 Introduction 454</p> <p>34.2 Overviews 455</p> <p>34.3 Summary 456</p> <p>References 456</p> <p><b>35 </b><b><i>In Vitro </i></b><b>to </b><b><i>In Vivo </i></b><b>Relationships with Respect to Kidney Safety Biomarkers 458<br /> </b><i>Paul Jennings</i></p> <p>35.1 Renal Cell Lines as Tools for Toxicological Investigations 458</p> <p>35.2 Mechanistic Approaches and <i>In Vitro </i>to <i>In Vivo </i>Translation 459</p> <p>35.3 Closing Remarks 460</p> <p>References 460</p> <p><b>36 Case Study: Fully Automated Image Analysis of Podocyte Injury Biomarker Expression in Rats 462<br /> </b><i>Jing Ying Ma</i></p> <p>36.1 Introduction 462</p> <p>36.2 Material and Methods 462</p> <p>36.3 Results 463</p> <p>36.4 Conclusions 465</p> <p>References 465</p> <p><b>37 Case Study: Novel Renal Biomarkers Translation to Humans 466<br /> </b><i>Deborah A. Burt</i></p> <p>37.1 Introduction 466</p> <p>37.2 Implementation of Translational Renal Biomarkers in Drug Development 466</p> <p>37.3 Conclusion 467</p> <p>References 467</p> <p><b>38 Case Study: Microrn as as Novel Kidney Injury Biomarkers in Canines 468<br /> </b><i>Craig Fisher, Erik Koenig and Patrick Kirby</i></p> <p>38.1 Introduction 468</p> <p>38.2 Material and Methods 468</p> <p>38.3 Results 468</p> <p>38.4 Conclusions 470</p> <p>References 470</p> <p><b>39 Novel Testicular Injury Biomarkers 471<br /> </b><i>Hank Lin</i></p> <p>39.1 Introduction 471</p> <p>39.2 The Testis 471</p> <p>39.3 Potential Biomarkers for Testicular Toxicity 472</p> <p>39.4 Conclusions 473</p> <p>References 473</p> <p><b>PART IX Best Practices in Biomarker Evaluations 475</b></p> <p><b>40 Best Practices in Preclinical Biomarker Sample Collections 477<br /> </b><i>Jaqueline Tarrant</i></p> <p>40.1 Considerations for Reducing Preanalytical Variability in Biomarker Testing 477</p> <p>40.2 Biological Sample Matrix Variables 477</p> <p>40.3 Collection Variables 480</p> <p>40.4 Sample Processing and Storage Variables 480</p> <p>References 480</p> <p><b>41 Best Practices in Novel Biomarker Assay Fit</b><b>‐</b><b>for</b><b>‐</b><b>Purpose Testing 481<br /> </b><i>Karen M. Lynch</i></p> <p>41.1 Introduction 481</p> <p>41.2 Why Use a Fit‐for‐Purpose Assay? 481</p> <p>41.3 Overview of Fit‐for‐Purpose Assay Method Validations 482</p> <p>41.4 Assay Method Suitability in Preclinical Studies 482</p> <p>41.5 Best Practices for Analytical Methods Validation 482</p> <p>41.6 Species‐ and Gender‐Specific Reference Ranges 486</p> <p>41.7 Analyte Stability 487</p> <p>41.8 Additional Method Performance Evaluations 487</p> <p>References 487</p> <p><b>42 Best Practices in Evaluating Novel Biomarker Fit for Purpose and Translatability 489<br /> </b><i>Amanda F. Baker</i></p> <p>42.1 Introduction 489</p> <p>42.2 Protocol Development 489</p> <p>42.3 Assembling an Operations Team 489</p> <p>42.4 Translatable Biomarker Use 490</p> <p>42.5 Assay Selection 490</p> <p>42.6 Biological Matrix Selection 490</p> <p>42.7 Documentation of Patient Factors 491</p> <p>42.8 Human Sample Collection Procedures 491</p> <p>42.9 Choice of Collection Device 491</p> <p>42.10 Schedule of Collections 492</p> <p>42.11 Human Sample Quality Assurance 492</p> <p>42.12 Logistics Plan 493</p> <p>42.13 Database Considerations 493</p> <p>42.14 Conclusive Remarks 493</p> <p>References 493</p> <p><b>43 Best Practices in Translational Biomarker Data Analysis 495<br /> </b><i>Robin Mogg and Daniel Holder</i></p> <p>43.1 Introduction 495</p> <p>43.2 Statistical Considerations for Preclinical Studies of Safety Biomarkers 496</p> <p>43.3 Statistical Considerations for Exploratory Clinical Studies of Translational Safety Biomarkers 497</p> <p>43.4 Statistical Considerations for Confirmatory Clinical Studies of Translational Safety Biomarkers 498</p> <p>43.5 Summary 498</p> <p>References 498</p> <p><b>44 Translatable Biomarkers in Drug Development: Regulatory Acceptance and Qualification 500<br /> </b><i>John</i><i>‐</i><i>Michael Sauer, Elizabeth G. Walker and Amy C. Porter</i></p> <p>44.1 Safety Biomarkers 500</p> <p>44.2 Qualification of Safety Biomarkers 501</p> <p>44.3 Letter of Support for Safety Biomarkers 502</p> <p>44.4 Critical Path Institute’s Predictive Safety Testing Consortium 502</p> <p>44.5 Predictive Safety Testing Consortium and its Key Collaborations 504</p> <p>44.6 Advancing the Qualification Process and Defining Evidentiary Standards 505</p> <p>References 506</p> <p><b>PART X Conclusions 509</b></p> <p><b>45 Toxicogenomics in Drug Discovery Toxicology: History, Methods, Case Studies, and Future Directions 511<br /> </b><i>Brandon D. Jeffy, Joseph Milano and Richard J. Brennan</i></p> <p>45.1 A Brief History of Toxicogenomics 511</p> <p>45.2 Tools and Strategies for Analyzing Toxicogenomics Data 513</p> <p>45.3 Drug Discovery Toxicology Case Studies 519</p> <p>References 525</p> <p><b>46 Issue Investigation and Practices in Discovery Toxicology 530<br /> </b><i>Dolores Diaz, Dylan P. Hartley and Raymond Kemper</i></p> <p>46.1 Introduction 530</p> <p>46.2 Overview of Issue Investigation in the Discovery Space 530</p> <p>46.3 Strategies to Address Toxicities in the Discovery Space 532</p> <p>46.4 Cross‐Functional Collaborative Model 533</p> <p>46.5 Case‐Studies of Issue Resolution in The Discovery Space 536</p> <p>46.6 Data Inclusion in Regulatory Filings 538</p> <p>References 538</p> <p><b>ABBREVIATIONS 540</b></p> <p><b>CONCLUDING REMARKS 542</b></p> <p><b>INDEX 543</b></p>
<p><b>Yvonne Will, PhD,</b> is a Senior Director and the Head of Science and Technology Strategy, Drug Safety Research and Development at Pfizer, Connecticut, USA. She co-edited the book <i>Drug-Induced Mitochondrial Dysfunction</i>, published by Wiley in 2008.<br /><b><br />J. Eric McDuffie, PhD,</b> is the Director of the Discovery / Investigative Toxicology and Laboratory Animal Medicine groups at Janssen Research & Development, California, USA.<br /><b><br />Andrew J. Olaharski, PhD,</b> is an Associate Director of Toxicology at Agios Pharmaceuticals, Massachusetts, USA.<br /><b><br />Brandon D. Jeffy, PhD,</b> is a Senior Principal Scientist in the Exploratory Toxicology division of Nonclinical Development at Celgene Pharmaceuticals, California, USA.</p>
<p>Developing novel pharmaceuticals requires nonclinical safety studies on candidate drugs to assess general toxicology (through in vivo experiments), safety pharmacology (effects on major organ systems), and genetic toxicity tests. These data provide risk assessment data that supports progression of candidate drugs from discovery phase through clinical development, to regulatory submission and registration. Traditionally, however, less emphasis was placed on the evaluation of safety issues for projects while still in the drug design phase.</p> <p>In response to this costly attrition, many pharmaceutical companies invested in “drug discovery toxicology” or “drug discovery safety” to identify hazards and take steps to design out or significantly reduce undesirable safety liabilities earlier; with the ultimate aim of enhancing the probability of success in non-clinical and clinical drug development. Because of this, there is a strong need for personnel involved with toxicology and pharmacology studies need to understand the varied tools and approaches to perform early drug discovery safety analysis.</p> <p><i>Drug Discovery Toxicology: From Target Assessment to Translational Biomarkers</i> serves as a valuable tool for those discovery scientists. The authors, writing from firsthand industry experience, give readers insight into the strategy and execution of predictive toxicology practices, including what experiments are possible and useful. In addition, they offer a view into the future, indicating key areas to watch for new predictive methods. Broken into different sections, the book deals with the key topics – Safety Lead Optimization Strategies, In Vitro-In Vivo Pharmacokinetics Translation, Predicting Organ Toxicity In Vitro, False Negative Space, --Omics in Predictive Toxicology, Translational Biomarkers, and Signal Investigation Rationale and Practices.</p> <p>As a guide for pharmaceutical professionals to the issues and practices of drug discovery toxicology, this book integrates and reviews the strategy and application of tools and methods throughout the pre-clinical drug discovery development process.</p>

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