Operational Overview Bude-Stratton Business Park Bude Cornwall
Exelgen Discovery background <ul><li>Building on the foundations of Exelgen originally established in 1997 </li></ul><ul><...
<ul><li>To work with Life Science Companies to help discover compound(s) which have </li></ul><ul><ul><li>the appropriate ...
Exelgen Discovery’s Offerings <ul><li>Collaborative Services </li></ul><ul><ul><li>Hit Finding and File Enhancement </li><...
Library Enhancement Strategy …  analyze existing collection Collaborative Services Corporate Screening Collection Desired ...
Toward Lead-like or Targeted Subsets … what is desirable <ul><li>Poor absorption or permeation of an orally administered d...
Enhancing a Compound Collection …   analyze vendors <ul><li>Process vendor collection in same manner as corporate collecti...
Enhancement Can Be Tailored …   only buy what’s needed <ul><li>Select sequentially </li></ul><ul><ul><li>Preferred Vendors...
Synthesis of Enhancement libraries …   Sources of Scaffolds From “Ideas”  Database (~2500 ideas) From Chemists “chemical i...
Careful Reagent Selection …   enhance synthetic success Reagent Pool Vendor Catalogs Library Reagents Depending on the lib...
Type of Library Needed Depends on What is Known Lead  Optimization Hit Validation or Lead Finding Hit Finding Knowledge of...
Focused libraries are rapidly generated by combining high quality sources of library ideas with techniques for filtering t...
Rapid Development of Focused Libraries Ideas can come directly from the chemist or other sources, based on knowledge or in...
Rapid Development of Focused Libraries The knowledge base is a continually evolving repository of knowledge about the desi...
Rapid Development of Focused Libraries <ul><li>The ideas are coded into “virtual” libraries, providing a pool of millions ...
Rapid Development of Focused Libraries The compounds that survive the virtual screening are all potentially active in the ...
Rapid Development of Focused Libraries Converting a library design into a physical set of compounds to screen is an intera...
Initial screening results in a number of hits and neighborhood analysis can be used to differentiate true positives from f...
Focused Compound Selection <ul><li>Compounds can be extracted from Existing Collections </li></ul><ul><ul><li>=> Library E...
Extracting a Focused Set from a Vendor Collection <ul><li>Grid chemical space with physiologically relevant descriptor and...
Scaffold Selection All sources of scaffolds can benefit from analysis Process most important for scaffolds with the least ...
Generating a Focused Library Design <ul><li>Collect knowledge of the target  </li></ul><ul><ul><li>Literature data </li></...
Full Library Design Synthetic   Scheme Reagent Pool Virtual Library Monomer Pool Drug/Lead-like Pool Initial Design Final ...
Physical Property Profiling <ul><li>Poor absorption or permeation of an orally administered drug is more likely to occur i...
ADMET Predictions Poor BBB Permeability Good BBB Permeability Moderate BBB Permeability High bioavailability (good solubil...
<ul><li>Identify Reasonable Binding Modes </li></ul><ul><ul><li>Cluster on RMS distance between docked structures </li></u...
Topomer Distances Split molecule into 2-3 fragments Rule-based alignment of fragments onto a grid Use probe atom to calcul...
Example - Tagamet and Zantac:  both do the same thing in the body Sulfur Ring Nitrogen rich section <ul><ul><li>What do th...
<ul><li>Design is an Iterative process </li></ul><ul><ul><li>What pleases the chemist often doesn’t please the computer an...
Summary of the Complete Process <ul><li>Most compounds that enter the drug discovery process fail </li></ul><ul><ul><li>Us...
<ul><li>Design Environment   </li></ul><ul><ul><li>Building & rapid searching of large databases </li></ul></ul><ul><ul><u...
We know which compounds to make Design Environment Production Environment Difficult Simple Distant Close Highest interest ...
Project Consultancy & Management <ul><li>Consultancy </li></ul><ul><ul><li>Work with client to establish project objective...
Contract Research <ul><li>Flexible approach </li></ul><ul><ul><li>FTE-based model gives client greatest flexibility in ste...
Screening Libraries <ul><li>Off the shelf </li></ul><ul><ul><li>Cherry-pick from ~25000 compounds </li></ul></ul><ul><ul><...
Novel Intermediates, Building Blocks & Custom Synthesis <ul><li>Wide range of intermediates and building blocks  </li></ul...
Custom Analysis & Purification <ul><li>Custom NMR and LC-MS services </li></ul><ul><ul><li>Can be tailored to customer’s s...
Summary Exelgen Discovery provides a broad spectrum of competitively priced Discovery Products and Services.  For further ...
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Exelgen Discovery

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Exelgen Discovery

  1. 1. Operational Overview Bude-Stratton Business Park Bude Cornwall
  2. 2. Exelgen Discovery background <ul><li>Building on the foundations of Exelgen originally established in 1997 </li></ul><ul><li>Based in UK with partners in US - 20 scientific personnel plus additional support staff </li></ul><ul><li>Experienced drug discovery Contract Research Organisation </li></ul><ul><ul><li>Chemistry, Design, Data Analysis and Mining </li></ul></ul>Background
  3. 3. <ul><li>To work with Life Science Companies to help discover compound(s) which have </li></ul><ul><ul><li>the appropriate biological activity </li></ul></ul><ul><ul><li>the appropriate target selectivity </li></ul></ul><ul><ul><li>an acceptable ADME-Tox profile </li></ul></ul><ul><ul><li>a patentable position </li></ul></ul>Exelgen Discovery’s Core Business All in as short a time as possible Background Lead Optimization Hit Validation or Lead Finding Hit Finding
  4. 4. Exelgen Discovery’s Offerings <ul><li>Collaborative Services </li></ul><ul><ul><li>Hit Finding and File Enhancement </li></ul></ul><ul><ul><li>Hit Follow-up/Hit-to-Lead </li></ul></ul><ul><ul><li>Lead Optimisation and LeadHopping </li></ul></ul><ul><ul><li>Project Consultancy & Management </li></ul></ul><ul><li>Contract Research </li></ul><ul><li>Screening Libraries </li></ul><ul><li>Novel Intermediates and Building Blocks </li></ul><ul><li>Custom Synthesis </li></ul><ul><li>Custom Analysis & Purification </li></ul>Background
  5. 5. Library Enhancement Strategy … analyze existing collection Collaborative Services Corporate Screening Collection Desired Compounds Acceptable Compounds Unacceptable Compounds Poor Chemistry Undesirable Properties Discard Good Chemistry Drug-like Properties Screen Good Chemistry Lead-like Properties Buy Compounds can be further subdivided by target
  6. 6. Toward Lead-like or Targeted Subsets … what is desirable <ul><li>Poor absorption or permeation of an orally administered drug is more likely to occur if any two of these criteria are violated: </li></ul><ul><ul><li>Molecular weight is greater than 500 </li></ul></ul><ul><ul><li>Lipophilicity is high (ClogP is greater than 5) </li></ul></ul><ul><ul><li>Number of Hydrogen bond donors is greater than 5 </li></ul></ul><ul><ul><li>Number of Hydrogen bond acceptors is greater than 10 </li></ul></ul>Compounds in a screening set should have drug-like or lead-like properties Properties of Oral Drugs Categorized by Gene Family Hopkins, et al, Nature Biotechnology 2006, 7, 805-815 Lipinski’s “Rule of 5” is the best known filtering criteria There are MANY others => Rules need to be tailored to specific customers needs Collaborative Services 9 7 4 5.7 505 Protein Kinases 12 8 4 4.8 572 Serine Proteases 9 8 2 5.2 465 Phospho-diesterases 17 10 8 6.5 752 Peptide GPCRs 10 6 2 7.3 495 Nuclear Hormone Receptors 7 6 3 4.7 430 Ion Channels 8 6 2 5.6 460 Aminergic GPCRs 90% Rbonds 90% HBA 90% HBD 90% ClogP 90% MW
  7. 7. Enhancing a Compound Collection … analyze vendors <ul><li>Process vendor collection in same manner as corporate collection </li></ul><ul><li>Produce a lead-like subset </li></ul><ul><li>Compare corporate collection to vendor collection </li></ul><ul><ul><li>Eliminate any vendor compounds that are within specified cut-off distance of corporate collection </li></ul></ul><ul><li>Cluster remaining lead-like, novel subset </li></ul><ul><ul><li>Grid spacing for vendor collection often looser than for corporate collection </li></ul></ul><ul><ul><li>Can also fill-in clusters with low occupancy of corporate compounds </li></ul></ul><ul><li>Select compounds from clusters based on client preferences </li></ul><ul><ul><li>Preferred vendors </li></ul></ul><ul><ul><li>Best properties </li></ul></ul><ul><ul><li>Best price </li></ul></ul><ul><ul><li>Purity </li></ul></ul>Collaborative Services
  8. 8. Enhancement Can Be Tailored … only buy what’s needed <ul><li>Select sequentially </li></ul><ul><ul><li>Preferred Vendors </li></ul></ul><ul><ul><li>Preferred Targets </li></ul></ul><ul><li>Select based on target </li></ul><ul><ul><li>Similarity to known actives </li></ul></ul><ul><ul><li>Privileged substructures </li></ul></ul><ul><ul><li>Meet pharmacophore model </li></ul></ul><ul><ul><li>Meet SAR model </li></ul></ul><ul><li>Select based on properties </li></ul><ul><ul><li>Preferred vendors </li></ul></ul><ul><ul><li>Best properties </li></ul></ul><ul><ul><li>Best price </li></ul></ul><ul><ul><li>Purity </li></ul></ul>Fill-in holes in chemistry space Include areas not covered by original collection Covered by Corporate Collection Collaborative Services
  9. 9. Synthesis of Enhancement libraries … Sources of Scaffolds From “Ideas” Database (~2500 ideas) From Chemists “chemical intuition” From “de novo” Scaffold Generation Scaffolds should be vetted for applicability Scaffold Idea Representative subset of reagents “ mini” virtual library Check that library has reasonable property profile and no overlap with known compounds For targeted libraries, use docking or similarity scores to verify desirability of the potential library Shape-based hierarchical clustering is employed to select diverse scaffolds 27,417 meet “rule of 5” 14,322 meet “rule of 4.5” 3,918 meet “rule of 4” using Aldrich reagents ClogP MW Collaborative Services
  10. 10. Careful Reagent Selection … enhance synthetic success Reagent Pool Vendor Catalogs Library Reagents Depending on the library design goals, custom synthesized and novel in-house reagents may also be used Reaction-Compatible Reagents must be compatible with reaction conditions in current and following reaction steps Reagant-Compatible Reagents must not contain competing functional groups Drug-like Cannot contain known toxicophores, etc. Reasonable Available at reasonable cost Collaborative Services
  11. 11. Type of Library Needed Depends on What is Known Lead Optimization Hit Validation or Lead Finding Hit Finding Knowledge of Target Protein X-ray Pharma- cophore Protein Class None Structure Based Design Pharmacophore Based Design Focused Sets Diverse Libraries Need for diversity is inversely proportional to knowledge about the target Degree of Diversity Needed and where you are in the drug-development process Collaborative Services Oprea, Ed. ChemoInformatics in Drug Discovery, Wiley, 2005, p. 45
  12. 12. Focused libraries are rapidly generated by combining high quality sources of library ideas with techniques for filtering these ideas using knowledge of the target. The process is iterative. Each new library adds to the knowledge base. So good SAR will be built into the libraries. Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Virtual Screening Ideas Database Knowledge Base Chemist Ideas de novo Design Rapid Development of Focused Libraries Collaborative Services
  13. 13. Rapid Development of Focused Libraries Ideas can come directly from the chemist or other sources, based on knowledge or intuition. The ideas database consists of reaction protocols for scaffolds, whose analogs have been made or synthetic route has good precedent, combined with sets of well vetted reagents. Our de novo tools use target and synthetic knowledge to generate relevant suggestions. Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Virtual Screening Ideas Database Knowledge Base Chemist Ideas de novo Design Collaborative Services
  14. 14. Rapid Development of Focused Libraries The knowledge base is a continually evolving repository of knowledge about the desired target. Information may come from public sources, such as crystal structures or patents. Information may also come from the customer, for example, results of earlier screening programs against the target of interest. Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Virtual Screening Ideas Database Knowledge Base Chemist Ideas de novo Design Collaborative Services
  15. 15. Rapid Development of Focused Libraries <ul><li>The ideas are coded into “virtual” libraries, providing a pool of millions of compounds as potential candidates. </li></ul><ul><li>How the virtual screening is done depends on the knowledge of the target, methods include: </li></ul><ul><ul><li>Property profiling </li></ul></ul><ul><ul><li>ADMET screening </li></ul></ul><ul><ul><li>Virtual docking </li></ul></ul><ul><ul><li>2D & 3D similarity comparisons </li></ul></ul>Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Virtual Screening Ideas Database Knowledge Base Chemist Ideas de novo Design Collaborative Services
  16. 16. Rapid Development of Focused Libraries The compounds that survive the virtual screening are all potentially active in the target. Generating the library design is the process of reducing this still potentially very large pool to a subset of compounds that can be synthesized, have reasonable reagent reuse, have the best potential to show activity and incorporate SAR to help understand the screening results. Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Virtual Screening Ideas Database Knowledge Base Chemist Ideas de novo Design Collaborative Services
  17. 17. Rapid Development of Focused Libraries Converting a library design into a physical set of compounds to screen is an interactive process involving design and medicinal chemistry. As the synthesis proceeds and the chemistry is better understood, some reagents may not be viable. This knowledge is fed back to design, and replacements chosen to insure the final compounds retain the same level of desirability as the initial set. Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Virtual Screening Ideas Database Knowledge Base Chemist Ideas de novo Design Collaborative Services
  18. 18. Initial screening results in a number of hits and neighborhood analysis can be used to differentiate true positives from false positives. IC 50 data from identified leads can be fed back into the knowledge base to identify additional libraries to synthesis. The leads can also be optimized using more refined techniques such as QSAR/CoMFA to optimize activity or pharmacological properties. Lead Molecules Synthesis Screening Library Design Computer Design Focused Library Candidate Pool Ideas Database Knowledge Base Chemist Ideas de novo Design Rapid Development of Focused Libraries Virtual Screening Collaborative Services
  19. 19. Focused Compound Selection <ul><li>Compounds can be extracted from Existing Collections </li></ul><ul><ul><li>=> Library Enhancement </li></ul></ul><ul><ul><li>Greater compound diversity to choose from </li></ul></ul><ul><ul><li>Limited IP </li></ul></ul><ul><li>Compounds can be Synthesized </li></ul><ul><ul><li>=> Library Design/Synthesis </li></ul></ul><ul><ul><li>Typically 200-300 compounds per scaffold </li></ul></ul><ul><ul><li>Novel IP Position </li></ul></ul><ul><li>Techniques for Library Design </li></ul><ul><ul><li>=> Focus on techniques applicable to large virtual libraries </li></ul></ul><ul><ul><li>Large pool of candidates increases probability of finding good leads </li></ul></ul><ul><ul><li>Methodology </li></ul></ul><ul><ul><ul><li>High-throughput virtual docking </li></ul></ul></ul><ul><ul><ul><li>High-throughput similarity searching </li></ul></ul></ul><ul><ul><ul><li>Property profiling </li></ul></ul></ul><ul><ul><ul><li>CoMFA prediction on virtual libraries </li></ul></ul></ul>Collaborative Services
  20. 20. Extracting a Focused Set from a Vendor Collection <ul><li>Grid chemical space with physiologically relevant descriptor and create clusters </li></ul><ul><li>Select compounds in same clusters as known actives </li></ul>Neighborhood principle: small change in biological activity correspond to small change in valid metric <ul><li>Use neighborhood principle to find valid metrics </li></ul><ul><ul><li>2D fingerprints </li></ul></ul><ul><ul><li>BCUTs </li></ul></ul><ul><ul><li>Topomer fields </li></ul></ul>Collaborative Services 0 0.5 1 1.5 2 2.5 1.00 0.95 0.90 0.85
  21. 21. Scaffold Selection All sources of scaffolds can benefit from analysis Process most important for scaffolds with the least prior medicinal chemistry input Representative reagents Pool of scaffolds Virtual Libraries Pool of Scaffold candidates Desired scaffold subset Appropriate physical properties Leadlike ADME/tox Appropriate match to target Efficiency and cost of design Similarity Docking Models Diversity analysis Match to target Novelty OptDesign Goal is to rank potential scaffolds on ability to produce a good pool of synthetic candidates. This can be very fast using our virtual screening technology Collaborative Services
  22. 22. Generating a Focused Library Design <ul><li>Collect knowledge of the target </li></ul><ul><ul><li>Literature data </li></ul></ul><ul><ul><li>Customer proprietary/screening data </li></ul></ul><ul><li>Collect a pool of synthetic routes to novel scaffolds </li></ul><ul><ul><li>Chemist suggestions </li></ul></ul><ul><ul><li>Ideas database </li></ul></ul><ul><ul><li>De novo scaffold generation </li></ul></ul><ul><li>Assess scaffold ideas </li></ul><ul><ul><li>Generate representative libraries </li></ul></ul><ul><ul><li>Using target knowledge to assess potential activity </li></ul></ul><ul><li>Design libraries around best scaffolds </li></ul><ul><ul><li>In collaboration with chemists to ensure most relevant products </li></ul></ul>Collaborative Services
  23. 23. Full Library Design Synthetic Scheme Reagent Pool Virtual Library Monomer Pool Drug/Lead-like Pool Initial Design Final Design <ul><li>Extract/Transform </li></ul><ul><li>Filter </li></ul><ul><li>Reagent Compatible </li></ul><ul><li>Drug-like </li></ul><ul><li>Chemist Inspection </li></ul>Reaction Compatible Drug/Lead-like Chemist Inspection <ul><li>Initial Design is Reviewed </li></ul><ul><li>Synthetic success validating reagents </li></ul><ul><li>Customer feedback on desirability of products </li></ul><ul><li>Several iterations needed if chemistry difficult </li></ul><ul><li>Extract Subset </li></ul><ul><li>Similarity to target </li></ul><ul><li>Docking scores </li></ul><ul><li>Pharmacophore match </li></ul>Enumerate Library Property Filtering Library Definition Add Target Knowledge Extract Design Review Collaborative Services
  24. 24. Physical Property Profiling <ul><li>Poor absorption or permeation of an orally administered drug is more likely to occur if any two of these criteria are violated: </li></ul><ul><ul><li>Molecular weight is greater than 500 </li></ul></ul><ul><ul><li>Lipophilicity is high (ClogP is greater than 5) </li></ul></ul><ul><ul><li>Number of Hydrogen bond donors is greater than 5 </li></ul></ul><ul><ul><li>Number of Hydrogen bond acceptors is greater than 10 </li></ul></ul>Typically libraries are designed to meet Lipinski’s “Rule of 5” Properties of Oral Drugs Categorized by Gene Family Hopkins, et al, Nature Biotechnology 2006, 7, 805-815 But in reality properties need to be tailored to target being addressed Collaborative Services 9 7 4 5.7 505 Protein Kinases 12 8 4 4.8 572 Serine Proteases 9 8 2 5.2 465 Phospho-diesterases 17 10 8 6.5 752 Peptide GPCRs 10 6 2 7.3 495 Nuclear Hormone Receptors 7 6 3 4.7 430 Ion Channels 8 6 2 5.6 460 Aminergic GPCRs 90% Rbonds 90% HBA 90% HBD 90% ClogP 90% MW
  25. 25. ADMET Predictions Poor BBB Permeability Good BBB Permeability Moderate BBB Permeability High bioavailability (good solubility and Permeability) Low bioavailability (poor solubility and permeability) Problematic bioavailability (poor solubility and good permeability) Problematic bioavailability (good solubility and poor permeability) Collaborative Services Delaney, J. S. J. Chem. Inf. Comput. Sci. 2004 , 44 , 1000 – 1005. ESOL – Estimated Aqueous Solubility
  26. 26. <ul><li>Identify Reasonable Binding Modes </li></ul><ul><ul><li>Cluster on RMS distance between docked structures </li></ul></ul><ul><ul><li>Visually inspect examples from each mode </li></ul></ul>Virtual Docking <ul><li>Dock a Diverse Subset of the Virtual Library </li></ul><ul><ul><li>Start with filtered virtual library </li></ul></ul><ul><ul><li>Select by diversity or similarity </li></ul></ul><ul><li>Dock Complete Virtual Library </li></ul><ul><ul><li>Use identified base poses </li></ul></ul><ul><ul><li>Select products to synthesize using scores and similarity </li></ul></ul>Collaborative Services -17.2 -0.8 -32.7 Abl -21.9 -26.7 -25.6 Best -5.1 2.7 2.8 Worst -14.4 -12.1 -11.6 Avg FGFr CDK2 P38 Mode 1 Mode2 Mode 3 Representative Structures in Abl
  27. 27. Topomer Distances Split molecule into 2-3 fragments Rule-based alignment of fragments onto a grid Use probe atom to calculate steric potential at grid points Topomer Fields Topomer distances are the sum of the pair-wise differences between the fields summed over the fragments plus alignment and steric penalties An example result from a Tripos validation study is shown above Similarity Searching Topomer based searching is effective in searching large virtual libraries Topomer fields can also be used for CoMFA predictions in virtual libraries Collaborative Services N F O O N + H 7.6 uM Query Structure Lead Hop D4.4
  28. 28. Example - Tagamet and Zantac: both do the same thing in the body Sulfur Ring Nitrogen rich section <ul><ul><li>What do they have in common in 3D? </li></ul></ul>H-bond Donor H-bond Acceptor Hydrophobe <ul><ul><li>What do they have in common in 2D? </li></ul></ul>Pharmacophore Modeling Goal of pharmacophore modeling is to find matches to key 3D features Collaborative Services
  29. 29. <ul><li>Design is an Iterative process </li></ul><ul><ul><li>What pleases the chemist often doesn’t please the computer and vice versa </li></ul></ul><ul><ul><li>All designs are a balance of competing requirements </li></ul></ul><ul><li>Designs have a good pedigree </li></ul><ul><ul><li>Developed from synthetic routes provided by experienced medicinal chemists </li></ul></ul><ul><ul><li>Reagent and reaction filters insure that designs can be converted to products </li></ul></ul><ul><ul><li>Modification of scaffold and/or reagents are done in collaboration with chemists to insure high value products are actually made </li></ul></ul><ul><li>High throughput techniques allow for thorough investigation of options </li></ul><ul><ul><li>Large numbers of ideas can be evaluated for appropriate properties, docking score and similarity to targets </li></ul></ul><ul><li>Goal is to obtain lead compounds with </li></ul><ul><ul><li>Improved biological activity </li></ul></ul><ul><ul><li>Improved target selectivity </li></ul></ul><ul><ul><li>Acceptable ADME-Tox profile </li></ul></ul><ul><ul><li>Patentable position </li></ul></ul>Summary of Focused Library Design Collaborative Services
  30. 30. Summary of the Complete Process <ul><li>Most compounds that enter the drug discovery process fail </li></ul><ul><ul><li>Use target knowledge early to eliminate poor candidates </li></ul></ul><ul><li>R educe the attrition rate through intelligent (informatics-based) application of appropriate tools </li></ul><ul><ul><li>Efficient library design process </li></ul></ul><ul><ul><li>Property filters and predictions </li></ul></ul><ul><ul><li>Activity prediction tools (receptor and ligand based) </li></ul></ul><ul><ul><li>Chemistry expertise and knowledge </li></ul></ul><ul><li>Goal is to obtain lead compounds with </li></ul><ul><ul><li>Appropriate biological activity </li></ul></ul><ul><ul><li>Appropriate target selectivity </li></ul></ul><ul><ul><li>Acceptable ADME-Tox profile </li></ul></ul><ul><ul><li>Patentable position </li></ul></ul><ul><li>All accomplished in as short a time as possible </li></ul>Collaborative Services
  31. 31. <ul><li>Design Environment </li></ul><ul><ul><li>Building & rapid searching of large databases </li></ul></ul><ul><ul><ul><li>Search criteria - fingerprint, topomer, feature matching </li></ul></ul></ul><ul><ul><ul><li>Input from experimental results & availability of reagents </li></ul></ul></ul><ul><ul><li>Captures chemistry we have developed/conceived - integrated with synthetic validation </li></ul></ul><ul><ul><ul><li>Evolution of knowledge base </li></ul></ul></ul>Strategic & Operational interface … optimal process engineering <ul><li>Production Environment </li></ul><ul><ul><li>State of the Art facilities </li></ul></ul><ul><ul><ul><li>Parallel Medicinal Chemistry </li></ul></ul></ul><ul><ul><ul><li>High-throughput robotics </li></ul></ul></ul><ul><ul><ul><li>Automated analysis & purification </li></ul></ul></ul>Both seamlessly integrated with in-house informatics system Collaborative Services
  32. 32. We know which compounds to make Design Environment Production Environment Difficult Simple Distant Close Highest interest & earliest delivery High interest & long delivery Synthesis development & Reagent synthesis Low interest & later delivery Low interest & quick delivery Every compound we make is designed and tracked via the informatics system Collaborative Services
  33. 33. Project Consultancy & Management <ul><li>Consultancy </li></ul><ul><ul><li>Work with client to establish project objectives </li></ul></ul><ul><ul><li>Analyze overall resourcing including any outsourcing </li></ul></ul><ul><ul><li>Identify major project milestones </li></ul></ul><ul><ul><li>Troubleshoot key issues </li></ul></ul><ul><ul><li>Define overall project plan and workflow </li></ul></ul><ul><li>Management </li></ul><ul><ul><li>Help define scope & goals of project </li></ul></ul><ul><ul><li>Monitor progress against goals & budget </li></ul></ul><ul><ul><li>Maintain regular contact with client counterpart </li></ul></ul><ul><ul><li>Active member of project Steering Committee </li></ul></ul>Collaborative Services
  34. 34. Contract Research <ul><li>Flexible approach </li></ul><ul><ul><li>FTE-based model gives client greatest flexibility in steering project and optimising resource usage </li></ul></ul><ul><ul><li>“ Mix and Match” chemistry, design, analysis and purification as workflow dictates </li></ul></ul><ul><li>Dedicated project team </li></ul><ul><ul><li>Project Manager assigned at earliest possible stage </li></ul></ul><ul><ul><li>Key named personnel assigned for duration of project </li></ul></ul><ul><ul><li>All documentation project/client specific </li></ul></ul><ul><ul><li>Regular project updates provided to client </li></ul></ul><ul><li>Dedicated laboratory space </li></ul><ul><ul><li>Provision for sensitive projects to have dedicated lab space if required </li></ul></ul>Contract Research
  35. 35. Screening Libraries <ul><li>Off the shelf </li></ul><ul><ul><li>Cherry-pick from ~25000 compounds </li></ul></ul><ul><ul><li>Catalogue continually being updated </li></ul></ul><ul><li>Custom request </li></ul><ul><ul><li>Can be made to customer’s specifications </li></ul></ul><ul><ul><ul><li>All compounds designed </li></ul></ul></ul><ul><ul><li>Typical library size 200-2000 compounds </li></ul></ul><ul><ul><li>Derived from database containing >2500 ideas </li></ul></ul><ul><ul><li>Supplied on exclusive basis if required </li></ul></ul><ul><ul><li>Typically >85% purity by LC-MS </li></ul></ul>Screening Libraries
  36. 36. Novel Intermediates, Building Blocks & Custom Synthesis <ul><li>Wide range of intermediates and building blocks </li></ul><ul><ul><li>Many available from stock </li></ul></ul><ul><ul><li>Rapid turnaround from order on larger amounts </li></ul></ul><ul><ul><li>Analoging around specific series readily achieved </li></ul></ul><ul><li>Custom synthesis routinely undertaken </li></ul><ul><ul><li>From mg to multi-kg scale </li></ul></ul><ul><ul><li>Scale-up trialling where no precedent exists </li></ul></ul>Novel Intermediates
  37. 37. Custom Analysis & Purification <ul><li>Custom NMR and LC-MS services </li></ul><ul><ul><li>Can be tailored to customer’s specific requirements </li></ul></ul><ul><ul><li>Single run or batchwise processing </li></ul></ul><ul><li>Custom analysis & purification </li></ul><ul><ul><li>Utilising customer defined protocols </li></ul></ul><ul><ul><li>Protocol development undertaken </li></ul></ul><ul><ul><li>Purified samples provided in customer’s desired format </li></ul></ul>Custom A&P
  38. 38. Summary Exelgen Discovery provides a broad spectrum of competitively priced Discovery Products and Services. For further information or enquiries please contact: Exelgen Discovery Bude-Stratton Business Park Bude EX23 8LY Cornwall, UK Dr Phil Billington Business Development Email: Mob: Dr Julian Smith Principal Scientist Email: Mob: Tel/Fax: +44 (0)1288 356500 [email_address] +44 07973 493403 [email_address] +44 07805 571662

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