AstraZeneca PLC · LSE:AZN

AstraZeneca — Investor Presentation (1999)

15 slides from AstraZeneca's investor presentation, 1999

  1. Slide 1: Building World Leading AstraZeneca Discovery

    AstraZeneca Discovery Jan M Lundberg Senior Vice President Global Discovery Building World Leading AstraZeneca Discovery

  2. Slide 2: How to further build AstraZeneca Discovery

    AstraZeneca Discovery h How to further build AstraZeneca Discovery to the major force in pharma AstraZeneca Discovery h How to further build AstraZeneca Discovery to the major force in pharma h Excellent complementarity

  3. Slide 3: How to further build AstraZeneca Discovery

    AstraZeneca Discovery h How to further build AstraZeneca Discovery to the major force in pharma h Excellent complementarity h Maximise productivity and quality AstraZeneca Discovery h How to further build AstraZeneca Discovery to the major force in pharma h Excellent complementarity h Maximise produ

  4. Slide 4: How to further build AstraZeneca Discovery to the major force in pharma

    How to further build AstraZeneca Discovery to the major force in pharma Optimise the Discovery organisation 3500 people in global organisation Mölndal Consolidation to achieve critical Södertälje Lund mass Charnwood Build on existing strengths, Alderley Montreal rebalance Research Areas and Reims Bo

  5. Slide 5: AstraZeneca global Discovery

    AstraZeneca global Discovery Disease focus Respiratory/ Cardiovascular/ Cancer/ CNS/ linked to Inflammation Gastrointestinal Infection Pain Control Therapy Areas Global platform Enabling Science & Technology (EST) Improve Safety Assessment, Drug Metabolism development success & Pharmacokinetics (DMP

  6. Slide 6: Integrating Discovery into Development

    Integrating Discovery into Development Target Hit Lead Lead Concept Development Launch Identification Identification Identification optimisation testing for launch Target Lead Candidate Stringent criteria drug Therapy Area input Medical pull Enabling science & technology Technology push Toxicology,

  7. Slide 7: Complementarity strengthens drug hunting

    Complementarity strengthens drug hunting h Spanning most major disease areas – Gastrointestinal (Gastro Esophageal Reflux / Irritable Bowel Syndrome) – Cancer (Solid tumours) – Respiratory (Asthma/Chronic Obstructive Pulmonary Disease) – Inflammation (Autoimmune) – Cardiovascular (Thrombosis) – Infe

  8. Slide 8: Human genetics and compound management

    Human genetics Linkage Response analysis variability 1 0.5 0 0 1 Broader genetics platform internally and externally Compound management b Liquids & solids b Fast reformatting & subsetting b Size, quality & diversity of collection

  9. Slide 9: Advanced statistical science

    Bioinformatics - genomic data exploitation Rapid access to in silico Discovery Advanced statistical science Physical property-based compound profiling Library optimisation - “drug like” Absorption, metabolism, toxicity

  10. Slide 10: Mathematical modelling of human physiology

    Mathematical modelling of human physiology Encyclopaedia of life Cell Nucleus Chromosome DNA From molecules, mRNA pathways, cells, organs amino acids to integrated physiology Protein in health & disease Maximise productivity and quality “Intelligent and predictable drug discovery machine”

  11. Slide 11: Integrating enabling technologies into drug hunting

    Integrating enabling technologies into drug hunting Lead CD Target Hit Lead Identification Identification Identification optimisation Identification Validation Production Integrating enabling technologies into drug hunting Lead CD Target Hit Lead Identification Identification Identification optimisa

  12. Slide 12: Integrating enabling technologies into drug hunting

    Integrating enabling technologies into drug hunting Lead CD Target Hit Lead Identification Identification Identification optimisation R1 N O N O R2 O R3 Combinatorial/medicinal Toxicogenomics chemistry Integrating enabling technologies into drug hunting Lead CD Target Hit Lead Identification Identif

  13. Slide 13: Capture more value from in vivo & in vitro

    Capture more value from in vivo & in vitro In silico R&D - Pharmacome Data integration & mining Disease information Target B Clinical trials Pharmacogenomics/ structure genetics Chemical structure Metabolism, and compound kinetics, bank Disease toxicology models Deliver the promise

  14. Slide 14: Tailored treatment

    Tailored treatment Disease mechanism Diagnostic Target Right patient Right drug Optimal dose Optimal delivery Optimal therapy The ultimate therapy - prevention or cure AstraZeneca Discovery h How to further build AstraZeneca Discovery to the major force in pharma – include expanding in the US h Exce

  15. Slide 15: Slide 15

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