Considerations for
RNAi Therapeutic Design
Life Science Technology Symposium
Iselin, NJ
16 September 2009
Dr. Paul Bauer
f...
Pfizer RNAi Therapeutic Unit
 structural modifications
 expanding IP space
 screening and SAR development
 targeting a...
Strategic approach has 3 components:Strategic approach has 3 components:
Design Platform
Delivery Platform
Therapeutic Pro...
4
RNAi Therapeutic Opportunities
Selection Criteria
• clinical product concept
• market assessment
• knowledge of target a...
RNAi Therapeutic Critical Path
5
Sequence Design
& Synthesis
Delivery Design
& Synthesis
Pre-clinical
GLP
Delivery
Assays
...
RNAi Therapeutic Critical Path
6
Sequence Design
& Synthesis
Delivery Design
& Synthesis
Pre-clinical
GLP
Delivery
Assays
...
in silico sequence design
7
Algorithm considerations
• sequence specificity
• splice regions/SNPs
• off-target effects
• t...
mRNA knockdown screening
plated
siRNA
• Mon (20 plates)
choose format (1pt triplicate,
3pt triplicate, 10pt IC50) and
top ...
Bar Chart
R_start
0
20
40
60
80
100
71 366 611 792 969 1089 1180 1275 1350 1402 1528 1779 1852 1943 2140 2364 2411 2687
%k...
Scatter Plot
C7577D_.4nM
-20
0
20
40
60
80
0 10 20 30 40 50 60 70 80
Compare Cell Lines A & B
10
%knockdown@0.4nM
CellLine...
Common modifications and designs
11
modifications designs
5’
5’
3’
3’
5’
5’3’
3’
RISC substrates
Dicer substrates
RNA
DNA
...
Bar Chart
R_start
-20
0
20
40
60
80
1390 1403 1419 1479 1553 1688 1770 1785 1796 1827 1853 1906 1937 1948 1988 2090
Gene W...
Scatter Plot
R_C7576D HIF1a_HUH7.5 % @ 0.4nM
-20
0
20
40
60
80
-10 0 10 20 30 40 50 60 70 80
siRNA Designs #1, #2, and #3
...
RNAi mechanism of action
14
purity of siRNA
stability to nucleases
interaction with delivery vehicle
“Formulation”
entry i...
Formulation
15
• purity
• stability
• interaction with delivery vehicle
• common delivery options for siRNA
from
Dharmacon...
Internalization
16
• fluorescently labeled siRNA
visualized by confocal microscopy
• majority of siRNA lipoplexes
internal...
Association
17
0 10 20 30 40 50 60 70 80 90 100 110
0
10
20
30
40
50
60
70
KDspec.= 3.9± 0.5 nM
[PAZ] (nM)
Intensity(RU)
0...
Variation
18
• Dicer and Ago2 levels vary between cell lines and
disease states
• mRNA synthesis rates, steady state level...
Accessibility
19Zhang, et al. Nucl. Acids Res. 31:e72 (2003)
• mRNA accessibility site tagging
• microarray profiling
• re...
Activity in vitro
20
position along gene
Assay Conditions:
[mRNA substrate] = 5 nM
[siRNA] = 50 nM
75 µg/mL S100 fraction ...
Considerations for RNAi
Therapeutic Design
21
Part of
Mechanism
Target
Issue?
Cell
Issue?
Design
Issue?
Estimated
Importan...
Acknowledgements
22
• Rob Stanton, Qing Cao, Lingling Shen, Jason Hughes,
Jeremy Little
• Xu Xu, Larry Drew, Meta Foster, ...
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Considerations for RNAi Therapeutic Design

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Considerations for RNAi Therapeutic Design

  1. 1. Considerations for RNAi Therapeutic Design Life Science Technology Symposium Iselin, NJ 16 September 2009 Dr. Paul Bauer former Director of Target Biology, Pfizer RNAi Therapeutic Unit Director of Biology, Forma Therapeutics
  2. 2. Pfizer RNAi Therapeutic Unit  structural modifications  expanding IP space  screening and SAR development  targeting and formulation  RNAi mechanism and processing  disease biology  safety and therapeutic index  PK/PD 2 The RNAi Therapeutic Unit, as part of the Biotherapeutic & Bioinnovation Center, will develop a cutting edge nucleic acid-based drug discovery platform and deliver Phase II clinical successes in Oncology and Metabolic Disease
  3. 3. Strategic approach has 3 components:Strategic approach has 3 components: Design Platform Delivery Platform Therapeutic Programs 3  Delivery (including activity at site)  Potency (sub nM)  Safety (RNA and formulations)  Cost of goods (unmodified GLP RNA >$10K/year)  Immune stimulation  Off-target effects  Stability and duration  Intellectual property Primary Issues for RNAi Therapy
  4. 4. 4 RNAi Therapeutic Opportunities Selection Criteria • clinical product concept • market assessment • knowledge of target and disease, particularly clinical • genetic linkage of target or pathway in human samples • validation of target through chemical or RNAi inhibition, overexpression, or genetically modified mouse phenotype • feasibility for RNAi sequence design and assays • feasibility for selective delivery and possible targeting ligands • availability of cell and animal models of disease • assessment of potential safety issues • applicability of target to other diseases Current RNAi Clinical Programs
  5. 5. RNAi Therapeutic Critical Path 5 Sequence Design & Synthesis Delivery Design & Synthesis Pre-clinical GLP Delivery Assays In Vitro ADME In Vitro Toxicology Cell-based Assays In Vivo Efficacy In Vivo Toxicology In Vivo ADME Disease Identification Scale-up GMP Biochemical Assays Clinical IND Biomarker Development Formulation Synthesis In Vivo Delivery Target Selection
  6. 6. RNAi Therapeutic Critical Path 6 Sequence Design & Synthesis Delivery Design & Synthesis Pre-clinical GLP Delivery Assays In Vitro ADME In Vitro Toxicology Cell-based Assays In Vivo Efficacy In Vivo Toxicology In Vivo ADME Disease Identification Scale-up GMP Biochemical Assays Clinical IND Biomarker Development Formulation Synthesis In Vivo Delivery Target Selection
  7. 7. in silico sequence design 7 Algorithm considerations • sequence specificity • splice regions/SNPs • off-target effects • thermodynamic stability • immune or toxic motifs Recommended approach for cell-based screening: • identify desired cell line and function • test a variety of transfection agents for efficacy and toxicity using a control gene • use in silico algorithms to develop ~5 sequences against gene of interest • optimize conditions (concentration, duration, etc.) • develop ~2 mismatch control sequences • screen for functional activity Cenix algorithm Kinase
  8. 8. mRNA knockdown screening plated siRNA • Mon (20 plates) choose format (1pt triplicate, 3pt triplicate, 10pt IC50) and top conc. (10nM, 3nM) transfection • Tues/Wed (20 plates) storage SelecT cells bDNA detection • Thurs/Fri (40 plates w/controls) data analysis • Mon/Tues after (in database) • Mon (20 Plates & 3 Flasks) storage Design Teams Disease Teams chemical synthesis storage new retest prioritization mRNA LE CE BL Panomics bDNA assay 8
  9. 9. Bar Chart R_start 0 20 40 60 80 100 71 366 611 792 969 1089 1180 1275 1350 1402 1528 1779 1852 1943 2140 2364 2411 2687 %knockdown@0.4nM Gene Walk Cell Line A 9 position along gene
  10. 10. Scatter Plot C7577D_.4nM -20 0 20 40 60 80 0 10 20 30 40 50 60 70 80 Compare Cell Lines A & B 10 %knockdown@0.4nM CellLineA % knockdown @0.4nM Cell Line B
  11. 11. Common modifications and designs 11 modifications designs 5’ 5’ 3’ 3’ 5’ 5’3’ 3’ RISC substrates Dicer substrates RNA DNA modified base 5’ 5’ 5’ 5’ 5’ 5’ 5’ 5’ 3’ 3’ 3’ 3’ 3’ 3’ 3’ 3’
  12. 12. Bar Chart R_start -20 0 20 40 60 80 1390 1403 1419 1479 1553 1688 1770 1785 1796 1827 1853 1906 1937 1948 1988 2090 Gene Walk Designs #1, #2, and #3 12 position along gene %knockdown@0.4nM
  13. 13. Scatter Plot R_C7576D HIF1a_HUH7.5 % @ 0.4nM -20 0 20 40 60 80 -10 0 10 20 30 40 50 60 70 80 siRNA Designs #1, #2, and #3 Design #1 vs. Design #2 Scatter Plot L_C7576D HIF1a_HUH7.5 % @ 0.4nM -20 0 20 40 60 80 -20 0 20 40 60 Design #1 vs. Design #3 13
  14. 14. RNAi mechanism of action 14 purity of siRNA stability to nucleases interaction with delivery vehicle “Formulation” entry into cell entry into cytosol “Internalization” association with RISC complex activity of Dicer “Association” accessibility of mRNA “Accessibility” duration of active complex activity of complex “Activity” “Variation”level of RISC components level of Dicer kinetics of mRNA
  15. 15. Formulation 15 • purity • stability • interaction with delivery vehicle • common delivery options for siRNA from Dharmacon Nanocarriers Liposome Nanosphere Nanocapsule Micelle Conjugates Polymer Dendrimer Cationic polymer and/or lipid + + + Complexes Macromolecule
  16. 16. Internalization 16 • fluorescently labeled siRNA visualized by confocal microscopy • majority of siRNA lipoplexes internalize via endocytosis • recent data suggests that functional siRNA may not enter this way Engelke & Rossi Meth. Enzymol. 392:120 (2005) Lu, et al. Mol. Pharmaceutics 6:763-771 (2009)
  17. 17. Association 17 0 10 20 30 40 50 60 70 80 90 100 110 0 10 20 30 40 50 60 70 KDspec.= 3.9± 0.5 nM [PAZ] (nM) Intensity(RU) 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 0 10 20 30 KDspec.= 12.6± 2.5 nM [Ds 21-mer siRNA] (nM) Intensity(RU) Ago2 PAZ Domain Binding to Immobilized Biotinylated ds 21-mer siRNA ds 21-mer siRNA Binding to Immobilized Ago2 PAZ Domain -10 0 10 20 30 40 50 60 70 80 -30 0 30 60 90 120 150 180 210 240 270 300 Fc=2 Spot=1-r Ago2 PAZ 100 - 1.5625 nM 1/2 dilution Intensity(RU) Time (s) -5 5 15 25 35 45 -30 0 30 60 90 120 150 180 210 240 270 300 Fc=2 Spot=1-r ds 21-mer RNA 1000 - 1.37 nM 1/3 dilution Intensity(RU) Time (s)
  18. 18. Variation 18 • Dicer and Ago2 levels vary between cell lines and disease states • mRNA synthesis rates, steady state levels, and degradation rates of target genes also vary • target sequence can differ between species used for efficacy, safety, pre-clinical, and clinical models Merritt, et al. NEJM 359:2641-50 (2009)
  19. 19. Accessibility 19Zhang, et al. Nucl. Acids Res. 31:e72 (2003) • mRNA accessibility site tagging • microarray profiling • reverse transcriptase priming
  20. 20. Activity in vitro 20 position along gene Assay Conditions: [mRNA substrate] = 5 nM [siRNA] = 50 nM 75 µg/mL S100 fraction of cell lysate 30 min reaction Readout: siRNA-dependent RNA substrate degradation by qPCR
  21. 21. Considerations for RNAi Therapeutic Design 21 Part of Mechanism Target Issue? Cell Issue? Design Issue? Estimated Importance Formulation no no yes low Internalization no yes yes high Association no yes yes unknown Variation yes yes no medium Accessibility yes yes no low Activity yes yes yes high Higher order cell-based assays • Primary human cells (normal and disease) • Functional assays (target, pathway and phenotypic) • Tissue engineered models (single and multiple cell types) • Mechanistic assays (biomarkers, toxicity, metabolism, etc.) • In vivo models (delivery, ADME, function)
  22. 22. Acknowledgements 22 • Rob Stanton, Qing Cao, Lingling Shen, Jason Hughes, Jeremy Little • Xu Xu, Larry Drew, Meta Foster, Yiding Yan, Tracy Chen, Yuxin Wang • Joe Wu, Gayatri Deshmuch, Mark Bernard, Suzanne Jacques-O’Hagan, Meg Mabuchi • Zhigang Wang, Liann Wang, Xiao-Qin Ren • Eugen Uhlmann (Düsseldorf)

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