Thriving on Information Anxiety

1. Thriving on Information Anxiety A Survival Guide to the Knowledge-Value Revolution Sam A. Falk Milosevich Associate Professor Chemical Informatics sam@IUPUI.edu

2. Introduction Common Challenges Information Anxiety Knowledge Value Revolution Home Page G WARNING: this presentation is rated “G” for “General” Session

3. Can you imagine? “glass house” turned inside-out systems - Twilight of Sovereignty simulations - Information Anxiety solutions - Knowledge-Value Revolution integrated value chain platforms with the power applications people with the problems unique value added to the enterprise multi-dimensional, parallel the next generation, not the next iteration Technology is the conceptual bridge linking the operating rules of science and the universe with those of economics.— Stan Davis, Future Perfect

4. How would you like? add unique value to your enterprise end-user solutions (authorship) enhanced products (publication) improved business (impact) imagination, innovation, renaissance reality data acquisition & delivery (commodity) information development (unique query) knowledge-value decision-making ("inform") example context specific to drug discovery at major pharma concept general to all sizes of organizations Future Shock is the dizzying disorientation brought on by the premature arrival of the future— A. Toffler

5. Common Challenges computer-based applications have been narrowly focused, often under-valued, rarely become part of the routine; vs. bioinformatics Information Anxiety mismatch between volume of data generated and dearth of understanding derived from it Knowledge-Value Revolution in post-industrial society, value is more subjective -- and unique value added is a matter unique to each consumer Nonlinearity means that the act of playing the game has a way of changing the rules.— James Gleick, Chaos

6. Eli Lilly and Company is a global research-based pharmaceutical corporation ... working to create and deliver superior health care solutions that provide customers worldwide with optimal clinical and economic outcomes. — http://www.lilly.com

7. Research isthe heart of the business,the soul of the enterprise.— Eli Lilly , 1947 value: competitive advantage classical values cheaper speed: geographic areas where can increase market/share faster quality: therapeutic areas where are or can become a leader better

8. Cost of developing new drug - $359M • Need peak worldwide sales of $1B • Delay in diminishing peak sales: • $31.69/second • $1,900/minute • $114,000/hour • $2,740,000/day Product Approvals Market Introduction Compound Synthesis Project Team First Human Global Registrations ~10,000 Compounds 1,000 3 8 1 Product Clinical Trials

9. The discovery is made with tears and sweat (at any rate, with a good deal of bad language) by people who are constantly getting the wrong answer. -- J. Bronowski

10. • TARGET IDENTIFICATION • ASSAYS / SCREENING - Biology / physiology - Precise - Pathophysiology - Specific - High Throughput - Automated •MOLECULAR DIVERSITY • OPTIMIZATION OF LEADS - Natural Products - Structure-Assisted - Proteins Drug Discovery - Corporate Libraries - Structure Activity - Combinatorial Libraries Optimization Drug Discovery What to look for How to look Where to look from M.F.Haslanger

11. Natural science does not simply describe and explain nature;it is a part of the interplay between nature and ourselves;it describes nature as exposed to our method of questioning.— Werner Heisenberg What If? "If...Then!" explore visual model XY123 What? Why? describe database explain rules

12. Much of the success of modern science and engineeringis based upon our ability to create an abstract mappingbetween motions of matter and symbols on paper.— Larry Smarr, NCSA Energy Surface Dynamic Molecules

13. Human intelligence thrives on context while computers work on abstract numbers alone.— A. Penzias, Ideas and Information

14. Computer Applications predominantly computational chemistry some computational engineering Computational Chemistry general molecular modeling computer graphics & data visualization Drug Design and Discovery transform molecular structure w/r molecular properties; empirical vs. virtual mathematical expressions of the laws of physics are used to model chemical entities and their transformations; more? It is a persistent mistake to define ‘science’ in termsof certain features of existing scientific theories.— John Searle

15. Structure-based drug design goals help generate novel ideas for new products help compress time for discovery and development being first is good enough: typically, Dt = 6 months Structure-based drug design results some published results some clinical trial candidates much current work is proprietary Structure-based drug design basics Combinatorial Chemistry, High Throughput Screens Genomics, Proteomics; Clinical Data; Patents Science is built up of facts, as a house is built of stones;but an accumulation of facts is no more a sciencethan a heap of stones is a house.— Henri Poincarè

16. Combinatorial Chemistry: application of process methodology to repetitive connection of different building blocks to yield a large array of diverse molecules. Limitations in molecular complexity. Rapidly expands compound libraries. Challenge is to maximize diversity. Increasing Molecular Diversity from M.F.Haslanger

17. Screen Paradigm Biological Target Selected by Strategy Screen Development Screen Validation Screen Automation and Optimization Screen Operation • High Throughput: • sensitivity • capacity Strategy Group Follow up from M.F.Haslanger

18. Genomics Genomic Biochemistry Genome-Based Screening Genetics Disease Genes Protective Genes Disease Gene Pathways Protein-based Drug Small Molecule Drug Genomics • Every new gene discovered represents a potential diagnostic or therapeutic target or a drug. • Integrated genomics tools provide a means to rapidly validate potential targets. from M.F.Haslanger

19. Select Disease Genomic Biochemistry Human Genetics Mouse Genetics Validated targets Relevant Models ID Function HTS screen Expression screening Structural Char. Drug Candidate Expression monitoring Patient subsetting Clinical Trials Efficacy Decision Gene to Drug from M.F.Haslanger

20. Therapeutic Target Pharmaceutical Lead Product Developoment, Submission, Marketing Knowledge is Powerful Medicine— Eli Lilly and Company, 1995 Bioinformatics Genomics Chemical Informatics Molecular Modeling and Molecular Diversity Combinatorial Chemistry and High-Throughput Screening Medical Informatics Clinical Trials Pharmacokinetics Health Informatics Disease Management Consumers

21. Information Anxiety is the black hole between data and knowledge, [which] happens when information doesn’t tell us what we want or need to know —R.S.Wurman, Information Anxiety Information Anxiety

22. Science <==> Economics Technology is the conceptual bridge linking the operating rules of science and the universe with those of economics. — S. M. Davis, Future Perfect

23. Knowledge-Value • What is important for the • production of knowledge-value is • ... the knowledge, experience, and • sensitivity to be found among • those engaged in its creation. • — T.Sakaiya, Knowledge-Value Revolution

24. We are competing globally on a cognitive basis.... Our economy today is based upon what you know. — Dr. W. Leigh Tompson, 13 Apr 94 Economic Reality

25. Strategy • Scientific & Economic Innovation • Quality: Effective products & services • Speed: Efficient processes & systems • Value: Competitive advantage • Unique Value Added • Standardized Concepts in Customized Contexts • S.M. Davis, Future Perfect • Social Subjectivity; Small Venture Business • T. Sakaiya, The Knowledge-Value Revolution • Commitment: Persistence of Strategies • P. Ghemawat, Commitment

26. ADD UNIQUE VALUE change is resisted when apparently irrelevant or out of control

27. Add Unique Value to Compete inthe Knowledge-Value Revolution MASS CUSTOMIZATION: • standardize the concept • customize the context efficiency is a ratio; effectiveness is not. DO IT BETTER, DO IT DIFFERENTLY, OR STOP DOING IT.

28. Put the SCIENTIST into the SCIENCE. Enhance personal Creativity and group Communications. XY123 "What If?" "If...Then!"

29. Supercomputing admits the very large, the very detailed, the very urgent. –Boyd & Milosevich, Persp. in Drug Disc. & Des. 1 (1993) 345 High Performance (Proc’s)

30. High Performance (People) huh? aha! oh? yes! perception patterns logic language in-sight active info system knowledge hind-sight (20/20) passive info system data

31. SCIENCE • problem-solving method integrators • knowledge management systems APPLICATIONS • science & technology designers • information exchange systems COMPUTERS • numerics & graphics performance • data distributed computation “DO GOOD SCIENCE” problem-solving focus

32. Complexity + Contiguity future present past Scientists need to stay in touch with their science experiments and with current science.

33. Simple Rules --> Complex Results

34. Chemical Informatics • provide timely solutions to scientists' problems • enhance chemists' ability to use all available data • enable time compression in R&D efforts • differentiate & support unique capabilities • integrate and cooperate w/corporate infrastructure • organize for science function, not system vendor • educate and consult with scientists on capabilities • educate and consult with management on costs • evaluate evolving computer science & technology

35. Solutions to fit Problems It is amazing what you learn if you take the time to talk to someone. — M.Jackman, Star Teams - Key Players

36. Understanding the unique and fundamentally complex nature of the data, processes, and problems that characterize the domain New acquisition and integration, analysis and synthesis, or dissemination and use of data Technological and infrastructure approaches to supporting meaningful, long-term interdisciplinary collaborations specifically for chemical informatics research Next Steps

37. Integrating strategic technologies for the internet with a focus on quick impact usable and widely deployable networking applications that promote collaborative research and information sharing. Integrating strategic techniques for pervasive computing and distributed terascale facilities new algorithms, data structures, advanced system software, distributed access to very large data archives, sophisticated information mining and visualization techniques, and collaborative environments for data exploration and analysis Next Steps

38. Providing innovative educational activities at the undergraduate level by the transfer of research results into the undergraduate curriculum. Enhancing inter-disciplinary insights through collaboration among IT and science professionals in industry and academia. Increasing policy-makers' awareness of the return on investment in chemical informatics Next Steps

39. A Functional Organization: • is distinguished by computational science capability, not computer system vendors • gives scientists more responsive power (and more responsibility) on their desktops • focuses on solving scientists' problems in a constantly-changing environment • replaces Mainframe class homogeneity with Personal Computer style individual diversity

40. development depends not so much on finding optimal combinations for given resources and factors of production as on calling forth and enlisting for development purposes resources which are hidden, scattered or badly utilized The Strategy of Economic Development in A.O. Hirschman, Exit, Voice, and Loyalty Vertical thinking is digging the same hole deeper; lateral thinking is trying again elsewhere. E. deBono, New Think Nature has no outline; imagination has. Blake Making the Most of It

41. The system will always be defended by those countless people who have enough intellect to defend but not quite enough to innovate. ... Politically, change forced by a crisis is much more accpetable because it is obvious that something must be done - and surviving a crisis is achievement enough. — E. deBono, I Am Right - You Are Wrong Why Change?

42. Marathon Challenge We can do it!

43. Introduction Common Challenges Information Anxiety Knowledge Value Revolution Home Page G WARNING: this presentation is rated “G” for “General” Session

44. Thriving on Information Anxiety A Survival Guide to the Knowledge-Value Revolution Sam A. Falk Milosevich Associate Professor Chemical Informatics sam@IUPUI.edu