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The Handbook of Medicinal Chemistry

Principles and Practice


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The Handbook of Medicinal Chemistry
08:35:55.
Published on 09 December 2014 on | doi:10.1039/9781782621836-FP001

Principles and Practice

Edited by
Andrew Davis
AstraZeneca, Mo¨lndal, Sweden
Email:

Simon E Ward
University of Sussex, Brighton, UK
Email:

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Print ISBN: 978-1-84973-625-1
PDF eISBN: 978-1-78262-183-6
A catalogue record for this book is available from the British Library
r The Royal Society of Chemistry 2015
All rights reserved
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Regulations 2003, this publication may not be reproduced, stored or transmitted, in any form or by any means,
without the prior permission in writing of The Royal Society of Chemistry or the copyright owner, or in the case of
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The RSC is not responsible for individual opinions expressed in this work.
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Preface
Medicinal Chemistry sits at the heart of the pharmaceutical industry and the medicinal
chemist has one of the most challenging and rewarding jobs imaginable. The medicinal
chemist designs the drug which must balance often conflicting demands of a suitable dose,
by the chosen delivery route, at a desired dose frequency to provide a therapeutic effect while
maintaining margins to adverse effects throughout the dosing period. The drug molecule
may be given to millions of patients all of whom may respond to the drug differently, and all
of whom must be treated safely and effectively. Whilst drug discovery is undoubtedly an endeavour involving a wide range of scientific disciplines, the medicinal chemists are critical to
the design and progression of a drug molecule. It is the medicinal chemist who integrates
and balances the diverse inputs into a single chemical structure which has the potential to
become a new medicine.
This is an enormously difficult task. Our advances in synthetic organic chemistry mean that
we can respond well to the challenges of preparing and purifying new molecules and chemists
can be trained in these skills during undergraduate and graduate studies. In contrast, compound design is far harder to control and requires extensive experience and knowledge to take
the sometimes subjective decisions to arrive at a potential drug candidate. There are few universal rules in drug design, and barely any universally accepted guidelines, and it sometimes
seems success is more a matter of chance. But, as Louis Pasteur said, ‘‘chance favours the
prepared mind’’. However, given the current challenges and high attrition during the development phase, and the acceptance that many reasons for failure are directly attributable to the
chemical structure of the drug candidate, medicinal chemists have a duty to design the best
molecule possible to advance from research into development and beyond.
The aim of this book, through a series of monographs by leading scientists from across the
world, from major pharmaceutical companies, biotechnology companies, contract research
organisations and academia is to prepare the medicinal chemist to spot the good chances.
The book covers the whole R&D process from target validation through to late stage clinical
trials, through descriptions of the background science, the process, learnings, case studies,
leading references and even hints and tips.
The foreword has been written by one of our industry’s most respected scientists, Simon
Campbell CBE FRS, FMedSci. Simon Campbell joined Pfizer as a Medicinal Chemist in 1972,
and was a key member of the teams that led to such blockbuster drugs as Cardura, Norvasc and

Viagra. He went on to become Pfizer’s Senior Vice President for World-wide Drug Discovery and
Medicinal R&D in Europe. He was President of the Royal Society of Chemistry from 2004 to 2006
The Handbook of Medicinal Chemistry: Principles and Practice
Edited by Andrew Davis and Simon E Ward
r The Royal Society of Chemistry 2015
Published by the Royal Society of Chemistry, www.rsc.org

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Preface

and maintains a very active and influential role in our industry. With his considerable experience Simon provides us with his personal learnings, and the undoubted opportunities for
medicinal chemistry looking forward.
The early chapters describe the tools of the medicinal chemist’s trade such as physical organic chemistry, computational chemistry and QSAR, library design, fragment based lead
generation and structure based design.
The middle section of the book covers the supporting scientific disciplines, including assay
development, receptor pharmacology and in vivo model development, drug metabolism and
pharmacokinetics, molecular biology, toxicology and translational science, computational
biology and of critical importance, intellectual property.
The later sections of the book describe the overall research and development process from
target generation, lead identification and optimisation through to pharmaceutical development, clinical development and chemical development, including the importance of efficient
project management.

Due to the high levels of failure faced during drug development, case studies of successful
R&D are hard to find, but are invaluable as a touchstone for pathways to success. So the last
three chapters provide case studies of drugs that made it into the later stages of clinical development and/or onto the market, Brilinta, Aleglitazar and Lapatinib. Even during the preparation of this book, one of our case studies was unfortunately halted during Phase III trials. As
sad as Phase III failure is, few drugs reach this stage of clinical development and there are many
lessons to be learnt in this story that justify its esteemed place in this section.
The book began as life as a proposal to update to a 3rd edition the Royal Society of
Chemistry’s long running publication ‘‘Principles and Practice of Medicinal Chemistry’’.
The first edition was published over 20 years ago, and was a spin-out from the biannual
Royal Society of Chemistry Medicinal Chemistry Summer Workshop, which itself has been
running for over 40 years and has been the training ground for many of our industry’s leading
medicinal chemists. The 3rd edition proposal retained some distinctive features of its predecessors, being highly practitioner focused, but grew to incorporate a broader context and
to reflect the changing reader demographic reflected in the changing industry and drug
discovery environments. It also grew to incorporate new opportunities that did not exist
20 years ago.
Paper publishing is as valid today as it has ever been, but mobile computing and e-publishing
are changing the way information can be used and presented. E-publications allow interaction
with the content which cannot occur with paper. App-stores allow easy access to sophisticated
software that can be delivered and updated with ease. Many tools potentially useful to medicinal
chemists do not exist in an easily accessible and secure manner. So for the 3rd edition we wanted
to develop, as a companion to the print book, a set of useful medicinal chemistry apps to run
locally on tablet computers, and also a fully interactive e-book version to complement the paper
copy. The apps would bring to life concepts described within the book chapters and allow
chemists to quickly and easily find help in their design challenges.
While even 10 years ago protein structure visualisation and small molecule modelling required high-end workstations and costly software, nowadays this can be accomplished on a
tablet computer. Indeed, the frontispiece image of this book was designed inside the freeware
app iMolview from Molsoft on an Apple iPad3. Similarly static pictures of X-ray crystal structures
within the chapters can be brought into high resolution reality, and the reader can interact with
the exact data that the original medicinal chemist used in the documented design. Structures
can link to ChemSpider or even Wikipedia and other online resources providing deeper context,
and hyperlinks to regulatory guidance mean the medicinal chemist has access to primary information sources relevant to each chapter.



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Preface

vii

So while this 3rd edition was inspired by its predecessors, with the companion apps and the
e-book format, it was time to change the book’s name. We hoped the book would become an
everyday companion for the practicing medicinal chemist, and so the title ‘‘Handbook of
Medicinal Chemistry’’ seemed appropriate. With both print and electronic format and
companion apps we hope that, with this handbook, we can more fully prepare the mind of the
medicinal chemist to pick the right chances.
Andrew Davis and Simon E Ward


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Contents

Introduction
Chapter 1

xxiii

Physicochemical Properties and Compound Quality
M. Paul Gleeson, Paul D. Leeson and Han van de Waterbeemd
1.1
1.2

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Physicochemical Properties . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.1 Lipophilicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.2 Calculating log P and log D7.4 . . . . . . . . . . . . . . . . . . .
1.2.3 Ionisation Constants . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.4 Hydrogen Bonding . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.5 Solubility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.6 Measurement of Solubility. . . . . . . . . . . . . . . . . . . . . .
1.2.7 Calculating Solubility . . . . . . . . . . . . . . . . . . . . . . . . .
1.2.8 Other Compound Quality Indicators . . . . . . . . . . . . . .
1.3 Compound Quality and Drug-likeness . . . . . . . . . . . . . . . . . .
1.3.1 The Rule of Five, and Other Physical Properties. . . . . .
1.3.2 ADME and Physicochemical Properties . . . . . . . . . . . .
1.3.3 Toxicity and Physicochemical Properties . . . . . . . . . . .
1.3.4 Effect of Time on Oral Drug Properties . . . . . . . . . . . .
1.3.5 Non-Oral Drug Properties . . . . . . . . . . . . . . . . . . . . . .
1.3.6 Effect of Target Class . . . . . . . . . . . . . . . . . . . . . . . . .
1.3.7 Effect of the Individual Chemist and the Organisation.
1.3.8 ‘Exception’ Space . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.4 The Drug Discovery Process: Does It Unknowingly Introduce

A Bias In Molecular Properties? . . . . . . . . . . . . . . . . . . . . . . .
1.4.1 Ligand Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.4.2 Multi-Objective Parameter Optimisation . . . . . . . . . . .
1.5 Hints and Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.6 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The Handbook of Medicinal Chemistry: Principles and Practice
Edited by Andrew Davis and Simon E Ward
r The Royal Society of Chemistry 2015
Published by the Royal Society of Chemistry, www.rsc.org

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Chapter 2

Contents

Parallel Synthesis and Library Design
Andy Merritt

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2.1
2.2
2.3
2.4
2.5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Start of Combichem in Drug Discovery . . . . . . . . . . . . . . . . . .
From Peptides to Small Molecules . . . . . . . . . . . . . . . . . . . . . . . . .
My Library’s Bigger than Your Library—the ‘Universal’ Library . . . .
From Combichem to High Throughput Chemistry—Remembering
it’s All About Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Realising a Collection—Technology Development and Commercial
Offerings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.7 Design Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.8 Diversity Collections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.9 Targeted Libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.10 Combinatorial Power in Design . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.11 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 3

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Useful Computational Chemistry Tools for Medicinal Chemistry

Darren V. S. Green

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3.1
3.2

Physics Based vs. Empirical Models . . . . . . . . . . . . . . . . . . . . . . .
Molecular Mechanics and Molecular Orbital Theory . . . . . . . . . . .
3.2.1 Quantum Mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.2 Molecular Mechanics . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3 Electronic Distribution and Electrostatic Isopotentials . . . .
3.2.4 Dimensional Molecular Similarity . . . . . . . . . . . . . . . . . . .
3.2.5 Energy Minimisation. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Molecular Simulation and Dynamics . . . . . . . . . . . . . . . . . . . . . .
3.4 Modelling Solvation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5 Conformations, Conformational Energy and Drug Design. . . . . . .
3.6 Quantifying Molecular Interactions from Experimental Data. . . . .
3.7 Docking and Scoring Functions . . . . . . . . . . . . . . . . . . . . . . . . . .
3.8 Examples of Impactful Computational Chemistry on Drug Design
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 4

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Structure-Based Design for Medicinal Chemists
Jeff Blaney and Andrew M. Davis
4.1
4.2
4.3
4.4
4.5
4.6
4.7
4.8
4.9

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Interpreting X-ray Crystal Structures . . . . . . . . . . . . . . . . .
Visualizing Shape Complementarity . . . . . . . . . . . . . . . . .

What Drives Binding? . . . . . . . . . . . . . . . . . . . . . . . . . . .
Enthalpy–Entropy Compensation . . . . . . . . . . . . . . . . . . .
Small Molecules Bind in Their Lowest Energy, Preferred
Conformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Preferred Protein–Ligand Interactions . . . . . . . . . . . . . . .
Hydrogen Bonds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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4.10
4.11

Electrostatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Hypothesis-based Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.11.1 Polar Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.11.2 Interactions at the Entrance to a Binding Site . . . . . . .
4.11.3 Self-Fulfilling Prophecy: The Local Minimum Problem .
4.12 Case Study: Nitric Oxide Synthase . . . . . . . . . . . . . . . . . . . . . .
4.13 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 5

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Fragment Based Lead Discovery
Roderick E. Hubbard
5.1
5.2
5.3
5.4


Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The General Features of FBLD . . . . . . . . . . . . . . . . . . . . . . . .
Fragment Library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fragment Screening Approaches. . . . . . . . . . . . . . . . . . . . . . .
5.4.1 Protein-Observed NMR. . . . . . . . . . . . . . . . . . . . . . . .
5.4.2 Ligand-Observed NMR . . . . . . . . . . . . . . . . . . . . . . . .
5.4.3 Surface Plasmon Resonance (SPR) . . . . . . . . . . . . . . .
5.4.4 Thermal Shift Analysis (TSA) or Differential Scanning
Fluorimetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4.5 Biochemical Assay . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4.6 Crystallography . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4.7 Mass Spectrometry. . . . . . . . . . . . . . . . . . . . . . . . . . .
5.4.8 Isothermal Titration Calorimetry (ITC) . . . . . . . . . . . .
5.4.9 Other Ideas and Approaches . . . . . . . . . . . . . . . . . . .
5.4.10 Validating Fragment Hits—Comparing Methods . . . .
5.5 Fragment Hit Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5.1 Hits vs. Non-Hits . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5.2 Hits for Different Types of Target. . . . . . . . . . . . . . . .
5.6 Determining Structures of Fragments Bound . . . . . . . . . . . . .
5.7 The Evolution of the Ideas and Methods—A Historical
Perspective. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.7.1 Some Early Ideas . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.7.2 The Emergence of De Novo Structure-Based Design . .
5.7.3 The Emergence of Fragment-Based Lead Discovery. . .
5.7.4 Some Important Underpinning Concepts . . . . . . . . . .
5.8 Fragment Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.9 Fragments and Chemical Space . . . . . . . . . . . . . . . . . . . . . . .
5.10 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 6

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Quantitative Structure–Activity Relationships
Andrew M. Davis


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6.1
6.2
6.3

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157

Quantitative Structure–Activity Relationships in Drug Design SAR. . . .
Brief History of QSAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
QSAR Model Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


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6.4

The Language of QSAR: Descriptors, Machine Learning Methods
and Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.4.1 An Unambiguous Endpoint—the Biological Response . . . . .

6.4.2 The Numerical Descriptors of Chemical Constitution. . . . . .
6.4.3 Preparation of the Dataset. . . . . . . . . . . . . . . . . . . . . . . . . .
6.4.4 Exploring the Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.4.5 Case Study: D2/b2 Agonists . . . . . . . . . . . . . . . . . . . . . . . . .
6.4.6 Building the QSAR Model . . . . . . . . . . . . . . . . . . . . . . . . . .
6.4.7 Appropriate Measures of Goodness of Fit—Model
Diagnostics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.4.8 A Defined Domain of Applicability . . . . . . . . . . . . . . . . . . .
6.4.9 Trying To Interpret Your Model—What Are The Controlling
Descriptors? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.5 Matched Molecular Pairs Analysis . . . . . . . . . . . . . . . . . . . . . . . . .
6.6 Examples of Influential QSAR Models . . . . . . . . . . . . . . . . . . . . . .
6.7 Accessing QSAR Tools and Models . . . . . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Drug Metabolism
C. W. Vose and R. M. J. Ings
7.1

7.2
7.3
7.4
7.5
7.6

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Drug Metabolism Pathways . . . . . . . . . . . . . . . . . . . . . . .
Sites of Drug Metabolism . . . . . . . . . . . . . . . . . . . . . . . . .
Relationship between Structure and Extent of Metabolism
How Is Drug Metabolism Studied? . . . . . . . . . . . . . . . . . .
Why Do We Study Drug Metabolism? . . . . . . . . . . . . . . . .
7.6.1 The Industry Perspective . . . . . . . . . . . . . . . . . . . .
7.6.2 Guidance on Safety Testing of Metabolites . . . . . . .
7.7 What Factors Can Modify Drug Metabolism? . . . . . . . . . .
7.7.1 Dose Level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.7.2 Route of Administration . . . . . . . . . . . . . . . . . . . .
7.7.3 Species Differences in Metabolism. . . . . . . . . . . . .
7.7.4 Gender-Related Differences . . . . . . . . . . . . . . . . . .
7.7.5 Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.7.6 Disease Effects on Metabolism . . . . . . . . . . . . . . .
7.7.7 Drug Interactions . . . . . . . . . . . . . . . . . . . . . . . . .
7.7.8 Genetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.8 Reactive Metabolites . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.9 Transporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.10 Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Prediction of Human Pharmacokinetics, Exposure and Therapeutic Dose in
Drug Discovery
Dermot F. McGinnity, Ken Grime and Peter J. H. Webborn


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8.1
8.2

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213

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
PK in Drug Discovery: a Historical Overview . . . . . . . . . . . . . . . . . . . .


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8.3

Optimising Pharmacokinetics in Drug
8.3.1 Absorption . . . . . . . . . . . . . . .
8.3.2 Volume of Distribution . . . . . .
8.3.3 Clearance . . . . . . . . . . . . . . . .
8.4 Strategic use of PK Parameters. . . . . .
8.4.1 Acidic Compounds . . . . . . . . .

8.4.2 Neutral and Basic Compounds
8.5 Case Examples. . . . . . . . . . . . . . . . . .
8.5.1 H1 Receptor Antagonists . . . . .
8.5.2 Brilinta/Brilique (Ticagrelor) . .
8.5.3 Acidic Compounds . . . . . . . . .
8.5.4 Basic Compounds . . . . . . . . . .
8.5.5 Inhaled PK . . . . . . . . . . . . . . .
8.6 Summary. . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 9

Discovery
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Molecular Biology for Medicinal Chemists
Giselle R. Wiggin, Jayesh C. Patel, Fiona H. Marshall and
Ali Jazayeri

Brief History of Molecular Biology . . . . . . . . . . . . . . . . . .
Impact of Molecular Biology on Target Identification and
Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.2.1 From Disease to Gene—A Genetic Approach . . . . .
9.2.2 Human Genome Project and Beyond . . . . . . . . . . .
9.2.3 Model Organisms . . . . . . . . . . . . . . . . . . . . . . . . .
9.2.4 RNA Interference (RNAi) . . . . . . . . . . . . . . . . . . . .
9.3 Impact of Molecular Biology on Hit Identification to Lead
Optimisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.3.1 Surface Plasmon Resonance . . . . . . . . . . . . . . . . .
9.3.2 X-Ray Crystallography . . . . . . . . . . . . . . . . . . . . . .
9.3.3 Safety and Clinical Efficacy . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Assays
Tim Hammonds and Peter B. Simpson
10.1
10.2
10.3

Use of Assays in Drug Discovery . . . . . . . . . . .
Assay Technologies. . . . . . . . . . . . . . . . . . . . .
10.2.1 Assay Designs . . . . . . . . . . . . . . . . . .
Examples of Common Drug Discovery Assays .
10.3.1 Enzyme Assays . . . . . . . . . . . . . . . . . .
10.3.2 Ion Channel Assays . . . . . . . . . . . . . .

10.3.3 GPCR Assays . . . . . . . . . . . . . . . . . . .
10.3.4 Immunoassays and ELISA-type Assays
10.3.5 Mass Spectrometry. . . . . . . . . . . . . . .
10.3.6 Cell Reporter Gene. . . . . . . . . . . . . . .
10.3.7 High Content Cell Assays . . . . . . . . . .
10.3.8 Cell Phenotypic Assays . . . . . . . . . . . .

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9.2

Chapter 10

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Contents

Assay Outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.4.1 Data Analysis . . . . . . . . . . . . . . . . . . . . . . .
10.4.2 Robustness Analysis and Data Comparison
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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10.4

Chapter 11

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In Vitro Biology: Measuring Pharmacological Activity
Iain G. Dougall
11.1
11.2

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Agonists and Antagonists . . . . . . . . . . . . . . . . . . . . . . . . . .
11.2.1 Agonist Concentration–Effect (E/[A]) Curves . . . . . .
11.2.2 Full Agonists, Partial Agonists and Inverse Agonists
11.2.3 Optimising Agonists. . . . . . . . . . . . . . . . . . . . . . . .
11.2.4 Antagonists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11.3 Application to Drug Discovery. . . . . . . . . . . . . . . . . . . . . . .
11.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 12


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Animal Models: Practical Use and Considerations
Milenko Cicmil and Robbie L. McLeod


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12.3

12.4

12.5

12.6


Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Basic Principles and Major Considerations of Animal Modeling . . .
12.2.1 Ethics, Legal Requirements and 3Rs. . . . . . . . . . . . . . . . . .
12.2.2 Define Objective of the Study and Readouts . . . . . . . . . . . .
12.2.3 Controlling for Variability . . . . . . . . . . . . . . . . . . . . . . . . .
12.2.4 Animal Housing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.2.5 Animal Weight. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.2.6 Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Additional Considerations When Working with Animals . . . . . . . . .
12.3.1 Controls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.3.2 Choice of Animals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.3.3 Species Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.3.4 Genetic Definition of Strain . . . . . . . . . . . . . . . . . . . . . . . .
12.3.5 Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.3.6 Unexplained Data Exclusion . . . . . . . . . . . . . . . . . . . . . . . .
Building a Platform of Evidence to Advance the Pharmacological
Pipeline Using Animal Models . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.4.1 Specificity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.4.2 Robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.4.3 Reproducibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.4.4 Simplicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.4.5 Tools and Reagents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Examples of Pathway Biology PD and Disease Mechanism Model . .
12.5.1 Pathway Biology PD Model . . . . . . . . . . . . . . . . . . . . . . . . .
12.5.2 Disease Mechanism Models . . . . . . . . . . . . . . . . . . . . . . . .
Additional Animal Models for Consideration . . . . . . . . . . . . . . . . .
12.6.1 Non-Human Primate Models . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 13

xv

12.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

331
333

Bioinformatics for Medicinal Chemistry
Niklas Blomberg, Bryn Williams-Jones and John P. Overington


336

13.1
13.2
13.3
13.4
13.5

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Target Dossier . . . . . . . . . . . . . . . . . . . . . . . . . . .
Protein Structure Resources and Homology Modelling
The Genomics Explosion . . . . . . . . . . . . . . . . . . . . . .
Small Molecule Resources and Data Integration for
Drug Discovery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Translational Science
Alasdair J. Gaw
14.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14.2 Linking Hypothesis to Disease . . . . . . . . . . . . . . . . . .
14.3 Creating a Screening Strategy From Molecule To Man.
14.4 Translational Science and Stratified Medicine. . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Discovery Toxicology In Lead Optimisation
Simone Braggio, Mauro Corsi, Aldo Feriani, Stefano Fontana,
Luciana Marocchio and Caterina Virginio
15.1
15.2

15.3

15.4
15.5

15.6

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
In Silico Toxicology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.2.1 In Silico Toxicology Tools . . . . . . . . . . . . . . . . . . . . .
15.2.2 Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.2.3 QSARs and Statistical Modelling. . . . . . . . . . . . . . . .
15.2.4 Human Knowledge-Based Methods . . . . . . . . . . . . .
15.2.5 ADME-Tox Modelling . . . . . . . . . . . . . . . . . . . . . . . .
15.2.6 Application of In Silico Tools in Lead Optimisation. .
Target Selectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.3.1 The Targets Panel for In Vitro Selectivity Evaluation .
15.3.2 Testing Strategies. . . . . . . . . . . . . . . . . . . . . . . . . . .
15.3.3 Data Interpretation . . . . . . . . . . . . . . . . . . . . . . . . .
Cell Viability Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . .
Cardiac Liability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.5.1 Cardiac Function and Ion Channels . . . . . . . . . . . . .
15.5.2 Channels With Safety Liabilities . . . . . . . . . . . . . . . .

15.5.3 Binding vs. Functional Assays. . . . . . . . . . . . . . . . . .
15.5.4 Integrated Cardiovascular Risk Assessment Strategy .
Drug–Drug Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.6.1 Drug–Drug Interaction Mechanisms . . . . . . . . . . . . .
15.6.2 CYP Driven DDI Test Systems. . . . . . . . . . . . . . . . . .

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xvi

Contents

15.6.3 Drug-Metabolising Enzyme Inhibition . . . . .
15.6.4 Pathway Identification . . . . . . . . . . . . . . . . .
15.6.5 Drug-Metabolising Enzyme Induction . . . . . .
15.7 Transporter-Mediated Drug Interactions . . . . . . . . . .
15.7.1 Most Relevant Transporters for DDIs . . . . . .
15.7.2 In Vitro Models to Study Transporter Related
Drug–Drug Interactions . . . . . . . . . . . . . . . .
15.8 Phospholipidosis . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.9 Phototoxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.10 Genotoxicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15.10.1 Bacterial Tests . . . . . . . . . . . . . . . . . . . . . .
15.10.2 In Vitro Mammalian Tests. . . . . . . . . . . . . .
15.10.3 Evaluation of Results . . . . . . . . . . . . . . . . .
15.11 Early In Vivo Toxicology . . . . . . . . . . . . . . . . . . . . . .
15.11.1 Preliminary Pharmacokinetics . . . . . . . . . .
15.11.2 In Vivo Tox Study . . . . . . . . . . . . . . . . . . . .
15.11.3 Early Safety Pharmacology Evaluation . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 16

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403
406

Toxicology and Drug Development
Mark W. Powley
16.1
16.2

413

Introduction and Background. . . . . . . . . . . . . . . . . .
Toxicology Testing . . . . . . . . . . . . . . . . . . . . . . . . . .
16.2.1 Safety Pharmacology . . . . . . . . . . . . . . . . . .
16.2.2 Genetic Toxicology . . . . . . . . . . . . . . . . . . . .

16.2.3 General Toxicology. . . . . . . . . . . . . . . . . . . .
16.2.4 Developmental and Reproductive Toxicology
16.2.5 Carcinogenicity . . . . . . . . . . . . . . . . . . . . . .
16.2.6 Miscellaneous Studies . . . . . . . . . . . . . . . . .
16.2.7 Toxicokinetics . . . . . . . . . . . . . . . . . . . . . . .
16.3 Small Molecule Drugs vs. Biopharmaceuticals . . . . . .
16.4 Regulatory Decision Making . . . . . . . . . . . . . . . . . . .
16.5 Disclaimer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 17

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Patents for Medicines
Paul A. Brady and Gordon Wright
17.1
17.2
17.3

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
What is a Patent? . . . . . . . . . . . . . . . . . . . . . . . . . .

What Conditions Need To Be Fulfilled In Order For
To Be Granted? Patentability . . . . . . . . . . . . . . . . .
17.3.1 Novelty . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.3.2 Inventive Step . . . . . . . . . . . . . . . . . . . . . .
17.3.3 Industrial Applicability. . . . . . . . . . . . . . . .
17.3.4 Exclusions . . . . . . . . . . . . . . . . . . . . . . . . .
17.3.5 Clarity and Sufficiency/Reproducibility . . . .

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Anatomy of a Patent Specification . . . . . . . . . . . . . . . . . . . . . . . .

17.4.1 The Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.4.2 Types of Patent Claim . . . . . . . . . . . . . . . . . . . . . . . . . .
17.4.3 Case Study (a): Typical Claims in a
Pharmaceutical Patent . . . . . . . . . . . . . . . . . . . . . . . . . .
17.4.4 Case Study (b): How Broad Should a Claim Be? . . . . . . .
17.4.5 Case Study (c): A Second Therapeutic Use . . . . . . . . . . . .
17.5 Ownership and Inventorship. . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.6 The Process for Obtaining a Patent . . . . . . . . . . . . . . . . . . . . . . .
17.6.1 The National Nature of Patents. . . . . . . . . . . . . . . . . . . .
17.6.2 A Typical Application Process . . . . . . . . . . . . . . . . . . . . .
17.6.3 Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.6.4 The National Phase: Examination of Patent Applications.
17.7 The Patent after Grant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.7.1 Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.7.2 Extension of Patents. . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.7.3 Challenges to Validity. . . . . . . . . . . . . . . . . . . . . . . . . . .
17.8 Use of Patents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.8.1 Infringement and Enforcement . . . . . . . . . . . . . . . . . . .
17.8.2 Defences and Exemptions to Infringement . . . . . . . . . . .
17.8.3 The Consequences of Patent Infringement . . . . . . . . . . .
17.8.4 Licensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.8.5 The Patent Box. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.9 Generic Medicines and Barriers to Generic Competition . . . . . . .
17.9.1 What is a Generic Medicine? . . . . . . . . . . . . . . . . . . . . .
17.9.2 Regulatory Data Exclusivity. . . . . . . . . . . . . . . . . . . . . . .
17.9.3 Technical Barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
17.10 Patents as a Source of Information . . . . . . . . . . . . . . . . . . . . . . .
17.11 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


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17.4

Chapter 18

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454
454

The Modern Drug Discovery Process
Mark C. Noe
18.1
18.2
18.3
18.4
18.5
18.6

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Hypothesis Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Lead Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Lead Validation and Optimization . . . . . . . . . . . . . . . . . . . . . . . .
Important Considerations for Optimizing Potency. . . . . . . . . . . . .
Important Considerations for Absorption, Distribution, Metabolism
and Excretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
18.7 PK/PD Relationships Influencing Design . . . . . . . . . . . . . . . . . . . .
18.8 Drug Safety. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18.9 The Preclinical Stage: Preparing for First in Human Studies . . . . .
18.10 Clinical Studies—Assessing PK, Safety and Efficacy . . . . . . . . . . . .
18.11 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 19

Contents

Target Validation for Medicinal Chemists
Paul Beswick and Keith Bowers
19.1
19.2
19.3

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Target Validation—Definition and Context . . . . . . . . . . . . . . . .
Key Questions Asked in Target Validation and Techniques
Employed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
19.4 Examples of Target Validation Studies and Data Interpretation .
19.5 Wider Consideration of a Target—Mode of Modulation . . . . . .
19.6 Tools Used in Functional Target Validation . . . . . . . . . . . . . . .
19.7 Experiments Commonly Conducted for Target Validation . . . . .
19.7.1 Presence of Target and/or Target Pathway . . . . . . . . . .
19.7.2 In Vitro Functional Models for Target Validation. . . . . .
19.7.3 In Vivo Models for Target Validation. . . . . . . . . . . . . . .
19.8 Single Target vs. Multiple Targets . . . . . . . . . . . . . . . . . . . . . . .
19.9 Phenotypic Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
19.10 Serendipitous Target Validation . . . . . . . . . . . . . . . . . . . . . . . .
19.11 In Silico Target Validation. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
19.12 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 20

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Lead Generation
Mark Furber, Frank Narjes and John Steele
20.1

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
20.1.1 What Do We Mean By ‘Lead’ And ‘Lead Generation’? . .
20.1.2 The Process of Lead Generation and How The Industry
Has Evolved Over Recent Years . . . . . . . . . . . . . . . . . .
20.1.3 Issues Faced and Resolutions. . . . . . . . . . . . . . . . . . . .
20.2 Hit Identification: How Do We Find A Start Point? . . . . . . . . . .
20.2.1 Strategy—What Are We Trying To Do? . . . . . . . . . . . . .
20.2.2 Target-Based Approaches . . . . . . . . . . . . . . . . . . . . . . .
20.2.3 Phenotype-Based Approaches (Phenotypic Screening) . .
20.3 Hit-to-Lead. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
20.3.1 Strategy—What Are We Trying To Do? . . . . . . . . . . . . .
20.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 21

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Lead Optimisation: What You Should Know!
Stephen Connolly and Simon E. Ward
21.1

The Role of Lead Optimisation . . . . . . . . . . . . . . . . . . . . . . . . .
21.1.1 What Is Obtained From Lead Identification:
Assessing the Series . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.1.2 What Does Lead Optimisation Deliver to Development:
Meeting the Candidate Profile . . . . . . . . . . . . . . . . . . .
21.1.3 The Process of Optimisation . . . . . . . . . . . . . . . . . . . .
21.1.4 Screening Cascade . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21.1.5 Decision-Making in the Screening Cycle . . . . . . . . . . . .

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21.1.6 Progression Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.1.7 Predicted Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.1.8 The Use of Colour to Simplify Decision-Making . . . . . . . .
21.2 Lead Optimisation—The Practicalities . . . . . . . . . . . . . . . . . . . . . .
21.2.1 Quality of Start Point Is of Paramount Importance . . . . . .
21.2.2 Starting Lead Optimisation: Identifying the
Weaknesses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.2.3 Formulating a Strategy for Full Lead Optimisation . . . . . .
21.2.4 Strategies to Optimise Common Parameters in Early Lead
Optimisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.2.5 Drop-Off in Cellular Potency. . . . . . . . . . . . . . . . . . . . . . .
21.2.6 Selectivity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.2.7 Solubility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.2.8 Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.2.9 Toxicity and Phospholipidosis . . . . . . . . . . . . . . . . . . . . .
21.2.10 Rules and Guidelines . . . . . . . . . . . . . . . . . . . . . . . . . . . .
21.3 The End Game: Choosing the Candidate Drug . . . . . . . . . . . . . . . .
21.3.1 Shortlisting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21.3.2 Scale-Up and Safety Testing . . . . . . . . . . . . . . . . . . . . . . .
21.3.3 Back-Up Approaches. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Appendix 21.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Appendix 21.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 22

Pharmaceutical Properties—the Importance of Solid Form Selection
Robert Docherty and Nicola Clear
22.1
22.2

22.3

22.4

Introduction and Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Solid State Chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22.2.1 Crystallography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22.2.2 Crystal Chemistry and Crystal Packing of Drug
Molecules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22.2.3 Intermolecular Interactions, Crystal Packing (Lattice)
Energies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22.2.4 Crystallisation Solubility, Supersaturation and the
Metastable Zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22.2.5 Pharmaceutical Properties and the Solid State . . . . . . .
22.2.6 Polymorphism, Thermodynamic Stability and
Solubility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Industry Practices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22.3.1 Salt Screening and Selection. . . . . . . . . . . . . . . . . . . . .
22.3.2 Co-crystals Screening . . . . . . . . . . . . . . . . . . . . . . . . . .
22.3.3 Polymorph Screening . . . . . . . . . . . . . . . . . . . . . . . . . .
22.3.4 Hydrate Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Integration Within the Early Clinical Phases of Development . .
22.4.1 The Changing Drug Product Design Paradigm . . . . . . .
22.4.2 Different Requirements for Dosage Form Types . . . . . .
22.4.3 Integration of Enabling Formulation Strategies Within
Development Paradigms . . . . . . . . . . . . . . . . . . . . . . .

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22.5

Outlook. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Solid Form Design . . . . . . . . . . . . . . . . . . . . . . . . . .
Particle Design to Enable Clinical Studies . . . . . . . .
Solvation Crystal Packing Balance for Low Solubility
Candidates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22.6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 23


Future
22.5.1
22.5.2
22.5.3

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587

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588
588

The Chemical Development and Medicinal Chemistry Interface
David Lathbury and David Ennis

592

23.1
23.2


What’s The Interaction Trying to Achieve? . . . . . . . . . . . . . . .
Why Don’t Medicinal Chemists Think Ahead To Chemical
Development? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23.3 What Constitutes A Good Synthesis?. . . . . . . . . . . . . . . . . . . .
23.4 What Medicinal Chemistry Can Do At No/Little Extra Cost To
Help Chemical Development . . . . . . . . . . . . . . . . . . . . . . . . .
23.4.1 Recording Experimental Data . . . . . . . . . . . . . . . . . . .
23.5 What Are The Tell-Tale Signs Of Potential Issues?. . . . . . . . . .
23.6 How Best To Deal with the Above Issues? . . . . . . . . . . . . . . . .
23.7 Final Thoughts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 24

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Project Management
Pauline Stewart-Long
24.1


Introduction. . . . . . . . . . . . . . . . . . . . . . . . . .
24.1.1 What is a Project? . . . . . . . . . . . . . . .
24.2 The Project Planning Process . . . . . . . . . . . . .
24.2.1 Initiation . . . . . . . . . . . . . . . . . . . . . .
24.2.2 Planning . . . . . . . . . . . . . . . . . . . . . .
24.2.3 Execution and Control . . . . . . . . . . . .
24.2.4 Close . . . . . . . . . . . . . . . . . . . . . . . . .
24.3 Key Project Management Practices . . . . . . . . .
24.3.1 Planning—Scheduling and Estimating
24.3.2 Risk and Opportunity Management . .
24.3.3 Project Control . . . . . . . . . . . . . . . . .
24.3.4 Stakeholder Management. . . . . . . . . .
24.4 Your Role as a Project Team Member . . . . . . .
24.4.1 Team Charters . . . . . . . . . . . . . . . . . .
24.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Chapter 25

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621

Clinical Drug Development
Maarten Kraan

623

25.1
25.2

623
624

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Types Of Clinical Trials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
25.2.1 Example of a Clinical Development Program of a Small
Molecule for the Treatment of Rheumatoid Arthritis (RA) . .

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25.4
25.5
25.6
25.7
25.8
25.9

Chapter 26

Phases of Drug Development . . . . . . . . . . . . . .
25.3.1 Example of Timelines . . . . . . . . . . . . .
Basic Statistical Considerations/Principles . . . .
25.4.1 Examples of Statistical Considerations .
Target Product Profile . . . . . . . . . . . . . . . . . . .
Study Protocol . . . . . . . . . . . . . . . . . . . . . . . . .
Health Authorities and Ethical Considerations .
25.7.1 Regulatory Examples . . . . . . . . . . . . . .
Investigational Brochure. . . . . . . . . . . . . . . . . .
Study Teams . . . . . . . . . . . . . . . . . . . . . . . . . .


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Aleglitazar: A Case Study
Peter Mohr
26.1 The History of Diabetes . . . . . . . . . . . . . . . . . . .
26.2 The Peroxisome Proliferator-Activated Receptors .
26.3 PPAR Programme at Roche Basel . . . . . . . . . . . .
26.4 A Jump-Start . . . . . . . . . . . . . . . . . . . . . . . . . . .
26.5 Striving for Optimisation . . . . . . . . . . . . . . . . . .
26.6 In-Depth Profiling . . . . . . . . . . . . . . . . . . . . . . .
26.7 Clinical development . . . . . . . . . . . . . . . . . . . . .
26.8 Technical Process. . . . . . . . . . . . . . . . . . . . . . . .
26.9 Epilogue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Note Added in Press . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Chapter 27

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Lessons Learned From the Discovery and Development of
Lapatinib/Tykerb
G. Stuart Cockerill and Karen E. Lackey
27.1
27.2
27.3
27.4
27.5

27.6
27.7
27.8

626
627
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628
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630
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631


Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Project Screening Strategy and Assays Evolved Over Time But
In Vitro and In Vivo Assay Alignment Was Constant. . . . . . . . . . . . .
The Identification of Lead Compounds Involved a ‘‘Screen All’’
Strategy and Rapid Progression to Evaluation in Animal Models . . .
Parallel Evaluation in Potency and Pharmacokinetic Assays Allowed a
Rapid Evaluation of Lead Compounds . . . . . . . . . . . . . . . . . . . . . .
The Use of Binding Hypotheses and Synthetic Tractability Provided
Access to Novel Structural Space by Exploring a ‘‘Putative Variable
Region’’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Synthetic Design and Compound Synthesis Quantity Allowed the
Rapid Evaluation of Compounds . . . . . . . . . . . . . . . . . . . . . . . . . .
Data Re-Evaluation and Rigorous Selection Criteria at This Stage
Led To the Identification of GW2016 . . . . . . . . . . . . . . . . . . . . . . .
Lapatinib, GW2016. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
27.8.1 Clinical Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 28

Contents

27.9 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


695
696
696

‘‘Daring to be Different’’: The Discovery of Ticagrelor
Bob Humphries and John Dixon

699

28.1
28.2
28.3
28.4
28.5

Prologue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Acute Coronary Syndromes (ACS)—A Sticky Problem . . . . .
‘‘I Wouldn’t Start There’’ . . . . . . . . . . . . . . . . . . . . . . . . .
‘‘You Have to Start Somewhere. . .’’—the Role of Cangrelor
Toward Ticagrelor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
28.5.1 Where to Start? . . . . . . . . . . . . . . . . . . . . . . . . . .
28.5.2 Taking Charge . . . . . . . . . . . . . . . . . . . . . . . . . . .
28.5.3 Parallel Universe . . . . . . . . . . . . . . . . . . . . . . . . .
28.5.4 The Human Factor. . . . . . . . . . . . . . . . . . . . . . . .
28.5.5 Complexity of Science, Simplicity of Thought . . . .
28.6 Biting the Bullet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
28.7 Enablers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Subject Index


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715


08:35:58.
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Introduction
I am delighted to have been invited to write an introduction for The Handbook of Medicinal
Chemistry: Principles and Practice. The editors and authors have played an outstanding role

in covering all of the major components of modern medicinal chemistry in an expert and
timely manner, within a comprehensive handbook relevant to newcomers and experienced
scientists alike. This volume will be a pleasure to read through, and then to pick out relevant
sections for in depth consultation. I am sure Principles and Practice will be in constant use,
as different problems arise in drug discovery projects almost on a daily basis, and will become essential reading for medicinal chemists of whatever background and experience.
An overview of the dramatic progress we have made with healthcare quality shows that life
expectancy has consistently risen over the past century with an increase from 60 to over 85 years
for women in most industrialised nations. Similar trends are evident for men and equally
importantly, the developing world is now moving in the same direction. While improved
standards of hygiene, nutrition, housing and other factors are obviously important, it is estimated that 40% of the recent increase in life expectancy in the US is due to modern medicines
largely discovered by the pharmaceutical industry:1 powerful antibiotics are available to treat
life-threatening bacterial infections; hypertension (the silent killer) can be controlled by any
number of once-daily therapies; elevated cholesterol which is a major cardiovascular risk factor,
is well managed with statins, while H2 antagonists and even proton pump blockers are available
over the counter to treat gastric ulcers. When HIV/AIDS appeared on the scene in the early
1980s, it was considered a death sentence and control was thought to be beyond our reach due
to facile transmission and potential for resistance. Today, over thirty drugs from six mechanistic
classes are available, and those in the West who contract the virus have enjoyed much improved
quality of life and longevity. Importantly, similar benefits are now emerging in the developing
world where for example, life expectancy in Kwa Zulu-Natal has risen from 49 in 2003 to 60 years
in 2011 as affordable anti-retroviral combinations became available in the public healthcare
system. Hopefully, recent headlines from The Economist such as: ‘‘The end of AIDS? How 5
million lives have been saved and a plague could be defeated’’ are now within sight, and a fair
balance between drug pricing and health benefits will become commonplace.
Despite such outstanding success, there are still tremendous healthcare challenges facing
medicinal chemists and the whole drug discovery community. We all know that cardiovascular
disease (CVD) is a major risk factor responsible for over four million deaths in Europe each year,
but few realise that 80% of global CVD mortality actually occurs in low- to middle-income
countries which are disproportionately affected. The prevalence of obesity in US adults will grow
The Handbook of Medicinal Chemistry: Principles and Practice

Edited by Andrew Davis and Simon E Ward
r The Royal Society of Chemistry 2015
Published by the Royal Society of Chemistry, www.rsc.org

xxiii


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xxiv

Introduction

to 50% by 2030, and it is also estimated that 92 million Chinese already suffer from Type 2
diabetes. While malaria, TB and HIV are still scourges in many parts of Africa, non-communicable diseases killed 36 million people in 2008 which represents 63% of total deaths, with
the majority occurring in emerging nations. In any one year, 40% of Europeans will be affected
by some type of brain disorder with total annual costs of care around Euro 800 billion, more
than CVD, cancer and diabetes combined. Mental depression is responsible for 38% of all
morbidity and 23% of Quality-Adjusted Life Years (QALYs) lost, whereas the corresponding
figures for cancer are 3 and 16%, respectively. The WHO has forecast an impending disaster due
to unchallenged increases in antimicrobial resistance, but only four new classes of antibiotics
have been introduced over the past 40 years. In response to these major threats to health and
well being, the demand for new medicines will continue unabated, albeit with different emphasis on quality of life or longevity depending on regional differences in economic and social
development. However, new paradigms for research focus, organisation, cooperation and
funding will be required, as we adjust to an ever changing scenario of contracting Pharma and
withdrawal from major therapeutic areas. This introduction offers a personal perspective on
some factors that may influence success and failure in drug discovery, and suggests how the

sector might learn from the past and evolve in the future.
Size and organisation are key factors for innovative drug discovery which have been overlooked in endless rounds of mergers and acquisitions over the past decade, and the relentless
drive to international research conglomerates. During the period when we were most productive
at the Pfizer research laboratories in Sandwich, our total staffing was probably around two to
three hundred, but that period witnessed outstanding discoveries such as amlodipine, diflucan,
doxazosin and sildenafil. Our research was driven by dedicated scientists working together in
multidisciplinary teams towards common objectives within a supportive, but focussed environment. Unusually, drug metabolism experts were also integral members of discovery projects which provided a significant competitive edge, as we did not have to beg, borrow or steal
from development which was the norm throughout Pharma at that time. While we fully
understood the need to compete internationally, we operated largely on a local and personal
scale where a trip to the US was an annual treat, not a weekly routine. We all knew each other,
managers and directors walked the job, and we were not distracted by administration. Scientists
were constantly in and out of each other’s laboratories as we had a hunger to generate, share
and exploit new data that would drive our projects forward. Face to face discussions were the
norm, and stimulated a level of intellectual challenge far beyond impersonal e-mails and text
messages. The current journals section of the library was a focal point for discussions where we
swapped ideas as we jostled for the latest articles, but paper copy has largely disappeared and
individual online access may not generate the same thought- provoking synergies unless alternative communication networks are established. In addition, we valued our ‘‘Tribal Elders’’
who had ‘‘been there, done that’’ and freely shared their experience, but successful role models
have largely disappeared in today’s cost cutting climate. However, the added value generated
through a mentoring and supportive culture coupled with institutionalised learning cannot be
over estimated.
As we grew we had to adapt, and I became drawn to the concept of the Roman Centurion who
traditionally leads and cares for 100 soldiers which seemed a sensibly sized unit, particularly in
a research environment. When there were 100 chemists in my discovery group, I knew them all
and what they were doing, and I was also able to engage at a personal level. However, as the
group expanded it became more difficult to maintain that level of interaction, and informal
discussions were diluted. Dunbar’s number of 150 is an estimate of the social contacts humans
can cope with, obviously at differing levels of engagement, which is roughly in line with the
Centurion concept. The average size of a village in the Domesday Book of 1086 was also around
150, and any further increase stimulated migration to form new settlements. These numbers



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Introduction

xxv

intuitively feel right as they reflect the importance of personal contact, and also address the
critical mass necessary for survival. Similar considerations should underpin drug discovery
organisations where large groups should be broken down into nimble, multidisciplinary units
that can be managed and led on a personal scale. Teams should be largely autonomous but
accountable, with innovation and a data-driven culture recognised and rewarded, rather than
the consensus management and upward decision making that has ossified Pharma in recent
years.
Critical mass is probably more important than size per se as the ability to respond rapidly to
breaking science can make the difference between success and failure. For example, we quickly
realised that half a dozen chemists on a lead optimisation project would not be competitive,
whereas 12 to 15 could hold their own. However, we could never manage the teams of 20 to 40
that others mobilised as duplication, poor communication and a loss of personal responsibility
inherent in such large groups compromised productivity and motivation. Innovative scientists
often want to be different, but some can drift into peripheral activities with a lack of focus and
commitment to team objectives. Crucially, the concept of critical mass and nimble research
units became confused with absolute size in the fruitless drive to build the largest R&D organisations. Even before the merger with Wyeth, Pfizer had an annual R&D budget of nearly $8
billion with thousands of staff spread over eight centres on three continents, which may not be
conducive to a personal or nimble approach. The negative impact of mergers and acquisitions
on productivity is well documented2 as research simply cannot be effectively managed in such

massive units, nor can innovation survive, particularly with multiple locations, cultures and
ever changing leadership. Technology can be expanded in a modular manner and centralised
facilities for HTS, gene sequencing and other service operations are efficient and cost effective,
but innovation simply does not scale. If readers were to take one key message from this
introduction, it would be my strong conviction that drug discovery is a personal and shared
experience, not a metrics-focused, mechanical event. So many times, successful projects are
driven by a small core of dedicated champions with a burning desire to address particular
medical needs, working together in a research-friendly environment not dominated by
numbers.
Hype and premature over-investment in new technologies are other examples of how Pharma
lost its way with the drive towards ‘‘faster, cheaper, better,’’ but quality was lost in the pursuit of
numerical goals. Most companies thought that industrialisation of drug discovery was the way
of the future and that attrition need not be improved if the number of candidates entering
development was significantly increased. Numbers and metrics became key drivers and innovation and personal accountability were lost in the process. Gone were the days of research
proposals that laid out a biological rationale and thoughtful chemistry plans that were subject
to rigorous challenge, and HTS assumed the default mode for new projects. HTS became a
macho competition across Pharma with migration from 96 to 384 to 1536 well plates, and the
drive to generate millions of data points over the shortest time frame. However, assays were
often not robust, and quality control was poor. Compound collections contained everything
chemists had registered, and it took some time to weed out frequent hitters, reactive intermediates and undesirable structural flags that were never intended to included in screening
files in the first place. Unfortunately, re-building these collections also became numbers driven
as it was easy to impress senior managers with the claim to synthesise millions of peptides
overnight, but without adding that these compounds had little utility for drug discovery.
Combinatorial libraries constructed from simple, non-peptide building blocks suffered a
similar fate as focus on ‘‘what we can make’’ rather than ‘‘what we should make’’ led to large
collections of closely related compounds with low value for screening, particularly as mixtures.
Some Pharma companies responded by investing up to $100 million in building diverse, multimillion compound collections, but such large files are rarely screened routinely as