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High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial Methods for Materials Discovery” ATP Fall National Meeting Atlanta, GA Wednesday November 18th 1998

High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

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Page 1: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

High Throughput Experimentation:Computational Requirements

John M. NewsamMolecular Simulations Inc.

(A Pharmacopeia subsidiary)

“Workshop on Combinatorial Methodsfor Materials Discovery”

ATP Fall National MeetingAtlanta, GA

Wednesday November 18th 1998

Page 2: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Potential Hindrances?

• Patent profusion– vigilance

• Unmet expectations– set reasonably

• Infrastructure cost– hindrance for academics

• Lack of standards– premature for hardware

• Inertia– resistance to change, short-term delivery focus

Page 3: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

High-throughput Experimentation

Lead compounds for resynthesis and secondary testing

Testing requirements drive synthesis format

Library Design

QSAR#

#Quantitative Structure-Activity relationships

Pooled, parallel or discreteSynthesis

Primary Testing Performance in specific application

Physical, mechanical etc. processingProcessing

Characterization of composition, purity, phases, structure

Analytical

Page 4: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Infrastructure Needs

• Vertical and horizontal integration

• Adaptable

• Modular

• Geared for huge throughput

• Broadly deployable

Page 5: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

New 1536 well HTS Format• 1536 wells, 2 l well volume

• Corning Science Products joint design

• Automated 961536 reformatterl-level fluids dispensing

• Oxidative and evaporative loss reduced

Engineering Solution

Page 6: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Process and Data ManagementData BaseEngines

Oracle

MaterialsAlgorithms

Display

Statistics

User Input & Workstation Interfaces

Chemistry & Materials Input

Workstation & Oracle Forms

MaterialsSpecific Tables

Analysis, Display and Data Access

Server-basedProcessing

MolecularSimulation

Page 7: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Luminescence data for a library of mixed metal oxides under 254nm UV irradiation

Data from E.Danielson et al., Science 279 (1998) 831

Page 8: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Some Specific Technology Needs

• Hits vs misses; improvement criteria• Descriptors• Experiment decision support• Abstracted feature models (AFMs)• Process optimization• Simulation for scale-up• Sensor data (unravelling response of arrays)

Page 9: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

• Which experiments should be done ?

Making it practical: computation

– 100 R1, 100 R2, 100 R3, 100 R4 108

– 50,000 compounds/week 40 years

• How do we manage the process ?• What knowledge do the experiments yield ?

Computation Solution

‘Hard materials’

M2

M1

X

+Temp

Scaffold

‘Soft materials’

R1

R2

R3

R4

Page 10: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Computation Solution

Compound library design• Library Specification

– Molecular: Product or Reaction-based– Polymers, Heterogeneous catalysts ?

• Library Design– Diversity and similarity metrics– Similarity Selection– Array and mixture design

• Library Comparison• Library Focussing

– Active site model (atomic or abstracted)– QSAR Model

C2.DiversityC2.LibCompareC2.LibSelect

World Drug Index of 35,873 compounds in a space of

principal components

Page 11: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Abstracted Feature Models

R.C.Willson

• Abstraction of key features

• Based on activity data

• Interesting ‘active’ definition

Page 12: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

DescriptorsTopological

Fragments

Receptor surface

Structural

Information-content

Spatial

Electronic

Thermodynamic

Conformational

Quantum mechanical

Descriptor Families

C2.Descriptor+C2.MFAC2.QSAR+C2.Synthia

Products

Plus Molecular and Quantum Methods

Descriptors - calculable molecular attributes that govern particular macroscopic properties

Computation Solution

Page 13: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Available, occupiable volume & framework density descriptors

(104 zeolite and zeolite-related framework types)

Correlative methods in catalyst design: Expert systems, neural networks and structure-activity relationships , in “Advances in Catalyst Design” Catalyst Advance Program (CAP) Report, The Catalyst Group, PA; in press (1998)

Page 14: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Structure-Activity Relationships

C2.QSAR+C2.GA

Products

Linear regression

Stepwise & multiple linear regression

Principal components analysis

Partial least squares

Genetic algorithm

Genetic function approximation

Statistical Models

Descriptors Correlative Methods Properties

E.g. K.F. Moschner and A. Cece, “Development of a General QSAR for Predicting Octanol-Water Partition Coefficients and its Application to Surfactants,” ASTM STP 1218 (1995); MSI C2 QSAR manual April 1997.

Computation Solution

Page 15: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

0

2

4

6

8

10

12

0 2 4 6 8 10 12

Activ ity

GF

A P

redi

cti

on

Oil Field Corrosion InhibitorsOrganics

H. Gråfen et al., Werkstoff und Korrosion, Vol. 36, 407 (1985)

• Benzimidazolines function at cathodic sites• Library studied by Kuron et al. (1985)• Key descriptors

• Terminal N charge• 3-substituted N charge• Octanol-water logP• Moment of inertia

M.Doyle

Page 16: High Throughput Experimentation: Computational Requirements John M. Newsam Molecular Simulations Inc. (A Pharmacopeia subsidiary) “Workshop on Combinatorial

Conclusion

• Computational infrastructure needs• Specific technology needs• Role of computation

– process management system– experiment decision support– data visualization and analysis– knowledge from the experimental data

• Integration