Systems biology embedded target validation: improving efficacy in drug discovery

The pharmaceutical industry is faced with a range of challenges with the ever‐escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in ‐omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment. WIREs Syst Biol Med 2014, 6:1–11. doi: 10.1002/wsbm.1253

[1]  A. Barabasi,et al.  Drug—target network , 2007, Nature Biotechnology.

[2]  B. Munos Lessons from 60 years of pharmaceutical innovation , 2009, Nature Reviews Drug Discovery.

[3]  P. Sorger,et al.  Sequential Application of Anticancer Drugs Enhances Cell Death by Rewiring Apoptotic Signaling Networks , 2012, Cell.

[4]  Charles Auffray,et al.  Application of ’omics technologies to biomarker discovery in inflammatory lung diseases , 2013, European Respiratory Journal.

[5]  A. Hopkins Network pharmacology: the next paradigm in drug discovery. , 2008, Nature chemical biology.

[6]  Khusru Asadullah,et al.  What makes a good drug target? , 2011, Drug discovery today.

[7]  Daniel M. Johnstone,et al.  Emerging real-time technologies in molecular medicine and the evolution of integrated 'pharmacomics' approaches to personalized medicine and drug discovery. , 2012, Pharmacology & therapeutics.

[8]  M. Tewari,et al.  The Limits of Reductionism in Medicine: Could Systems Biology Offer an Alternative? , 2006, PLoS medicine.

[9]  Josep Roca,et al.  A Systems Biology Approach Identifies Molecular Networks Defining Skeletal Muscle Abnormalities in Chronic Obstructive Pulmonary Disease , 2011, PLoS Comput. Biol..

[10]  K. Shokat,et al.  The evolution of protein kinase inhibitors from antagonists to agonists of cellular signaling. , 2011, Annual review of biochemistry.

[11]  Patricia L. Harris,et al.  Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. , 2004, The New England journal of medicine.

[12]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[13]  Peter Høngaard Andersen,et al.  Priorities for improving drug research, development and regulation , 2013, Nature Reviews Drug Discovery.

[14]  C. Mehta,et al.  The future of drug development: advancing clinical trial design , 2009, Nature Reviews Drug Discovery.

[15]  Joanna M. Sasin,et al.  Protein Tyrosine Phosphatases in the Human Genome , 2004, Cell.

[16]  Albert-László Barabási,et al.  Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits* , 2013, Molecular & Cellular Proteomics.

[17]  J. Arrowsmith Trial watch: Phase III and submission failures: 2007–2010 , 2011, Nature Reviews Drug Discovery.

[18]  Igor Goryanin,et al.  Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. , 2009, Cancer research.

[19]  F. Azuaje,et al.  Drug-target network in myocardial infarction reveals multiple side effects of unrelated drugs , 2011, Scientific reports.

[20]  John P. Overington,et al.  Can we rationally design promiscuous drugs? , 2006, Current opinion in structural biology.

[21]  Dirk Schadendorf,et al.  Improved survival with MEK Inhibition in BRAF-mutated melanoma for the METRIC Study Group , 2012 .

[22]  M. Rask-Andersen,et al.  Trends in the exploitation of novel drug targets , 2011, Nature Reviews Drug Discovery.

[23]  C. Sawyers,et al.  Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. , 2001, The New England journal of medicine.

[24]  Joseph Loscalzo,et al.  Systems pharmacology, pharmacogenetics, and clinical trial design in network medicine , 2012, Wiley interdisciplinary reviews. Systems biology and medicine.

[25]  B. Ladizinski,et al.  Thalidomide and analogues: potential for immunomodulation of inflammatory and neoplastic dermatologic disorders. , 2010, Journal of drugs in dermatology : JDD.

[26]  J. DiMasi,et al.  Trends in Risks Associated With New Drug Development: Success Rates for Investigational Drugs , 2010, Clinical pharmacology and therapeutics.

[27]  S. Kingsmore,et al.  Genome-wide association studies: progress and potential for drug discovery and development , 2008, Nature Reviews Drug Discovery.

[28]  International consortium completes human genome project. , 2003, Pharmacogenomics.

[29]  S. Iacobelli,et al.  Prediction of Survival by Neutropenia According To Delivery Schedule of Oxaliplatin–5-Fluorouracil–Leucovorin for Metastatic Colorectal Cancer in a Randomized International Trial (EORTC 05963) , 2011, Chronobiology international.

[30]  Melvin E Andersen,et al.  Dose-response modeling in reproductive toxicology in the systems biology era. , 2005, Reproductive toxicology.

[31]  M. Mann,et al.  Global Effects of Kinase Inhibitors on Signaling Networks Revealed by Quantitative Phosphoproteomics , 2009, Molecular & Cellular Proteomics.

[32]  S. Safe,et al.  Aspirin Inhibits Colon Cancer Cell and Tumor Growth and Downregulates Specificity Protein (Sp) Transcription Factors , 2012, PloS one.

[33]  Sridhar Ramaswamy,et al.  Rational design of cancer-drug combinations. , 2007, The New England journal of medicine.

[34]  N. Trayanova,et al.  A Computational Model to Predict the Effects of Class I Anti-Arrhythmic Drugs on Ventricular Rhythms , 2011, Science Translational Medicine.

[35]  Gary R. Mirams,et al.  Application of cardiac electrophysiology simulations to pro-arrhythmic safety testing , 2012, British journal of pharmacology.

[36]  Jan Lankelma,et al.  Principles behind the multifarious control of signal transduction , 2004, The FEBS journal.

[37]  Susumu Goto,et al.  Network analysis identifies a putative role for the PPAR and type 1 interferon pathways in glucocorticoid actions in asthmatics , 2012, BMC Medical Genomics.

[38]  T M Grogan,et al.  Comparison of a standard regimen (CHOP) with three intensive chemotherapy regimens for advanced non-Hodgkin's lymphoma. , 1993, The New England journal of medicine.

[39]  Boris N. Kholodenko,et al.  Signalling ballet in space and time , 2010, Nature Reviews Molecular Cell Biology.

[40]  Philip E. Bourne,et al.  PROMISCUOUS: a database for network-based drug-repositioning , 2010, Nucleic Acids Res..

[41]  E. Hafen,et al.  A Novel, Evolutionarily Conserved Protein Phosphatase Complex Involved in Cisplatin Sensitivity*S , 2005, Molecular & Cellular Proteomics.

[42]  P. Hajduk,et al.  Rational approaches to targeted polypharmacology: creating and navigating protein-ligand interaction networks. , 2010, Current opinion in chemical biology.

[43]  J. Arrowsmith Trial watch: Phase II failures: 2008–2010 , 2011, Nature Reviews Drug Discovery.

[44]  David R. Croucher,et al.  Signalling by protein phosphatases and drug development: a systems‐centred view , 2012, The FEBS journal.

[45]  D. Kell,et al.  Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it , 2013, The FEBS journal.

[46]  J. Shryock,et al.  Inhibition of the late sodium current as a potential cardioprotective principle: effects of the late sodium current inhibitor ranolazine , 2006, Heart.

[47]  T. Ideker,et al.  Network-based classification of breast cancer metastasis , 2007, Molecular systems biology.

[48]  Xiaobo Zhou,et al.  Drug Inhibition Profile Prediction for NFκB Pathway in Multiple Myeloma , 2011, PloS one.

[49]  P J Noble,et al.  Late sodium current in the pathophysiology of cardiovascular disease: consequences of sodium–calcium overload , 2006, Heart.

[50]  Michael J. Keiser,et al.  Predicting new molecular targets for known drugs , 2009, Nature.

[51]  Gerhard Dürnberger,et al.  Chemical proteomic profiles of the BCR-ABL inhibitors imatinib, nilotinib, and dasatinib reveal novel kinase and nonkinase targets. , 2007, Blood.

[52]  A. Barr Protein tyrosine phosphatases as drug targets: strategies and challenges of inhibitor development. , 2010, Future medicinal chemistry.

[53]  F. Lévi,et al.  Cancer chronotherapeutics: experimental, theoretical, and clinical aspects. , 2013, Handbook of experimental pharmacology.

[54]  D. J. Ashley,et al.  The two "hit" and multiple "hit" theories of carcinogenesis. , 1969, British Journal of Cancer.

[55]  H. Handa,et al.  Teratogenic effects of thalidomide: molecular mechanisms , 2011, Cellular and Molecular Life Sciences.

[56]  Muffy Calder,et al.  The Mammalian MAPK/ERK Pathway Exhibits Properties of a Negative Feedback Amplifier , 2010, Science Signaling.

[57]  T. Reiss Drug discovery of the future: the implications of the human genome project. , 2001, Trends in biotechnology.

[58]  B. Garvik,et al.  Principles for the Buffering of Genetic Variation , 2001, Science.

[59]  Albert Goldbeter,et al.  Identifying mechanisms of chronotolerance and chronoefficacy for the anticancer drugs 5-fluorouracil and oxaliplatin by computational modeling. , 2009, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[60]  J. Utikal,et al.  Improved survival with MEK inhibition in BRAF-mutated melanoma. , 2012, The New England journal of medicine.

[61]  Annabelle Ballesta,et al.  A Combined Experimental and Mathematical Approach for Molecular-based Optimization of Irinotecan Circadian Delivery , 2011, PLoS Comput. Biol..

[62]  Charles C. Persinger,et al.  How to improve R&D productivity: the pharmaceutical industry's grand challenge , 2010, Nature Reviews Drug Discovery.

[63]  Sumit K Chanda,et al.  Fulfilling the promise: drug discovery in the post-genomic era. , 2003, Drug discovery today.

[64]  Kevan M. Shokat,et al.  Chemical genetic discovery of targets and anti-targets for cancer polypharmacology , 2012, Nature.

[65]  Martin Vingron,et al.  A systems biological approach suggests that transcriptional feedback regulation by dual‐specificity phosphatase 6 shapes extracellular signal‐related kinase activity in RAS‐transformed fibroblasts , 2009, The FEBS journal.

[66]  Vikram Sinha,et al.  Pharmacokinetics/pharmacodynamics and the stages of drug development: Role of modeling and simulation , 2005, The AAPS Journal.

[67]  B. Kholodenko,et al.  Systems medicine: helping us understand the complexity of disease. , 2013, QJM : monthly journal of the Association of Physicians.

[68]  R. Hällgren,et al.  The timing of glucocorticoid administration in rheumatoid arthritis , 1997, Annals of the rheumatic diseases.

[69]  Jorge Cortes,et al.  Systems approaches and algorithms for discovery of combinatorial therapies. , 2009, Wiley interdisciplinary reviews. Systems biology and medicine.

[70]  E. Petricoin,et al.  Proteins, drug targets and the mechanisms they control: the simple truth about complex networks , 2007, Nature Reviews Drug Discovery.