Accelerating Lead Generation:
Emerging technologies and strategies
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| Overview: | |
| It is well documented that productivity in the pharma industry is in decline. Over the past 15 years the number of new drug applications (NDAs) and biologics license applications (BLAs) approved has fallen steadily, despite an ever increasing R&D spend. In drug discovery, the lead generation process takes the company’s library of available compounds and narrows down the number of potential candidates through a process of elimination. Lead generation is achieved through a process of ‘hit’ finding using high throughput screening, followed by hit verification and optimization. Hits and leads should fulfill a range of important criteria, although the exact criteria will depend on the company and the project. The earliest hit finding processes focus solely on potency, but projects will rapidly widen their efforts to include more parameters including chemistry factors, pharmacology and absorption/distribution/ metabolism/elimination and toxicology. Innovations in the assessment of each of these areas that aim to miniaturize assays to increase their throughput and reduce costs are the focus of this report. |
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| Keywords: Lead generation, Hit and lead profiling, HTS, Virtual screening, Fragment based drug discovery, Cheminformatic, Toxicogenomics, Systems biology, Label-free assay technologies, Cell-based screening, | |
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By Dr Cheryl L Barton / Publication Date: 1st June 2009
Contents:
Executive Summary 10
Introduction 10
Identifying hits: library design, virtual screening and fragment based
drug discovery 11
Innovations in biological assay development 12
ADME and toxicology in lead generation 13
Lead generation strategies in the pharma industry 14
R&D models, innovation and future success of lead generation 15
Chapter 1 Introduction 18
The drug discovery process: defining lead generation 20
Hit finding and verification 21
Hit optimization 22
Lead optimization 23
Criteria for potential lead compounds 24
Chemistry 24
Pharmacology 24
Absorption, Metabolism, Excretion, Distribution (ADME) and
Toxicity 24
Chapter 2 Identifying hits: library design,
virtual screening and fragment
based drug discovery 28
Summary 28
Introduction 29
Hit to lead – identifying possible structures 30
Compound selection 30
Physiochemical properties 30
Chemical optimization and modification of hits 32
Engineering novelty 33
Beyond HTS – alternative methods for identifying hits 35
Fragment-based drug discovery 36
Companies involved in FBDD 39
Case study: deCODE chemistry & biostructures Inc 40
Case study: Zenobia Therapeutics 41
Can FBDD generate successful new drugs? 42
Technology improvements driving FBDD 43
Improving x-ray crystallography 43
Improvements in NMR spectroscopy for FBDD 47
High concentration biological assays 49
Improving biophysical methods 50
Improving fragment library design 50
Chemistry-based methods 52
HTS vs FBDD 53
Virtual screening 53
Target based virtual screening 54
Case study: Epix Pharmaceuticals’ 55
When to use virtual screening 56
Target based virtual screening: challenges 56
Ligand based screening 57
Commercial virtual screening platforms 58
Conclusions 60
Chapter 3 Innovations in biological assay
development 64
Summary 64
Introduction 65
Improving high throughput screening 66
Identifying valid hits 66
A quantitative approach to primary screening 67
Compound management and quality assessment 68
Dispensing 69
Informatics and data analysis 70
Improving in vitro assays for HTS 71
Surface plasmon resonance 73
Isothermal titration calorimetry and nanocalorimetry 76
Back-Scattering Interferometry 77
Differential scanning fluorimetry 78
High throughput Mass Spectrometry 79
Bio-layer interferometry 80
Innovations in cell-based assay technology 82
Automated confocal microscopy methods 83
Flow cytometry 86
Laser scanning cytometry 87
Label-free cell-based screens 88
Photonic crystal biosensors 88
Dynamic mass redistribution 89
Impedance-based whole cell biosensors 89
Other cell-based assays 90
Reverse arrays 90
Enzyme Fragment Complementation 91
HCS and SAR 93
Novel cell types and cultures 94
In vivo methods in lead generation 96
Zebrafish 96
Whole animal imaging and microscopy 99
Conclusions 103
Chapter 4 ADME and toxicology in lead
generation 106
Summary 106
Introduction 107
Assessing ADME characteristics 108
Oral absorption 108
P-Glycoprotein interactions 109
Plasma protein binding 109
Clearance 110
Metabolic stability 110
Selectivity and off-target effects 110
Solubility 111
Toxicology at the lead generation stage 111
In silico structure-toxicity relationships 111
Chemoinformatic methods 113
Toxicogenomics 116
High content screening 118
Zebrafish 121
Whole animal imaging 122
Determining mutagenic and clastogenic potential 123
Measuring HERG liability 125
Investigating CYP inhibition and induction 126
Conclusions 127
Chapter 5 Lead generation strategies in the
pharma industry 130
Summary 130
Introduction 131
Lead generation teams 132
Case studies 134
Bayer 134
Boehringer Ingelheim 135
Millennium Pharmaceuticals (Takeda) 137
Conclusions 137
Chapter 6 R&D models, innovation & future
success of lead generation 140
Summary 140
Introduction 141
R&D models: influence on lead generation 141
R&D models 141
Outsourcing and offshoring 142
Dealing with academia 145
Pharma collaboration – ‘Co-opetition’ 146
Innovation and the future 147
Targets and HTS 147
Focus on RNA 148
Focus on lead optimization 149
Nanochemistry – returning chemistry to its central role in drug discovery 149
Lead generation now and in the future 153
Chapter 7 Appendix 155
Primary research methodology 155
Acknowledgments 156
Glossary 157
Index 160
Bibliography 161
List of Tables:
List of Figures
Figure 1.1: Pharma industry productivity decline (1999-2008) 19
Figure 1.2: Patent losses occurring between 2008-2014 20
Figure 1.3: The drug discovery process 21
Figure 1.4: Example of a lead generation workflow 23
Figure 1.5: Technologies involved in lead generation 25
Figure 2.6: Use of structural information in structure-based drug design 36
Figure 2.7: Examples of the chemical structures of compounds discovered using FBDD 42
Figure 2.8: ZoBio’s target immobilized NMR spectroscopy method for fragment-based drug
discovery 48
Figure 3.9: Areas of innovation in high throughput screening 66
Figure 3.10: Acoustic droplet ejection 69
Figure 3.11: Attributes required of software for HTS data storage and analysis 71
Figure 3.12: Kinetic characterization of 5 lead series using SPR (Biacore) 75
Figure 3.13: Bio-Layer Interferometry from ForteBio 81
Figure 3.14: Advantages of cell-based screening in HTS 82
Figure 3.15: Principle of detection: cell based assays with the Epic system from Corning 89
Figure 3.16 Principle of the EFC assay for a biochemical target: HitHunter from DiscoveRx 93
Figure 4.17: ADME and toxicology data available in high throughput assays 107
Figure 4.18: The Safety Intelligence Program from BioWisdom 114
Figure 4.19: Examples of assertions in the Safety Intelligence Program from BioWisdom 114
Figure 4.20: A typical toxicogenomics workflow in the pharma industry 117
Figure 5.21: Key innovations in lead generation technologies 131
Figure 5.22: Key activities of medicinal chemists during lead generation 133
Figure 5.23: ADME-Tox traffic light criteria in use at Bayer 134
Figure 5.24: Discovery-Assays-By-Stage paradigm of Millennium Pharmaceuticals 137
Figure 6.25: The microreactor-based lead discovery system 151
List of Tables
Table 2.1: Fragment-based drug discovery: the pros and cons 37
Table 2.2 Techniques used to assess fragment binding for FBDD 39
Table 2.3: Examples of companies with product pipelines derived from FBDD 40
Table 2.4: Examples of compounds discovered using FBDD 43
Table 2.5: Rule of Three criteria for a fragment library 50
Table 2.6: Examples of companies offering fragment libraries and collections for FBDD 51
Table 2.7: Examples of companies offering software for virtual screening 59
Table 3.8: Examples of companies providing software for HTS information storage and analysis
71
Table 3.9: Emerging technologies for high throughput screening 73
Table 3.10: A comparison of free-solution, label-free molecular interaction techniques 78
Table 3.11: Examples of recent collaborations between stem cell companies and big pharma for the
use of stem cells in drug discovery research 96
Table 3.12: Advantages and disadvantages of zebrafish for compound screening 97
Table 3.13: Companies offering zebrafish screening products and services 98
Table 3.14: Advantages of molecular imaging of whole animals for preclinical studies 101
Table 3.15: Half lives of important positron emitting isotopes 102
Table 4.16: Examples of contract laboratories offering HCA cytotoxicity screening 119
Table 4.17: Examples of higher throughput or miniaturized versions of the Ames test 124
Table 6.18: Recent examples of academic drug discovery funding by big pharma 146