COLLABORATIVE COMPUTATIONAL TECHNOLOGIES FOR BIOMEDICAL RESEARCH

Wiley Series on Technologies for the Pharmaceutical Industry Sean Ekins , Series Editor

Editorial Advisory Board

Dr. Ren é e J.G. Arnold (ACT LLC, USA) Dr. David D. Christ (SNC Partners LLC, USA) Dr. Michael J. Curtis (Rayne Institute, St Thomas ’ Hospital, UK) Dr. James H. Harwood (Delphi BioMedical Consultants, USA) Dr. Maggie A.Z. Hupcey (PA Consulting, USA) Dr. Dale Johnson (Emiliem, USA) Prof. Tsuguchika Kaminuma, (Tokyo Medical and Dental University, Japan) Dr. Mark Murcko, (Vertex, USA) Dr. Peter W. Swaan (University of Maryland, USA) Dr. Ana Szarfman (FDA, USA) Dr. David Wild (Indiana University, USA)

Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals Edited by Sean Ekins

Pharmaceutical Applications of Raman Spectroscopy Edited by Slobodan Š a š i c

Pathway Analysis for Drug Discovery: Computational Infrastructure and Applications Edited by Anton Yuryev

Drug Effi cacy, Safety, and Biologics Discovery: Enmerging Technologies and Tools Edited by Sean Ekins and Jinghai J. Xu

The Engines of Hippocrates: From the Dawn of Medicine to Medical and Pharmaceutical Informatics Barry Robson and O.K. Baek

Pharmaceutical Data Mining: Applications for Drug Discovery Edited by Konstantin V. Balakin

The Agile Approach to Adaptive Research: Optimizing Effi ciency in Clinical Development Michael J. Rosenberg

Pharmaceutical and Biomedical Project Management in a Changing Global Environment Scott D. Babler

COLLABORATIVE COMPUTATIONAL TECHNOLOGIES FOR BIOMEDICAL RESEARCH

Edited by

SEAN EKINSMAGGIE A. Z. HUPCEYANTONY J. WILLIAMS

A JOHN WILEY & SONS, INC., PUBLICATION

Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved

Published by John Wiley & Sons, Inc., Hoboken, New JerseyPublished simultaneously in Canada

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifi cally disclaim any implied warranties of merchantability or fi tness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profi t or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.

Library of Congress Cataloging-in-Publication Data:

Collaborative computational technologies for biomedical research / edited by Sean Ekins, Maggie A.Z. Hupcey, and Antony J. Williams. p. cm. Includes index. ISBN 978-0-470-63803-3 (cloth) 1. Drug development. 2. Cooperation. 3. Pharmaceutical industry–Data processing. 4. Cloud computing. I. Ekins, Sean. II. Hupcey, Maggie A. (Maggie Anne Zo?), 1972- III. Williams, Antony J. RM301.25.C65 2011 615'.19–dc22 2010046374

Printed in the United States of America

oBook ISBN: 978-1-11802603-8ePDF ISBN: 978-1-11802601-4ePub ISBN: 978-1-11802602-1

10 9 8 7 6 5 4 3 2 1

For Mum and Dad with thanks for letting me follow a route of my own. Sean Ekins

For Motts, short but loud. Maggie A. Z. Hupcey

For my twin sons, Taylor and Tyler — two of the best collaborators I know. Antony J. Williams

In the long history of human kind (and animal kind, too) those who have learned to collaborate and improvise most effectively have prevailed.

Charles Darwin

FOREWORD xiAlpheus Bingham

PREFACE xv

CONTRIBUTORS xix

PART I GETTING PEOPLE TO COLLABORATE 1

1. The Need for Collaborative Technologies in Drug Discovery 3Chris L. Waller, Ramesh V. Durvasula, and Nick Lynch

2. Collaborative Innovation: The Essential Foundation of Scientifi c Discovery 19Robert Porter Lynch

3. Models for Collaborations and Computational Biology 39Shawnmarie Mayrand-Chung, Gabriela Cohen-Freue, and Zsuzsanna Hollander

4. Precompetitive Collaborations in the Pharmaceutical Industry 55Jackie Hunter

5. Collaborations in Chemistry 85Sean Ekins, Antony J. Williams, and Christina K. Pikas

6. Consistent Patterns in Large-Scale Collaboration 99Robin W. Spencer

CONTENTS

vii

viii CONTENTS

7. Collaborations Between Chemists and Biologists 113Victor J. Hruby

8. Ethics of Collaboration 121Richard J. McGowan, Matthew K. McGowan, and Garrett J. McGowan

9. Intellectual Property Aspects of Collaboration 133John Wilbanks

PART II METHODS AND PROCESSES FOR COLLABORATIONS 147

10. Scientifi c Networking and Collaborations 149Edward D. Zanders

11. Cancer Commons: Biomedicine in the Internet Age 161Jeff Shrager, Jay M. Tenenbaum, and Michael Travers

12. Collaborative Development of Large-Scale Biomedical Ontologies 179Tania Tudorache and Mark A. Musen

13. Standards for Collaborative Computational Technologies for Biomedical Research 201Sean Ekins, Antony J. Williams, and Maggie A. Z. Hupcey

14. Collaborative Systems Biology: Open Source, Open Data, and Cloud Computing 209Brian Pratt

15. Eight Years Using Grids for Life Sciences 221Vincent Breton, Lydia Maigne, David Sarramia, and David Hill

16. Enabling Precompetitive Translational Research: A Case Study 241Sándor Szalma

17. Collaboration in Cancer Research Community: Cancer Biomedical Informatics Grid (caBIG) 261George A. Komatsoulis

18. Leveraging Information Technology for Collaboration in Clinical Trials 281O. K. Baek

PART III TOOLS FOR COLLABORATIONS 301

19. Evolution of Electronic Laboratory Notebooks 303Keith T. Taylor

CONTENTS ix

20. Collaborative Tools to Accelerate Neglected Disease Research: Open Source Drug Discovery Model 321Anshu Bhardwaj, Vinod Scaria, Zakir Thomas, Santhosh Adayikkoth, Open Source Drug Discovery (OSDD) Consortium, and Samir K. Brahmachari

21. Pioneering Use of the Cloud for Development of Collaborative Drug Discovery (CDD) Database 335Sean Ekins, Moses M. Hohman, and Barry A. Bunin

22. Chemspider: a Platform for Crowdsourced Collaboration to Curate Data Derived From Public Compound Databases 363Antony J. Williams

23. Collaborative-Based Bioinformatics Applications 387Brian D. Halligan

24. Collaborative Cheminformatics Applications 399Rajarshi Guha, Ola Spjuth, and Egon Willighagen

PART IV THE FUTURE OF COLLABORATIONS 423

25. Collaboration Using Open Notebook Science in Academia 425Jean-Claude Bradley, Andrew S. I. D. Lang, Steve Koch, and Cameron Neylon

26. Collaboration and the Semantic Web 453Christine Chichester and Barend Mons

27. Collaborative Visual Analytics Environment for Imaging Genetics 467Zhiyu He, Kevin Ponto, and Falko Kuester

28. Current and Future Challenges for Collaborative Computational Technologies for the Life Sciences 491Antony J. Williams, Renée J. G. Arnold, Cameron Neylon, Robin W. Spencer, Stephan Schürer, and Sean Ekins

INDEX 519

FOREWORD

xi

You have in your hands a book on collaboration, more specifi cally a book on scientifi c collaboration, and most specifi cally, a book on collaboration in the science of pharmaceutical development — the discovery of new therapies and medicines — products addressing the, as - yet, unmet medical needs of twenty - fi rst century health. While only a few would take issue with the merits of collaboration, perhaps even most fail to appreciate the implications of col-laborative technologies in the present day. The ability to fuse ideas — especially ideas that cross disciplines — is a crucial capability responsible for accelerating innovation and progress. Matt Ridley recently gave a TED talk entitled, “ When Ideas Have Sex, ” the salient point being that the fusion of ideas, each bringing its own set of memes, is a powerful way of creating new memetic material.

People have collaborated as long as . . . well . . . as long as there have been people. Often nothing more than self - interest incites us to collaborate, to fi ll in portions of a solution important to us, portions we were not capable of creating on our own. Unfortunately, modern - day organizational structures very often serve as impediments to collaboration. Collaborating with those outside the walls of an institution may be more than culturally frowned upon, it may even be illegal under legislation written to hinder corporate espionage, or protect trade or national technological capabilities. (I guess if that were the only problem, it could be readily solved by a new set of policies or regulations.)

But institutional boundaries are not the only barriers that impede collabora-tion. Even within an institution — which should be legally, strategically, and fi nancially incented for alignment, and for maximizing the opportunities for

xii FOREWORD

internal collaboration — barriers still exist. The subunits of the institution: its departments, its divisions, its components produce collaboration “ walls ” of varying substantiality. Organizational lore and personal relationships add another layer of “ not - invented here ” (NIH) culture, and allegiances to local agendas, even to the point of disadvantaging the larger institutional unit. In fact, if we wish to pursue the elimination of collaboration barriers we have to realize that many barriers are not institutional at all. Choices to collaborate or not col-laborate are sometimes based not just on current affi liations but on past affi li-ations, degrees obtained, reputations, and even a less than rational bias as to just who our collaboration partners should be.

A bright spot in recent history has been the open - source movement. It was loosely organized. It was NOT the project management assignment of any large corporate fi rm fi lled with project managers looking for substantial devel-opment programs like this one. While we acknowledge that there was a com-ponent of centralization, that is, Linus Torvald ’ s role in Linux, the majority of work was exercised in a distributed manner, each module remaining somewhat independent of the constraints often imposed by centralized planning func-tions. Most importantly, the basis upon which individuals contributed was informed solely by the contribution itself, not perceived qualifi cations or past reputations.

While the open - source movement has been associated primarily with the development of software, the demonstration that it can compete effectively with the traditional modes of corporate technology development raises the possibility that such collaborative forms will soon move well beyond software and into other arenas of complex development. This is more than mere specu-lation. In the chapters that follow you ’ ll see early endeavors to accomplish pharmaceutical development in a much more open manner. While these may still fall short of the phenomenon associated with Linux, they more than hint at a future to come. One barrier to this progression was highlighted in Harvard Business Review ’ s ten best business ideas for 2010; namely, the current lack of a well - accepted and digitized representation of this work. The vast majority of collaborative pharmaceutical development still remains primarily a local and classically social phenomenon.

While change is still impeded for the reasons described above, the corporate model of the fully integrated pharmaceutical company is under threat for very good reasons. In the past decade, it has shown its inability to create and sustain shareholder value. A closer examination of the business model itself reveals a variety of fl aws (or features, if you ’ d prefer): long monetization cycles, large capital investments with high risks, and a complex union of both information and materials management. We might argue that a typical pharmaceutical company tries to operate, under one roof, three distinctive business entities. It is a high - tech manufacturer, producing exquisitely expensive fi ne chemicals or complex biotechnical products. It is a purveyor of information to the regula-tory and medical communities, information with specifi cations and demands rarely matched in any other sector. And, fi nally, it is a high risk research

FOREWORD xiii

venture, which can only show returns when managed as a portfolio of complex assets demanding constant invention and breakthroughs.

Each of these three business entities would ideally be managed with a dis-tinctive set of overarching strategies and yet such an approach is rarely accom-modated. This book addresses, for the most part, only the unique challenge associated with managing large, complex, high - risk research endeavors. But of the three business - entity challenges cited here, a novel new approach to this one could transform the economics of the entire business.

Considering the present state the pharmaceutical industry fi nds itself in, the promise of innovative medicines for children and our children ’ s children may well depend on fi nding new collaborative paradigms with attendant business models. The material for this genesis, though nascent, may well be found in these pages.

Alpheus Bingham April 2011

PREFACE

xv

Biomedical research has become increasingly driven by creating and consum-ing tremendous volumes of complex data whether biological, genomic, pro-teomic, metabolomic or molecular in nature. At the same time the pharmaceutical industry is utilizing an extended network of partner organiza-tions of various sorts (CRO ’ s, not - for - profi t organizations, clinicians and aca-demics) in order to discover and develop new drugs. Current areas of interest for delivering new technologies or molecules to the industry are Open Innovation, Collaborative Innovation and of course, Open Source. Due to the mounting costs, collaborative research and development is undoubtedly the future of biomedical research. There is currently little if any guidance for managing information and computational resources across collaborations of different types. This represents a large cost as experiments can be repeated inadvertently and the cost and time - savings that could result from precompeti-tive data sharing have generally been ignored. Improving drug discovery or development technology alone is not the solution and we need intelligent information systems and an understanding of how to use them effectively to create and manage knowledge across these collaborations. This book thor-oughly details a real set of problems from the human collaborative and data and informatics aspects and is therefore very relevant to the day - to - day activi-ties of running a laboratory or a collaborative research and development project. The processes, approaches and recommendations provided in this book could be applied to help organizations immediately make critical deci-sions about managing drug discovery and development partnerships. The chapters provide case histories of biomedical collaborations while the technol-ogy specifi c chapters have effectively balanced technological depth and acces-sibility for the non - specialist reader. The structure of the book will follow a “ man - methods - machine ” format and the book is divided into four sections:

xvi PREFACE

Part I. Getting People to Collaborate Part II: Methods and Processes for Collaborations Part III. Tools for Collaborations Part IV. The Future of Collaborations

This book may offer the reader a “ getting started guide ” or instruction on “ how to collaborate ” for new laboratories, new companies, and new partner-ships, as well as a user manual for how to troubleshoot existing collaborations. This book should therefore be of interest to most researchers involved in developing IT systems in the pharmaceutical industry. It should also be par-ticularly pertinent to those leading and participating in collaborative IT con-sortia for Drug Discovery and Development which are, at the time of writing, increasing in both scope and number.

The book is possible as a result of the contributions of a wide array of authors from pharmaceutical companies, consulting companies, software com-panies, government institutes, nonprofi ts, and academia with chapters written by acknowledged pioneers in the fi eld. We have aimed for a complete volume that can be read by all interested in biomedical research and development and with each chapter edited to ensure consistency across the common theme of collaboration and with appropriate explanatory fi gures and key references. We are confi dent this book will become a valuable reference work for those inter-ested in collaborative approaches to biomedical research. Certainly this volume represents a point in time for a fast - moving domain of innovation and effort. We hope to revisit this again in the coming years and report on the eventual successes, impacts and shifts in technology as well as cover areas not included in detail.

ACKNOWLEDGMENTS

We are extremely grateful to Jonathan Rose and colleagues at Wiley for their assistance with this book and in particular Bea Roberto for copy editing. Our anonymous proposal reviewers are gratefully acknowledged for their helpful suggestions which, along with other scientists who provided suggestions for additional authors, helped bring this book to fruition.

We are immensely honored that approximately 50 authors agreed to par-ticipate sharing their research and ideas and accepting our editorial changes. Clearly this book would have been impossible without their time, effort and input which they provided despite these diffi cult economic times. This book would have been impossible without their personal sacrifi ces and collaborations.

We sincerely thank Alph Bingham for the magnifi cent Foreword and Bryn Williams - Jones for the kind words on the back cover, which they willingly provided at very short notice.

PREFACE xvii

Our authors and ourselves have endeavored to reference as many groups as possible in these chapters but accept and apologize to the many others that may have been unfortunately omitted due to lack of space. We hope we can include you in future volumes!

We acknowledge Tagxedo for the cover image and also made good use of GoogleDocs and its collaborative features when preparing and sharing these chapters. We thank the many scientists that suggested contributors including Dr. Larry Smarr.

Our own research owes a great deal to past, present (and doubtless future) collaborators and we acknowledge them for helping to stimulate this book.

In order to better serve our readers, color versions of selected illustrations from this book can be found at the following ftp address:

ftp://ftp.wiley.com/public/sci_tech_med/collaborative_computational

Finally, we dedicate this book to our families that have followed this project and provided us the time and support to do it.

Sean Ekins Maggie A. Z. Hupcey

Antony J. Williams

Jenkintown, Pennsylvania

Wake Forest, North Carolina

April 2011

CONTRIBUTORS

xix

Santosh Adayikkoth, Ph.D., Infosys Technologies Limited, Electronic City, Bangalore, India

Ren é e J. G. Arnold, Pharm.D., R.Ph., Arnold Consultancy & Technology LLC, New York, New York; Master of Public Health Program, Department of Preventive Medicine, Mount Sinai School of Medicine, New York, New York; Division of Social and Administrative Sciences, Arnold and Marie Schwartz College of Pharmacy, Long Island University, Brooklyn, New York

O. K. Baek, IBM Canada Ltd., Markham, Ontario, Canada

Anshu Bhardwaj, Ph.D., Institute of Genomics and Integrative Biology (IGIB), CSIR, Delhi, India

Alpheus Bingham, Ph.D., Cascade Consulting, Carmel, Indiana; InnoCentive, Inc., Waltham, Massachusetts; Monitor Talent, Cambridge, Massachusetts

Jean - Claude Bradley, Ph.D., Department of Chemistry, Drexel University, Philadelphia, Pennsylvania

Samir K. Brahmachari, Ph.D., Council of Scientifi c and Industrial Research (CSIR), Institute of Genomics and Integrative Biology (IGIB), Delhi, India

Vincent Breton, Ph.D., Laboratory of Corpuscular Physics, Clermont University and University Blaise Pascal, Clermont - Ferrand, France

Barry A. Bunin, Ph.D., Collaborative Drug Discovery, Burlingame, California

Christine Chichester, Ph.D., Netherlands Bioinformatics Center, Nijmegen, The Netherlands

Gabriela Cohen - Freue, Ph.D., PROOF Centre of Excellence, Vancouver, British Columbia, Canada

xx CONTRIBUTORS

Ramesh V. Durvasula, Ph.D., Bristol - Myers Squibb Company, Princeton, New Jersey

Sean Ekins, Ph.D., D.Sc., Collaborations In Chemistry, Jenkintown, Pennsylva-nia; ACT LLC, New York, New York; Collaborative Drug Discovery, Burlingame, California; Department of Pharmaceutical Sciences, University of Maryland, Baltimore, Maryland; Department of Pharmacology, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, Piscataway, New Jersey

Rajarshi Guha, Ph.D., NIH Chemical Genomics Center, Rockville, Maryland

Brian D. Halligan Ph.D., Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin

Zhiyu He, Ph.D., Graphics, Visualization and Virtual Reality Laboratory (GRAVITY), University of California, San Diego, California

David Hill, Ph.D., Clermont University, University of Blaise Pascal, LIMOS, Clermont - Ferrand, France

Moses M. Hohman, Ph.D., Collaborative Drug Discovery, Burlingame, California

Zsuzsanna Hollander, M.Sc., PMP, PROOF Centre of Excellence, Vancouver, British Columbia, Canada

Victor J. Hruby, Ph.D., Department of Chemistry and Biochemistry, University of Arizona, Tucson, Arizona

Jackie Hunter, Ph.D., OI Pharma Partners, Ltd. Red Sky House, Fairclough Hall Farm, Halls Green, Weston, Hertfordshire, United Kingdom

Maggie A. Z. Hupcey, Ph.D., PA Consulting Group, Princeton, New Jersey

Steve Koch, Ph.D., Center for High Technology Materials, Albuquerque, New Mexico

George A. Komatsoulis, Ph.D., Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services, Rockville, Maryland

Falko Kuester, Ph.D., Graphics, Visualization and Virtual Reality Laboratory (GRAVITY), University of California, San Diego, California

Andrew S. I. D. Lang, Ph.D., Department of Computer Science and Mathe-matics, Oral Roberts University, Tulsa, Oklahoma

Nick Lynch, Ph.D., AstraZeneca UK Limited, Alderley Park, Macclesfi eld, United Kingdom

CONTRIBUTORS xxi

Robert Porter Lynch, Ph.D., The University of Alberta Edmonton, Alberta, Canada and The University of British Columbia, Vancouver, British Columbia, Canada

Lydia Maigne, Ph.D., Laboratory of Corpuscular Physics, Clermont University and University Blaise Pascal, Clermont - Ferrand, France

Shawnmarie Mayrand - Chung, Ph.D., J.D., National Institutes of Health, Public - Private Partnerships Program — Offi ce of Science Policy Analysis, Offi ce of the Director, Bethesda, Maryland

Garrett J. McGowan, Ph.D., Chemistry Department, Alfred University, Alfred, New York

Matthew K. McGowan, Ph.D., Foster College of Business Administration, Peoria, Illinois

Richard J. McGowan, Ph.D., Philosophy and Religion Department, Butler University, Indianapolis, Indiana

Barend Mons, Ph.D., Netherlands Bioinformatics Center, Nijmegen, The Netherlands

Mark A. Musen, Ph.D., Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California

Cameron Neylon, Ph.D., STFC Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, Oxfordshire, United Kingdom

Christina K. Pikas, Doctoral Candidate, College of Information Studies, University of Maryland, College Park, Maryland

Kevin Ponto, Ph.D., Graphics, Visualization and Virtual Reality Laboratory (GRAVITY), University of California, San Diego, California

Brian Pratt, Insilicos LLC, Seattle, Washington

David Sarramia, Ph.D., Laboratory of Corpuscular Physics, Clermont University and University Blaise Pascal, Clermont - Ferrand, France

Vinod Scaria, Ph.D., Institute of Genomics and Integrative Biology (IGIB), CSIR, Delhi, India

Stephan Sch ü rer, Ph.D., Department of Pharmacology, Miller School of Medicine, Center for Computational Science, University of Miami, Miami, Florida

Jeff Shrager, Ph.D., Symbolic Systems Program (consulting), Stanford University, Stanford, California; CollabRx., Inc., Palo Alto, California

Robin W. Spencer, Ph.D., Pfi zer Inc. (retired), United States

Ola Spjuth, Ph.D., Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

xxii CONTRIBUTORS

S á ndor Szalma, Ph.D., Centocor R & D, Inc. and Johnson & Johnson Corporate Offi ce of Science and Technology, San Diego, California ; Rutgers, The State University of New Jersey, New Brunswick, New Jersey

Keith Taylor, Ph.D., Accelrys, Inc., San Ramon, California

Marty Tenenbaum, Ph.D., CollabRx., Inc., Palo Alto, California

Zakir Thomas, Ph.D., Council of Scientifi c and Industrial Research (CSIR), Rafi Marg, New Delhi, India

Michael Travers, Ph.D., CollabRx., Inc., Palo Alto, California

Tania Tudorache, Ph.D., Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California

Chris L. Waller, Ph.D., Pfi zer, Inc., Groton, Connecticut

John Wilbanks, Ph.D., Creative Commons, San Francisco, California

Antony J. Williams, Ph.D. F.R.S.C., Royal Society of Chemistry, Wake Forest, North Carolina

Egon Willighagen, Ph.D., Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

Edward D. Zanders, Ph.D., BioVillage Ltd., St. John ’ s Innovation Centre, Cambridge, United Kingdom

PART I

GETTING PEOPLE TO COLLABORATE

1 NEED FOR COLLABORATIVE TECHNOLOGIES IN DRUG DISCOVERY

Chris L. Waller , Ramesh V. Durvasula , and Nick Lynch

3

Collaborative Computational Technologies for Biomedical Research, First Edition. Edited by Sean Ekins, Maggie A. Z. Hupcey, Antony J. Williams.© 2011 John Wiley & Sons, Inc. Published 2011 by John Wiley & Sons, Inc.

1.1 Introduction 4 1.1.1 Brief History of Pharmaceutical Industry 4 1.1.2 Brief History of Biotechnology 5 1.1.3 Brief History of Government - Funded Academic Drug Discovery 6

1.2 Setting The Stage for Collaborations 7 1.2.1 Current Business, Technical, and Scientifi c Landscape 7 1.2.2 Externalization of Research: Collaboration with Partners 8

1.3 Overview of Value of Precompetitive Alliances in Other Industries 11 1.3.1 Overview of Existing Precompetitive Alliances 12 1.3.2 Pistoia Alliance: Construct for Precompetitive Collaborations 12 1.3.3 How Does Pistoia Plan to Differentiate Itself? 13 1.3.4 Overview of Current Pistoia Projects 14

1.3.4.1 SESL — Semantic Enrichment of Scientifi c Literature 14 1.3.4.2 Sequence Services 14 1.3.4.3 ELN Query Services 15

1.4 Conclusion 17 References 17

4 NEED FOR COLLABORATIVE TECHNOLOGIES IN DRUG DISCOVERY

1.1 INTRODUCTION

From its accidental beginnings in Alexander Fleming ’ s laboratory, pharmaceu-tical drug discovery and development has emerged as a multi - billion - dollar industry that has revolutionized practically all aspects of human (and animal) life as we know it. Over the past 100 years, serendipitous discovery has been replaced by a structured process that in its current state is highly structured, automated, and regulated. It is also expensive and lengthy and suffers from a 99% failure rate. Industry averages suggest that the cost to bring a new drug to the market under this so - called blockbuster paradigm is in the neighbor-hood of $1.5 – 2.0 billion and takes nearly 16 years (Fig. 1.1 ) [1] .

1.1.1 Brief History of Pharmaceutical Industry

The origins of the pharmaceutical industry can be traced back to the 1800s and the dye industry in Switzerland. From the dye industry, specialty chemistry companies emerged with Ciba, Geigy, and Sandoz in Switzerland along with Bayer and Hoechst in Germany evolving into the fi rst pharmaceutical compa-nies. In the early 1900s, the center of pharmaceutical research and develop-ment (R & D) migrated to the United States, specifi cally New Jersey, with companies such as American Home Products, Johnson & Johnson, Warner Lambert, Merck & Co., Pharmacia - Upjohn, Schering - Plough, BASF, Hoechst, Schering AG, Hoffman LaRoche, and Novartis making it the location of choice for their U.S. operations. The late 1900s saw the emergence of North Carolina as a pharmaceutical industry hot spot with Glaxo - Wellcome making its U.S. headquarters there. Also in the late 1900s, the biotechnology industry emerged

Figure 1.1 Pharmaceutical research and development process.

TargetSelection

ChemicalSelection

ClinicalTrials

Launch

Cost = $1.3B/new drug

0 2

Years

4 6 8 10

Discovery(2–10 years)

Preclinical TestingLaboratory and animal testing

Phase 120–80 healthy volunteers - safety and dosage

FDA Review/Approval

Phase 33,000–5,000 patient volunteers used to monitor

adverse reactions to long-term use

12 14 16

INTRODUCTION 5

with companies congregated in the Boston/Cambridge area; the San Francisco Bay Area, San Diego, California; Princeton, New Jersey; Washington, D.C., metro area; as well as Philadelphia. In recent years the economic pressures that forced the pharmaceutical industry to think differently about the sourcing of many operational commodity services has driven a trend toward the emer-gence of both large pharmaceutical and biotechnology footprints in emerging markets such as Brazil, Russia, India, and China (the traditional BRIC coun-tries) as well as Indonesia [2] .

1.1.2 Brief History of Biotechnology

The biotechnology “ revolution ” began in earnest in 1976 with the founding of Genentech. Inspired by similar movements over the past century in the semi-conductor, computer, and advanced materials business, a business model was adopted that would see science evolve from being a tool for the creation of new products and services to being the business itself. Science would move from being “ outside ” of the business to being the actual business. Genentech was founded as the fi rst of a number of private fi rms that would monetize the basic research process. Herbert Boyer, an academician, and Robert Swanson, a venture capitalist, invested $500 each into a new business venture that would seek practical uses for the engineered proteins being developed in Boyer ’ s laboratory [3] . Genentech remains one of the largest and most successful of the biotech companies, posting revenues in 2008 in excess of $10 billion, and is now wholly owned by Roche. The Genentech business model continues to be cloned as academicians seek venture capital to advance their ideas and blend science and business.

Despite the business success seen by some of the biotechnology companies, the vast majority of the entrants into this fi eld failed. The business environ-ment imagined (and required) by this new sector was one in which pharma-ceutical (R & D) activities were organized through a web of collaborative agreements between the traditional large pharmaceutical and newer biotech-nology companies. This collaborative network was envisioned to dramatically alter the industry and transform human health through improved products and services. In reality, while the biotechnology sector has seen exponential growth in revenues over the past 25 years, operational income has been fl at or negative, and there has been no discernable difference in research and development productivity as measured by new drug launches. However, the biotechnology sector has contributed to the diversity of treatments in the world ’ s medicine chest. In 2008, 31 new medicines were launched, 10 of biolog-ics (non - small - molecule) origin, the preferred modality of the biotechnology sector [4] .

The promise of transformation of the health care industry brought about by the emergence of “ science business ” biotechnology companies has failed to materialize due to fundamental differences between the pharmaceutical (R & D) business and the organizational models indiscriminately borrowed

6 NEED FOR COLLABORATIVE TECHNOLOGIES IN DRUG DISCOVERY

from the semiconductor industry. Science - based businesses face unique chal-lenges not present in these other industries, and the focus on monetization of intellectual property, rather than products or services, has actually been detri-mental to the creation of the collaborative network envisioned by the early pioneers of the biotechnology movement. Specifi cally, this misaligned focus has led to (1) the creation of numerous information silos and barriers to sharing — a key requirement for collaboration, (2) fragmentation of the indus-try and duplication of noncompetitive activities, and (3) a proliferation of new fi rms competing for resources from a limited pool [5] .

1.1.3 Brief History of Government - Funded Academic Drug Discovery

In 1980, the Bayh - Dole Act was enacted with the intention to stimulate phar-maceutical research into key disease areas by allowing academic institutions as well as individual researchers to benefi t directly from commercialization of their government - funded research efforts. Although greatly criticized as a mechanism that promotes science with no direct market relevance [6] , government - funded research spending is signifi cant and increasing. Across the National Institutes of Health (NIH), a number of “ center grants ” have been awarded over the last several years to build out the necessary infrastructure to power an academic revolution. Examples of the types of work being sup-ported are as follows: (1) Burnham was awarded a $98 million grant to estab-lish one of four comprehensive national screening centers as part of the NIH ’ s, Molecular Libraries Probe Production Centers Network (MLPCN); (2) 83 National Center for Research Resources (NCRR) – funded Centers of Biomedical Research Excellence (COBRE) have been awarded two consecu-tive, fi ve - year, $10 million grants; (3) Northwestern is awarded $11 million to create a Center to Speed Drug Discovery (Northwestern); and (4) a grant from the NIH will help establish the Chicago Tri - Institutional Center for Chemical Methods and Library Development. The NIH will pump $62 million into more than 20 studies focused on using epigenomics to understand how environmen-tal factors, aging, diet, and stress infl uence human disease.

In 2008, the National Cancer Institute (NCI) alone funded research efforts in excess of $12 billion. More recently, the NCI has been funding efforts that would increase the value of academic research through the creation of public – private partnerships to translate knowledge from academia into new drug treatments. To this end, the NCI has established the Chemical Biology Consortium, which is advertised as an integrated network of chemical biolo-gists, molecular oncologists, and chemical screening centers. Current members of the consortium include. The University of North Carolina in Chapel Hill, North Carolina; Burnham Institute for Medical Research in La Jolla, California; Southern Research Institute in Birmingham, Alabama; Emory University in Atlanta; Georgetown University in Washington, D.C.; the University of Minnesota in St. Paul and Minneapolis; the University of Pittsburgh and the University of Pittsburgh Drug Discovery Institute; Vanderbilt University