1. 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

2. Potential Hindrances? Patent profusion Unmet expectations
vigilance
Unmet expectations
set reasonably
Infrastructure cost
hindrance for academics
Lack of standards
premature for hardware
Inertia
resistance to change, short-term delivery focus

3. High-throughput Experimentation
Library Design
Synthesis
Pooled, parallel or discrete
Processing
Physical, mechanical etc. processing
Characterization of composition,
purity, phases, structure
Analytical
Primary Testing
Performance in specific application
QSAR#
Testing requirements drive synthesis format
Lead compounds for resynthesis and secondary testing
#Quantitative Structure-Activity relationships

4. Infrastructure Needs Vertical and horizontal integration Adaptable
Modular
Geared for huge throughput
Broadly deployable

5. New 1536 well HTS Format 1536 wells, 2 l well volume
Engineering Solution
New 1536 well HTS Format
1536 wells, 2 l well volume
Corning Science Products joint design
Automated 961536 reformatter
l-level fluids dispensing
Oxidative and evaporative loss reduced

6. Process and Data Management
User Input & Workstation Interfaces
Chemistry &
Materials Input
Workstation & Oracle Forms
Materials
Specific
Tables
Analysis, Display and Data Access
Server-based
Processing
Molecular
Simulation
Data Base
Engines
Oracle
Materials
Algorithms
Display
Statistics

7. Luminescence data for a library of
mixed metal oxides under 254nm UV irradiation
Data from E.Danielson et al., Science 279 (1998) 831

8. 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)

9. Making it practical: computation
Computation Solution
Making it practical: computation
Scaffold
‘Soft materials’ R1 R2 R3 R4
‘Hard materials’ M2 M1 X +
Temp
Which experiments should be done ?
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 ?

10. Compound library design
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
World Drug Index of 35,873 compounds in a space of principal components
C2.Diversity
C2.LibCompare
C2.LibSelect

11. Abstracted Feature Models
Abstraction of key features
Based on activity data
Interesting ‘active’ definition
R.C.Willson

12. Descriptors Computation Solution
Descriptor Families
Topological
Fragments
Receptor surface
Structural
Information-content
Spatial
Electronic
Thermodynamic
Conformational
Quantum mechanical
Descriptors - calculable molecular attributes that govern particular macroscopic properties
Products
C2.Descriptor+
C2.MFA
C2.QSAR+
C2.Synthia
Plus Molecular and
Quantum Methods

13. 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)

14. Structure-Activity Relationships
Computation Solution
Structure-Activity Relationships
Properties
Descriptors
Correlative Methods
Statistical Models
Linear regression
Stepwise & multiple linear regression
Principal components analysis
Partial least squares
Genetic algorithm
Genetic function approximation
Products
C2.QSAR+
C2.GA
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.

15. Oil Field Corrosion Inhibitors
Organics
Oil Field Corrosion Inhibitors
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
H. Gråfen et al., Werkstoff und Korrosion, Vol. 36, 407 (1985)
M.Doyle

16. 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