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Emerging Therapeutic Targets Volume 4, 2000 - Issue 6
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Biosystems modelling for in silico target validation: challenges to implementation

Richard Li-Xiang Ho RW Johnson Pharmaceutical Research Institute, 3210 Merryfield Row, San Diego, CA 92121, USA. [email protected]
Pages 699-714 | Published online: 25 Feb 2005

Bibliography

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  • •This account of Boeing's development of the 777 jetliner describes how computer modelling revolutionised the engineering process. It also exemplifies company-wide systems thinking.
  • ROSES AD: Pharmacogenetics and the practice of medicine. Nature (2000) 405:857–865.
  • KENNEDY T: Managing the drug discovery/develop-ment interface. Drug Disc. Today (1997) 2(10):436–444.
  • CALDWELL GW: Compound optimization in early-and late-phase drug discovery: acceptable pharmacoki-netic properties utilizing combined physicochemical, in vitro and in vivo screens. Curr. Opin. Drug Disc. Devel (2000) 3(1):30–41.
  • HARRIS G: Drug firms, stymied in the lab, become marketing machines. The Wall Street Journal (2000) 236:A1, Al2.
  • DREWS J: In Quest of Tomorrow's Medicines. Springer-Verlag, NY, USA (1999):203.
  • •Summary of the state of pharmaceutical R&D with good chapters on Management of Innovation and the Future of Research and Development. It is focused mainly on the need for accessing innovation from universities and biotechs, but barely mentions any role for in silico methods.
  • BURSTALL ML, REUBEN BG: Outlook for the World Pharma-ceutical Industry to 2010. Decision Resources (Dec 1999). R4172.
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  • FURNESS LM, HENRICHVVARK S, EGERTON M: Expres-sion databases-resources for pharmacogenomic R&D. Pharmacogenomics (2000) 1 (3)281–288.
  • •Good summary of current technologies for pharmacoge-nomic research and companies providing them.
  • JAIN KK: Transforming innovation and commercialization in drug discovery. Drug Disc. Today (2000) 5:318–320.
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  • •Discusses how the syndrome of hypertension is being slowly broken up into a slew of genetic diseases. The same will likely hold true for essentially every other disease syndrome.
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  • CORNISH-BOWDEN A: Metabolic control analysis inbiotechnology and medicine. Nature Biotechnol (1999) 17:641–643.
  • •Nice summary that names many important contributors to metabolic control analysis.
  • SERESSIOTIS A, BAILEY JE: MPS: an artificially intelli-gent software system for the analysis and synthesis of metabolic pathways. Biotechnol. Bioeng. (1988) 31:587–602.
  • SCHILLING CH, EDWARDS JS, PALSSON BO: Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol. Prog. (1999) 15: 288–295.
  • •Good summary of metabolic pathway analysis, also called flux balance analysis.
  • NOBLE D, COLATSKY TJ: A return to rational drug discovery: computer-based models of cells, organs and systems in drug target identification. Emerging Therapeutic Targets (2000) 4(0:39–49.
  • •Excellent introduction to Physiome Sciences' bottom-up modelling approach. I believe they first coined the term 'parts catalogue' referring to the genome.
  • EDWARDS JS, PALSSON BO: Systems properties of the Haemophilus influenzae Rd metabolic genotype. J. Biol. Chem. (1999) 274:17410–17416.
  • ••Worthwhile reading for anyone working in microbiology-shows what is possible, but NOT intuitive, with today's genomic information combined with systems thinking and computational analysis.
  • SCHILLING CH, PALSSON BO: The underlying pathway structure of biochemical reaction networks. Proc. Natl. Acad. Sci. USA (1998) 95:4193–4198.
  • •Lays out red blood cell biochemical pathways.
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  • •Kauffman discusses how self-organisation could be an emergent property of all complex systems. Many of the points apply to cellular automata.
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  • •Despite higher UCP3 levels in response to thyroid hormone and a posited role in brown adipose tissue, Ucp3 (-/-) knockout mice show normal thyroid thermogenesis and no obesity.
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  • •This book shows how institutional policies can interfere with increasing productivity and how to identify such situations. Goldratt's subsequent books describe how to plan for change and set-up win-win situations for those involved.
  • CHRISTENSEN C, OVERDORF M: Meeting the challenge of disruptive change. Harvard Business Review (Mar-Apr 2000):66–76.
  • ••A succinct summary of the ideas in Christensen's book TheInnovator's Dilemma with additional discussion addressing how a successful organisation's strengths migrate from Resources, to Processes, then to Values. They suggest that managers should analyse whether their organisation has the resources, processes and values to develop each new innovation and if not there are other ways to acquire those capabilities.
  • VOIT EO, SAVAGEAU MA: A primer on metabolic pathway analysis. Intelligent Systems for Molecular Biology 2000. San Diego, USA (19 August 2000).
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  • DRAZEN JM, STOKES C: Managing the complexity ofasthma. American Thoracic Society, 96th International Conference. Toronto, Canada (8 May 2000).
  • •Cindy Stokes gave a very clear summary of the kinds of conflicts that arise from the scientific literature when building internally consistent models.
  • INNES C, WHITE N: IL-4 receptor-a breath of fresh airfor asthmatics? Inpharma (2000) 1231:7-8. This reference is also available on the web: http://www.adis.com/newsletters/inpharma/ articles/763450.html
  • KUHN TS: The Structure of Scientific Revolutions (2ndedition). University of Chicago Press, Chicago, USA (1970).
  • •A classic in the history of science, this book puts forth the idea that scientific thinking advances by continual replace-ment of its theories-paradigm shifts. Even when scientific data supports a new way of thinking, many scientists cling to previous paradigms. Promoters of in silico target validation and modelling may find themselves in the same situation.
  • CHRISTENSEN CM: The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business School Press, Boston, USA (1997).
  • ••Christensen carefully shows how there are two kinds ofinnovations: sustaining and disruptive. Successful companies excel with sustaining innovations (continuous improvement) but often stumble on disruptive innovations (radical change). His definitions indicate that top-down modelling in pharmaceutical companies is a disruptive innovation.
  • TUFTE ER: Visual Explanations. Graphics Press, Cheshire, CT, USA (1997).
  • •Tufte's books show off methods for clear and direct graphics that quickly communicate complex ideas.
  • ZALTMAN G, DUNCAN R, HOLBECK J: Innovations and Organizations. Wiley and Sons, NY, USA (1973).
  • KOTTER JP: Leading Change. Harvard Business School Press, Cambridge, MA, USA (1996).
  • ••Kotter feels radical change is becoming more common intoday's world thus being able to lead such change is a necessary skill. He advocates an 'Eight Stage Change Process' for leading more successful projects that is more practical and detailed than simply 'Decide and Implement'.
  • ROGERS EM: Diffusion of Innovations (4th edition). The Free Press, NY, USA (1995):397.
  • ••A comprehensive book that includes broad discussion intohow and why innovations are implemented successfully or not by companies and governments around the world.
  • MOORE GA: Crossing the Chasm (revised edition). Harper-Business, New York, USA (1999).
  • ••Describes how to bring a technology from early adoptersand visionaries to the early and late majority of customers-by analogy, the change agent has the same challenge within their own company in implementing modelling.
  • KLEIN G: Sources of Power. MIT Press, Cambridge, MA, USA (1999).
  • ••This book is subtitled 'How People Make Decisions'.Chapters 13 and 14 are superb in describing how people follow directions and how a team functions and then how to best use those principles for maximum productivity. The rest of the book, although it does not directly address computer models, supports the idea that models are how people make decisions.
  • GOLDRATT EM: Critical Chain. North River Press, Great Barrington, MA, USA (1997).
  • •Goldratt applies his 'Thinking Processes' to project manage-ment. This book is full of useful insights regarding task scheduling, multitasking etc.
  • SCHRAGE M: Serious Play Harvard Business School Press, Boston, USA (2000).
  • ••A book totally devoted to the use of models from claymock-ups to spreadsheets to sophisticated computer simulations, including discussion of critical failure factors. He believes the best companies use modelling because it stimulates innovation and suggests this is due largely to discussions provoked by predictions and thus clearer communication about a company's assumptions and goals.
  • ALIZADEH, EISEN MB, DAVIS RE et al.: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature (2000) 403(6769) :503–511.
  • ••Being able to use gene expression profiling like this toidentify each subtype of every disease would revolutionise medicine and lead to true individualised treatment.
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  • ZIPKIN I: Entelos: simulating disease. BioCentury (5 Oct 1998):A9.
  • •Abbott is listed as a corporate partner and process of elimination from other public documents indicates Abbott was partnering for an HIV/AIDS model.
  • DINERSTEIN RJ, PATERSON TS: The Asthma Phy sio lab: a software environment designed to simulate asthma disease processes for drug discovery and develop-ment. Drug Discovery Technology 2000. Boston, MA, USA (16 Aug 2000).
  • FINK PK, MORGAN K: Evolving an understanding of gene expression data resulting from oxidative stress. In Silico Biology. San Francisco, USA (21 June 2000).
  • HO RLX: Integrating traditional and in Silico approaches for diabetes target triage. In Silico Biology. San Francisco, USA (22 June 2000).

Websites

  • http://www.boeing.com/commercia1/777family/ cdfacts. html 777 Computing Design Facts-brief descriptions of the modelling technology and co-ordination of teams and computers.
  • http://www.nytimes.com/library/national/science/ 081500sci-environ-climate.html The city of Atlanta produces enough heat to make its own storms.
  • http://wwwghcc.msfc.nasa.gov/atlanta/ Description of the NASA study researching the urban heat island phenomenon for Atlanta.
  • http://www.eastlundscience.com/currentd.html Manipulate tornadoes with microwaves?
  • http://www.fortune.com/fortune/fortune500/ medians12.html Listing by industry of total return to shareholders over the past ten years.
  • http://www.decode.com deCODE Genetics investigates the genetics of the population of Iceland.
  • http: //snp .cshl.org The SNP Consortium is funded by a group of pharmaceutical companies to keep SNPs public.
  • http://cmgm.stanford.edu/pbrown Lab of Patrick Brown, pioneer of microarray technology for genes, proteins etc.
  • http://www.ncbi.nlm.nih.gov/geo/ Gene Expression Omnibus-a public collection of gene expression data from microarrays etc.
  • http://industry.ebi.ac.uld-alan/MicroArray/ European collection of gene expression data.
  • http://genome-www.stanford.edu/nci60/index.shtml NCI60 Cancer Microarray Project.
  • http: //www. affymetrix. corn/ Uses photolithographic techniques to make very high density microarrays (GeneChips), clients can arrange for custom arrays for proprietary research.
  • http://www.genelogic.com/ Making custom gene expression databases using differential display technology and Affymetrix GeneChips.
  • http: //www. curagen corn/ Makes gene expression databases and provides analysis to identify protein pathways.
  • http ://www. dna. com DNA Sciences is signing up volunteers to give health histories then will make gene profiles of certain disease types found in the volunteer population.
  • http://www.ardais.com Ardais wants to be a provider of clinical samples and patient medical histories for gene and target discovery.
  • http://www.simulations-plus.com SimulationsPlus makes software to model drug absorption in the GI tract and is now going into 3-dimesional protein modelling.
  • http://www.trega.com Trega makes software to model ADME parameters for in silico pharmacokinetic predictions.
  • http://www.camitro.com Camitro makes software to model ADME and toxicity parameters for in silico pharmacokinetic predictions.
  • http://www.globomax.com GloboMax provides services for clinical trial simulations and also PK/PD modelling.
  • http://www.pharsight.com Pharsight provides clinical trial simulation services.
  • http://www.acslsim.com AEgis Software bought MGA Software which created the ACSL simulation packages used for many engineering modelling applications.
  • http://afcs.swmed.edu/ The Alliance for Cellular Signaling is a multidisciplinary research program to focus on B-cells and cardiac myocyte signalling to understand 'how cells interpret signals in a context-dependent manner'.
  • http://www.e-cell.org/ E-CELL is a computer model of a single cell using only 127 genes, based largely on Mycoplasma genitalium. It allows one to monitor protein and chemical concentrations over time.
  • http://www.nrcam.uchc.edu/ The Virtual Cell project specifies physiology separately from geometry so that simplifications based on geometric considerations can be handled appropriately for each physiological situation modelled, rather than specifying both physiology and geometry each time.
  • http://geo.nihs.go.jp/csndb/ The Cell Signaling Network DataBase is a prelude to a signal pathway modelling project.
  • http://www.stke.org/ Signal Transduction Knowledge Environment (STKE) is sponsored by Science magazine and Stanford University Libraries. STKE is meant to be a knowledge base for workers in the field of signal transduction and is accumulating map representations of various pathways with links to underlying data.
  • http://www.cs.washington.edu/homes/larrya/ cccon00_files/frame.htm The Cell Systems Initiative wants to 'establish a complete theory of the cell' and create predictive models in a distributed environment.
  • http://www.genomics.princeton.edu/ The Lewis-Sigler Institute for Integrative Genomics is a multidisciplinary group focusing on signal transduction, transcriptional networks and morphological diversity.
  • http://www.systemsbiology.org The Institute for Systems Biology is a private, non-profit multidisciplinary group that will also develop technology while they explore systems biology.
  • http://iR2lcb.cnrs-mrs.fr/-athel/mcafaq.htm Metabolic control analysis FAQ.
  • http://gepasi.dbs.aber.ac.uk/metab/mca_home.htm Gepasi is a simulation package; lots of links here, too.
  • http://www.cs.princeton.edu/immsim/index.html IMMSIM is a cellular automata model of the immune system consisting of B-cell, T-cells, antigen-presenting cells, antigens, antibodies, and antigen/antibody complexes.
  • http: //www. physiome. com/ Physiome Sciences creates bottom-up computational models of receptors and ion channels, cells, tissues and organs. Their most developed model is of the heart.
  • http: //www. economist .com/4 G77eU1Q/editorial/ justforyou/18-7-98/st4580.html Roche used the cardiac model from Physiome Sciences to simulate various electrical rhythms induced by drugs. The FDA accepted the simulations as evidence that the drug-induced electrical changes from mibefradil (PosicorTm) were common for several marketed drugs and did not lead to arrhythmia.
  • http://www.fda.gov/medwatch/safety/ 191998/ safety98.htm#posico PosicorTm withdrawn due to interactions with other commonly prescribed drugs.
  • http://physiome.org/ The academic effort attempting to model organs from the bottom-up, like Physiome Sciences.
  • http://www.physiome.org.nz/ Links to XML standards for bottom-up biological modelling.
  • http: //www.bmej hu. edu/news/microphys/ The Microcirculation Physiome Project.
  • http://www.entelos.com Entelos creates top-down models of disease with hundreds of separate compartments.
  • http: //www. kennatechnologies .com/ Kenna Technologies has experience in top-down modelling of diseases affected by cytokine polymorphisms such as osteoporosis, periodontitis, diabetic retinopathy, and coronary artery disease.
  • http: //www. bioscience .org/knockout/noeffect. htm A list (probably created in 1996) of 13 genes knocked-out with hard to find effects on phenotype; some have since been found.
  • http://www.entelos.com/PDFs/ AntiIL-5%20AppNote_8_3_00.pdf Entelos predicted anti-IL-5 would not have much effect on asthma before clinical trials confirmed the result.
  • http://www.beowufforg The Beowuff Project created supercomputer power using an inexpensive cluster of standard PCs networked together.
  • http://www.entropia.com Entropia links idle computers via an intranet or the Internet to provide distributed computing power to academic and industrial customers.
  • http://www.datasynapse.com DataSynapse links idle computers via an intranet or the Internet to provide distributed computing power to its clients. People who donate their computer's idle power receive compensation of various kinds.
  • http://lisetiathome.ssl.berkeley.edu/index.html The SETI@home project is an experiment to use idle computer power via the Internet to analyse radioastronomy data from the Search for Extraterrestrial Intelligence.
  • http://www.stanford.eduigroup/pandegroup/Cosmi Folding@home project for protein folding.
  • http://www.distributed.net This group is using distributed computing over the Internet to work on mathematical challenges and decrypting cryptographic keys.
  • http://www.popularpower.com This company implements distributed computing over the Internet to work on non-profit and commercial projects.
  • http://www.uniteddevices.com This company implements distributed computing over the Internet, and has recently formed a collaboration with Popular Power.
  • http://www.shodor.orgiaida/ This model of Type I diabetes has three main compartments: blood glucose, plasma insulin and active insulin. It is available in PC and web versions.
  • http://www.entelos.com/NewsEvents/press20.html AstraZeneca licenses the Obesity PhysioLab.
  • http://www.entelos.com/NewsEvents/press22.html Bayer signs up for consulting with the Asthma PhysioLab.
  • http://www.entelos.com/NewsEvents/press10.html Procter & Gamble signs up for unspecified consulting services.

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