Thriving onThriving onInformation AnxietyInformation Anxiety

A Survival Guide to theKnowledge-Value

Revolution

Sam A. Falk MilosevichAssociate ProfessorChemical Informaticssam@IUPUI.edu

Home Page

• Introduction• Common Challenges• Information Anxiety• Knowledge Value Revolution

WARNING: this presentation is rated “G” for “General” Session G

• 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 bridgelinking the operating rules of science and the universe

with those of economics.— Stan Davis, Future Perfect

• 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 isthe dizzying disorientation brought on

by the premature arrival of the future— A. Toffler

• Common Challengescomputer-based applications have been narrowly

focused, often under-valued, rarely become part of the routine; vs. bioinformatics

• Information Anxietymismatch between volume of data generated and

dearth of understanding derived from it

• Knowledge-Value Revolutionin post-industrial society, value is more subjective --

and unique value added is a matter unique to each consumer

Nonlinearity means thatthe act of playing the game

has a way of changing the rules.— James Gleick, Chaos

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

Research isthe heart of the business,the soul of the enterprise.

— Eli Lilly , 1947

speed:geographic areas wherecan increase market/share

quality:therapeutic areas whereare or can become a leader

value:competitive advantageclassical values

faster

better

cheaper

Clinical Trials Clinical Trials

~10,000Compounds

CompoundSynthesis

ProjectTeam

FirstHuman

GlobalRegistrations

ProductApprovals

MarketIntroduction

8 3 1 Product

• 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

1,000

The discovery is madewith tears and sweat(at any rate, with agood deal of bad language)by people who areconstantly gettingthe wrong answer.-- J. Bronowski

Drug Discovery

•MOLECULAR DIVERSITY

- Natural Products

- Proteins

- Corporate Libraries

- Combinatorial Libraries

• ASSAYS / SCREENING

- Precise

- Specific

- High Throughput

- Automated

• OPTIMIZATION OF LEADS

- Structure-Assisted

Drug Discovery

- Structure Activity

Optimization

How to lookWhat to look for

Where to look

• TARGET IDENTIFICATION

- Biology / physiology

- Pathophysiology

from M.F.Haslanger

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?

Why?What?describedatabase

explainrules

explorevisual model

"If...Then!"

XY123

Energy = Bonds + Angles + Dihedral Angles + "Improper"Dihedrals + Non-bonds

Total Energy =

bond  

R

  KR(R-R 0)2 +

angle 

  K(-0)2 +

dihedr

  K[1+cos(n -)n=1,2,3,4,6]+

improp

  K( -0)2 +

nonbond

1-4...

  

 A

rij 12  - B

rij 6   + qiqj

40rij 2

Much of the success of modern science and engineeringis based upon our ability to create an abstract mapping

between motions of matter and symbols on paper.— Larry Smarr, NCSA

C CQ

R

Y

XP

ZC CQ

R

Y

XP

Z

C Y C Y

X

-0R-R0

C CQ Y

1+cos(n) Energy Surface

Dynamic Molecules

Cricket Softwareuserdict /md known{/CricketAdjust true def}{/CricketAdjust false def}ifelse /mypsb /psb load def /mypse /pse load def/psb {} store /pse {} storecurrentpoint /picOriginY exch def /picOriginX exch defcurrentpoint pop /newWidth exch picOriginX sub defcurrentpoint /newHeight exch picOriginY sub def pop/newXScale newWidth 150 div def/newYScale newHeight 90 div def/psb /mypsb load store/pse /mypse load store

Human intelligence thrives on context whilecomputers work on abstract numbers alone.

— A. Penzias, Ideas and Information

It is a persistent mistake to define ‘science’ in termsof certain features of existing scientific theories.

— John Searle

• 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?

• 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, t = 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 science

than a heap of stones is a house.— Henri Poincarè

Increasing Molecular Diversity

• 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.

from M.F.Haslanger

Screen ParadigmBiological Target Selected by Strategy

Screen Development

Screen Automation and Optimization

Screen Operation

Strategy Group Follow up

Screen Validation

High Throughput:sensitivitycapacity

from M.F.Haslanger

from M.F.Haslanger

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.

Genomics

Genetics Genome-BasedScreening

GenomicBiochemistry

DiseaseGenes

ProtectiveGenes

Disease GenePathways

Protein-basedDrug

Small MoleculeDrug

Gene to DrugSelect Disease

Validated targets

Drug Candidate

GenomicBiochemistry

MouseGenetics

Human Genetics

Expression screening

ID FunctionHTS screen

Structural Char.

Relevant Models

Expression monitoring

Patientsubsetting

Clinical Trials

Efficacy Decision

from M.F.Haslanger

TherapeuticTarget

PharmaceuticalLead

Product Developoment,Submission, Marketing

Knowledge is Powerful Medicine— Eli Lilly and Company, 1995

BioinformaticsGenomics

Chemical InformaticsMolecular Modeling andMolecular DiversityCombinatorial Chemistry andHigh-Throughput Screening

Medical InformaticsClinical TrialsPharmacokinetics

Health InformaticsDisease ManagementConsumers

Information Anxiety

Information Anxietyis the black holebetween data and knowledge,[which] happens wheninformation doesn’t tell uswhat we want or need to know

—R.S.Wurman, Information Anxiety

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

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

Knowledge-Value

Economic Reality

We are competing globallyon a cognitive basis....Our economy today is basedupon what you know.

— Dr. W. Leigh Tompson, 13 Apr 94

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

ADD UNIQUE VALUE

.

RELEVANCE

TO CUSTOMERRELIA

BILITY -

QUALITY-SPEED

UNIQUEVALUEADDED

change is resisted when apparently irrelevant orout of control

Add Unique Value to Compete inthe Knowledge-Value Revolution

UN

IQU

E V

AL

UE

AD

DE

D

CUSTOMER RELEVANCE

0

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.

"What If?" "If...Then!"

XY123

Put the SCIENTISTinto the SCIENCE.

Enhance personal Creativityand group Communications.

High Performance (Proc’s)

long

larg

e

man

y

Supercomputing admits the very large, the very detailed, the very urgent.

–Boyd & Milosevich, Persp. in Drug Disc. & Des. 1 (1993) 345

High Performance (People)

huh? aha! oh? yes!

hind-sight (20/20)passive info system

data

in-sightactive info system

knowledge

logic

language

perception

patterns

“DO GOOD SCIENCE”SCIENCE

• problem-solving method integrators

• knowledge management systems

APPLICATIONS

• science & technology designers

• information exchange systems

COMPUTERS

• numerics & graphics performance

• data distributed computation

problem-solving focus

Complexity + Contiguity

past

present

future

Scientists need to stay in touch with theirscience experiments and with current science.

Cray-2

Simple Rules --> Complex Results

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

Solutions to fit Problems

.

chemists

sys

experts

applications

systems integr ator s:knowledge domain exper ts:

appl i cations developer s:computational & lab chemists:

computer per spectivemethod per spectiveappl i cation per spectiveproblem per spective

hiear chical pyr amid

"key" stone arches

each member :each arch:

problem per spectivedi ffer ent problem

It is amazing what you learn if you take the time to talk to someone.

— M.Jackman, Star Teams - Key Players

Next Steps

• 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

• 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

• 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

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

Making the Most of It

– 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

Why Change?

The system will always be defendedby those countless people whohave enough intellect to defendbut not quite enough to innovate. ...

Politically, change forced by a crisisis much more accpetable because it isobvious that something must be done - andsurviving a crisis is achievement enough.

— E. deBono, I Am Right - You Are Wrong

Marathon Challenge

We can do it!

Home Page

• Introduction• Common Challenges• Information Anxiety• Knowledge Value Revolution

WARNING: this presentation is rated “G” for “General” Session G

Thriving onThriving onInformation AnxietyInformation Anxiety

A Survival Guide to theKnowledge-Value

Revolution

Sam A. Falk MilosevichAssociate ProfessorChemical Informaticssam@IUPUI.edu