Pharma Research Revolution in Drug Discovery

Transcription

1 Pharma Research Revolution in Drug Discovery Wolfgang Hartwig Head of Research, Pharmaceuticals Business Group Life Science Revolution at the Turn of the Millennium 1992: Robotic screening 1999: New organs with pluripotent stem cells 2000: Human genome sequenced 1996: Yeast genome sequenced 1995: DNA-Chip : Cloning of mammals becomes standard 1997: Dolly 1st cloned mammal 1989: Automated DNA-sequencing 1991: Robotic synthesis

2 The 90s: Explosion of Knowledge and the Pharma Industry - Fascination and disenchantment - Science: Blast of knowledge in the Life Science Technologies Pharma industry: Number of launches stagnant Deficits in R&D productpipeline Dreadful increase of R&D expenses Knowledge Research productivity Market growth Bayer Pharma Faces Challenging Goals Ensure longterm growth with and above market through increasing launch performance from 0.5 to 2 NCE per year Consequences for Pharma Research: Establish competitive research platform and increase productivity to 20 new development candidates per year

3 To ensure the business goal of 2 NCE per year Pharma Research has to increase its productivity by tenfold No. Dev. Candidates To ensure the business goal of 2 NCE per year Pharma Research has to increase its productivity by tenfold No. Dev. Candidates 20 Strategic Concept: Increase productivity by 30% annually to reach 20 development candidates in Improve efficiency by 17% per year (total 300 %)

4 Bayer Research Strategy To build a competitive research platform major restructuring initiatives were implemented Portfolio Technologies Resources, People Processes, Organization To reach critical capacity Bayer Pharma Research focused in 1997 on 15 indications Therapeutic Research Area Cardiovascular diseases Cancer CNS disorders Respiratory disease Infectious diseases Metabolic disorders Bone disorders % of Budget 26 % 16 % 14 % 12 % 12 % 11 % 8 % Indication Arteriosclerosis Hematology Coronary heart disease Liver fibrosis All tumor types Acute neurology (stroke) Dementia (Alzheimer s disease) Pain Asthma Chronic-obstructive pulmonary disease Bacterial infections Viral infections Diabetes Obesity Osteoporosis

5 Drug Discovery Research is Technology Driven Goal Strategy Implementation Disease? Pathomechanism Molecular target Screening Functional Optimization Drug Preclinical development The Gene Rush is ON The human genome is represented by 100,000 to 150,000 genes All genes will be known within the next few months 5,000-10,000 interesting targets usable for drug discovery expected Probability of success and proprietary rights correlated to timely investment in genomebased approaches Claims for function / use are already made today % of known Genes Prognosis Celera (2000) Prognosis Start HUGO (1988) Narrow time window for investment

6 Bayer Pharma Strategy Goal: Alliance with expert partner to achieve immediate competitive strength Implementation: Millennium Pharmaceuticals selected as leading expert in genomics technologies - leading edge genomics capabilities - fully integrated excellent expert technology platform The BAYER - Millennium Collaboration Millennium deliverables: novel proprietary disease modifying gene targets - technology transfer Collaborative research areas: cardiovascular diseases, cancer, pain, hematology, osteoporosis, liver fibrosis, virology Costs: 465 mio US$ Contract term: 5 years (`98-`03) The new disease modifying genes will enable BAYER Pharma Research to identify 30 drug development candidates

7 Technologies Accelerate Target Discovery Tissue to Gene (I) healthy diseased RNA Tagged cdna Look for differentially expressed genes cdna Arrays Diseased Cells Normal Cells Technologies Accelerate Target Discovery Gene to Target (II) Sequence Function Assay Diseased Cell Normal Cells CTG TGC TTC CTG GGT TCG CTG GCC GTC CTG CTG TGT GTG TGC ACT GAG Sequence analysis Full length cloning Functional characterization (in vitro / in vivo) Tissue distribution Validated molecular target for drug screening Gene of interest Molecular Target

8 Virtual Discovery of Statins Sequence Function Assay Diseased Cell Normal Cells CTG TGC TTC CTG GGT TCG CTG GCC GTC CTG CTG TGT GTG TGC ACT GAG Sequence analysis Full Length Cloning Functional characterization (in vitro / in vivo) tissue distribution Validated molecular target for drug screening Overexpression in Arteriosclerosis Gene: Reductase Gene of interest Overexpression in cells: lipid accumulation in vivo: arteriosclerosis HMG CoA- Reductase essential in cholesterol synthesis Molecular Target ICAST in Cancer is the Most Advanced BAYER-Millennium Gene Target Tissue gene lead compound in 10 months (standard 2.5 years) Discovery of gene that is overexpressed in tumor specimens CTG TGC TTC CTG GGT TCG CTG GCC GTC CTG CTG TGT GTG TGC ACT GAG Full Length Cloning Identification of gene as ICAST Expression Profile: 2/4 breast carcinomas 3/3 colon carcinomas 4/4 lung carcinomas ICAST overexpressed up to 1000-fold in clinical tumor specimens HT-Assay development and screening 2 lead candidates with IC50 < 100nM Current Activities in vivo pharmacology in cancer models Development candidate planned in 12/2000

9 During the last 15 months the BAYER - Millennium collaboration has overachieved the goals 36 drug targets identified by April 2000 (Goal 34) 25 targets in assay development and screening (Goal 13) Lead compounds identified in 4 indications (5 months earlier than expected) 1 st genomics derived development candidate to be expected in 2000 (12 months earlier than expected) Know-how, technology and cultural transfer due to integration of Bayer scientists into Millennium s infrastructure ( collocation model ) Core competencies of partners are complementary to one another The Bayer - Millennium Kooperation Mark Levin, President and CEO Millennium Pharmaceuticals

10 Drug Discovery Research is Technology Driven Goal Strategy Implementation Disease? Pathomechanism Molecular target Screening Functional Bioinformatics Optimization Drug Preclinical development -Technologies produce enormous amount of data 3000 gene sequences and 2000 genomic inputs per day Increase of data by ca. 12 GB per month Bioinformatics expertise necessary for analysis and linking of data

11 -Technologies produce enormous amount of data 3000 gene sequences and 2000 genomic inputs per day Bayer s strategic goal: Increase of data by ca. 12 GB per month Immediate competitiveness by collaboration with bioinformatics expert Bioinformatics expertise necessary for analysis and linking of data Bayer-Lion Bioinformatics Alliance Alliance formed with Lion Biosciences in 1999, leading expert in Bio IT with integrated technology platform Lion Bioinformatics Research Institute (LBRI) in Cambridge, MA established; exclusively working for Bayer IT-platform und software development for all Bayer Life Sciences Continuous worldwide screening of public databases Identification of in silico - gene targets Status April 2000: Intelligent software established 85 in silico gene targets identified 56 patent applications submitted Gene to patent: 1 week

12 Bayer LION Millennium Collaboration Synergies between Bayer s Collaboration Partners Millennium Both Cambridge, MA LBRI 225 qualified targets, expertise in functional genomics provide Bio-IT expertise deliver in silico gene targets and markers BAYER Transforming novel targets into innovative drugs applying HT-screening and chemical expertise New drug leads in cardiovascular, CNS, metabolic, antiinfectives, oncology, bone disease, respiratory, and other indications Drug Discovery Research is Technology Driven Goal Strategy Implementation Disease? Pathomechanism Molecular target Screening Optimization Functional Bioinformatics High Throughput Screening Drug Preclinical development

13 Explosion of Throughput in Drug Screening Screening capacity (substances per day) Ultra High Throughput Screening (UHTS) biochemical tests cell culture High Throughput Screening (HTS) isolated organs recombinant cells receptor binding /day 1999 (60 000/day) Robotics 1 animal experiment First integrated 1536 well UHTS system worldwide will provide more than 200,000 testpoints per day Integrated computerized proprietary screening and hit - identification system - Acceleration of lead generation - Quality improvement by higher data density

14 Screening with cell based assays Drug Discovery Research is Technology Driven Goal Strategy Implementation Disease? Drug Pathomechanism Molecular target Screening Optimization Preclinical development Functional Bioinformatics High Throughput Screening Combinatorial Chemistry

15 Combinatorial Chemistry Substantial increase in No. of compounds synthesized Acceleration of lead optimization substances / laboratory unit / year ~ 20, Strategic Goal: Significant Growth of Test Compound Library Collaboration with external partners Investments in compound acquisition 55 Mio 1997: 0.4 million 2000: 0.9 million single compounds Improvement of logistics: new modern robot-operated repository

16 According to Benchmark Analysis Bayer s Single Compound Library Compares to the Best in Industry No. of compounds ( * 1000) Bayer acquisition internal Competitors 1. Tier 2. Tier 3. Tier Source: Andersen Consulting / Chemical Research In 1999, BAYER Reached Top Tier Status in Key Technologies Technologies (BAYER s-strategy Strategy) (external) 3. Tier 2. Tier 1. Tier Bioinformatics (external, MiFri internal) Chemical Library (internal + acquisition) Combichem (internal) HTS (internal) Competitive strength in all key technologies is critical for success.

17 Bayer Pharma s High Tech Platform Integrates Technology Experts Worldwide Bioinformatics HTS Combinatorial chemistry Protein drugs Bayer Pharma s High Tech Platform is Leading in the Industry Bioinformatics Bayer s... drug discovery platform is arguably one of the best in the global industry. HTS Lehman Brothers Report Combinatorial chemistry Protein drugs

18 The Key Drivers for Revolutionary Techniques are Smart People Hire and retain the most qualified and talented people Performance based incentive system Intensive training programs in key technologies Intranet based world-wide employee know how database Visiting scientist and delegate program to foster knowledge and cultural exchange Exploratory Research Research Process Management Strategic Project Research Concept 60% 25 % 50% Strategic Screen Project months months months Devel. Candidate Success Factors: Goals: Clearly defined product criteria continuous intranet based monitoring review milestones, kill and nurture clear team performance expectations reduce timelines to 24 months continuously increase success rates and improve quality through e.g. pharmacophor informatics, toxicogenomics

19 Results of New Research Strategy 350 % increase in research output within 4 years Continuous overachievement of plan by 25 % Goals adjusted to 10 candidates in 2000 and further 30 % increase / year No. Dev. Candidates Results of New Research Strategy Net portfolio value generated - reached break even in increased to + 40 Mio in is planned to increase to Mio CFROR (Mio )

20 Beginning in 2002 the New Research Strategy will Contribute to New NCE Launches Beginning in 2002 probability of 1 launch / year is > 80% Beginning from 2007 more than 1 launch / year can be expected Steady state is reached in 2011 (2 launches / year) 2 Launches / Year portfolio before 1996 development candidates presentations planned presented Given industry standard success rates of development candidates Since 1996, 26 new chemical entities have been added from research to our development pipeline, covering all therapeutic areas Cardiovascular Diseases Guanylate cyclase stimulator (CHD) cgmp enhancer (CHD) Erythropoietin sensitizer (anemia) Adenosine reuptake inh. (CHD) Plasmin (periph. art. occl.) Guanylate cyclase stimulator (CHD) PDE V (erect. dysfunction) CETP inhibitor (dyslipidemia) Cancer Topoisomerase inhibitor (cancer) Raf kinase inhibitor (cancer) IL2 selective agonist (cancer) Antiinfectives Hepatitis B virus inhibitor HCMV inhibitor Gastroquinolone Pyrimidinone Antibiotic Central Nervous System Adenosine reuptake inhibitor (stroke ) IL4 selective agonist (multiple sclerosis) Cannabinoid agonist (stroke) Respiratory Diseases Tryptase inhibitor (asthma) Metallo-matrix protease inhibitor (asthma) Inhibitor of Na + channel activation (cystic fibrosis) IL4 (asthma) PDE IV (asthma) Bone Diseases Progestin receptor agonist (osteoporosis) Metabolic Diseases Beta 3 adrenoceptor agonist (diabetes) Glucagon antagonist (diabetes)

21 BAYER Pharma Research in 2000 Through strategic alliances and in house core competencies Bayer Research reached top tier status in all key enabling technologies Productivity and efficiency have significantly improved Research output will further increase by 25-30% annually In 2000, 10 development compounds are expected, including the first genomics derived candidate The new research strategy will lead to first launches in 2002 BAYER Pharma Research Synergies Know How International Research Family Key Technologies