Alnylam Pharmaceuticals, Inc. · NASDAQ:ALNY
Alnylam Pharmaceuticals — Technical Presentation (September 2009)
40 slides from Alnylam Pharmaceuticals's technical presentation, Sep 24, 2009
Slide 1: Alnylam RNAi Roundtable
Alnylam RNAi Roundtable September 24, 24 2009
Slide 2: Alnylam Forward Looking Statements
Alnylam Forward Looking Statements This presentation Thi t ti contains t i f forward-looking d l ki statements. t t t There are a number of important factors that could cause actual results to differ materiallyy from the results anticipated p by these forward-looking statements. These important fact
Slide 3: RNAi Lead Development (RLD)
RNAi Roundtable - September 24, 2009 RNAi Lead Development (RLD) 3
Slide 4: RNA Interference
RNA Interference Synthetic siRNA dicer dsRNA Cleavage Natural Process St d separation Strand ti off RNAi Targeted Gene RISC Complementary pairing Silencing mRNA (A) n Cleavage mRNA degradation (A)n 4
Slide 5: Achieving RNAi as Therapy
Achievingg RNAi as Therapy py • Introducing “drug-like” drug like properties into siRNAs » Potency » Selectivity S l ti it » Stability • Achieving delivery to target tissues/cells » PK/PD/Biodistribution » Cellular uptake 5
Slide 6: Alnylam RNAi Product Platform
Alnylam RNAi Product Platform T i siRNAs Turning iRNA into i t Drugs D Lead Selection Lead Optimization Delivery conjugation formulation Incorporate minimal number of modifications required for appropriate pharmaceutical properties y siRNA design y Stabilization y PK/PD y Selectivity screen y Potenc
Slide 7: Alnylam RNAi Product Platform
Alnylam RNAi Product Platform T i siRNAs Turning iRNA into i t Drugs D Lead Selection Lead Optimization Delivery conjugation formulation Incorporate minimal number of modifications required for appropriate pharmaceutical properties y siRNA design y Stabilization y PK/PD y Selectivity screen y Potenc
Slide 8: RNAi Lead Discovery
RNAi Lead Discovery Starting Pool Design/Specificity/Crossreactivity (Screening Set) In vitro Activity Screen 3-6 Months to Optimization/Stabilization/ Immunostimulation results in NHP’s In vivo pharmacology Lead Candidate 8 Confidential
Slide 9: siRNA Design Considerations
SiRNA Design Considerations A hit t • Sequence Architecture S • Chemistry Ch i t 9
Slide 10: siRNA Design
siRNA Design A hit t Architecture N t l canonical Natural, i l U t l non-canonical Unnatural, i l 5´ 3´ 5´ shRNA 3´ 5´ 3´ Design Longer siRNA 5´ 3´ “blunt-end”, “dicer siRNA 3´ 5´ substrate” Length 19-23 >24 Chemistry Yes/No; Lower COGS Yes/No; Higher COGS Biology y↑ Potency Off-target ↓ Immunostimu
Slide 11: siRNA Design
siRNA Design Sequence Optimal siRNAs x xx x Mouse • Cross reactivity x xx Rat ………. x x xx Cyno y » Splice variants » Viral isolates » Species orthologs • Specificity x Off-Target 1 » Hit only target sequences of x Off-Target 2 interest 11
Slide 12: siRNA Design
siRNA Design Sequence Crossreactvity Human Cyno y Intersection of species with perfect match 19mers typically 5-20% of human oligos depending on species Rat 12
Slide 13: siRNA Design
siRNA Design Sequence Specificity mRNA / transcript 5’-TTGCGAAUCGUGCAUGCAGUGACCGA-3’ 3’-CUUAGCACGUACGUCACUG-5’ siRNA antisense strand 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 ‘ th ’ ‘other’ > ‘cleavage ‘ l it ’ > ‘seed’ site’ ‘ d’ Mismatch Region Scoring • Off-target score is evaluated for ea
Slide 14: Effect of Architecture on Specificity/Crossreactivity
siRNA Design Effect ff off Architecture on S Specificity/Crossreactivity f /C Number of Specific siRNA Candidates Species Cross-Reactivity 50 c siRNAs’ 2500 45 40 # siRNAs (x1000) 35 2000 ercent of specific 30 25 1500 20 15 1000 10 5 pe 500 0 19 21 23 25 27 29 31 33 35 0 17 19 21 23 25 27 29 31 33 3
Slide 15: siRNA Design: Chemistry
siRNA Design Chemistry Unmodified siRNA Modified siRNA Prevention of exonuclease degradation • phosphorothioate C1 0 2 4 8 24 Full-Length Full Length Degraded Prevention of endonuclease degradation • 2’-F • 2’-OMe Not only is chemistry important for stability, but it also crucial for eliminating imm
Slide 16: siRNA Design Strategy Depends on Goal
siRNA Design Strategy Depends on Goal • siRNAs iRNA designed d i dbbased d on emerging i efficacy ffi rules l » Smaller sets (~20-50) of modified duplexes synthesized and screened for efficacy empirically » Mini dose response done as primary screen • siRNAs designed based on cross-reactivity and spe
Slide 17: Efficacy-based siRNA Design
Optimal Design Efficacy-based siRNA Design • Large L d datasets t t allow ll evaluation l ti of “rules” for predicting efficacy • Rules can be useful to direct siRNA modification when sets siRNA #s Number Of Rules Broken are limited s • Several rules for antisense strand determined thus far • Rules
Slide 18: siRNA Synthesis
siRNA Synthesis 18
Slide 19: Small Scale RNA Synthesis
Small Scale RNA Synthesis Single strands • Synthesis S th i ththroughput h t (96 wellll fformat): t) ~ 600 single strands /wk • Purification process: IEX-HPLC, SEC-; ~400 strands/wk • In-process QC testing – IEX-HPLC, LC-MS, UV • Single strand purity: 75-85% Chemical modifications • Ribo, 2’Ome, 2’F
Slide 20: Purification and Analytics
Purification and Analytics Blue: Crude Red: Purified Ion Exchange IEX LC-MS Desalting 20
Slide 21: Efficacy Screening
Efficacy Screening 21
Slide 22: Liquid Handling Robot for Screening
Liquid Handling Robot for Screening 96-Tip-Head delivers in 384 well format for rapid assay » cDNA Synthesis » RNA purification » qPCR 22
Slide 23: Canonical siRNAs Equipotent with Dicer Substrate siRNAs
Canonical siRNAs Equipotent with “Dicer Substrate” siRNAs 10 nM Screen Gene 1 Canonical Dicer control siRNAs 10 nM Screen Gene 2 Ca o ca Canonical Dicer control siRNAs 23
Slide 24: Identifying High Potency siRNAs: Example 1
Identifying High Potency siRNAs Initial In Vitro Screens: Example 1 Single dose screen 1.8 1.6 1.4 1.2 1 08 0.8 0.6 0.4 0.2 0 Candidate siRNAs DRCs of best candidates... ...versus a less efficient one 1.1 0.6 1 0.5 0.9 0.8 0.4 06 0.6 IC50 3.2 p pM 0.7 0.3 0.2 0.4 0.5 IC50 0.45 nM 0.1 0.2 0 IC50 168
Slide 25: Identifying High Potency siRNAs: Example 2
Identifying High Potency siRNAs Initial In Vitro Screens: Example 2 1.4 Target remaining 1.2 1 0.8 0.6 0.4 0.2 0 Candidate siRNAs DRC off b DRCs bestt candidate did t DRCs of less efficient candidate 70 95 % of Remaining Message 60 % of Remaining Message 85 50 75 40 65 30 55 IC50 0.6 nM 20 45 10 IC5
Slide 26: Active siRNAs Are Not Evenly Distributed
Active siRNAs Are Not Evenly Distributed 1.2 1 0.8 0.6 0.4 0.2 0 1 400 800 1200 1600 1.2 nockdown 0.8 0.4 kn 0 351 700 1.2 0.8 wn knockdow 0.4 0 486 554 26
Slide 27: Considerations for Effective and Sustained Target Silencing
Considerations for Effective and Sustained Target 1 Silencing Target 2 • Many possible correlates to effective t target t knockdown k kd Target 3 » Transcript abundance » Protein/RNA half-life Target 4 » Position along transcript Oliigo count » Genomic/RNA structure Target 5 » Biological g consequen
Slide 28: siRNA Specificity
siRNA Specificity 28
Slide 29: Minimizing Off Target Effects
Minimizing “Off Off Target” Target Effects RISC/miRNA “seed”-mediated • Potential to target homologous sequences in non-target genes » Doench et al., (2003) Genes Dev. 17(4):438-442 » Jackson et al., (2003) Nat Biotech. 21, 635-637 • Solutions » IC50 specificity analysis toward “nearest” homolog's I
Slide 30: Potential Off-Targets Identified for Lead siRNAs
Potential Off-Targets Identified for Lead siRNAs On/Off target sequence On-target transcript 5’ - TTGCGAAUCGUGCAUGCAGUGACCGA - 3’ Off-target 1 5’-NNNNGACUGGUGCAUGCAGUGACNNN-3’ On-target RNA Off-target 2 5’-NNNNGUAUCGAGCUUGCAGUGACNNN-3’ 5’-TTGCGAAUCGUGCAUGCAGUGACCGA-3’ 3’-CUUAGCACGUACGUCACUG-5’ Off-t
Slide 31: Selection Algorithm Minimizes Off-target Silencing
Selection Algorithm Minimizes Off Off-target target Silencing On vs. Off-target Silencing Off-target Silencing 160 1,2 140 0ff-target ession 1 120 ve RLuc expre % Target Expression 0,8 100 80 0,6 60 relativ 0,4 0n-target 40 0,2 IC50 = 0.056 nM 20 Where tested IC50 >50nM 0 0 1x10-5 0,01 10 0 1 2 3 4
Slide 32: Innate Immunity and dsRNA
Innate Immunity and dsRNA Longer and Unmodified siRNA More Likely to Trigger Endosomal ? Receptors TLR3 ? ? TLR9 Key triggers -dsRNA TLR7 TLR8 - ssRNA - ssRNA - DNA - CpG • Sequence -siRNA siRNA - siRNA - siRNA ? • Longer L siRNA iRNA • Unmod. siRNA Cell Inflammatory Membrane Response Key triggers •
Slide 33: Screening Paradigm for Immunostimulatory dsRNAs
Screening Paradigm for Immunostimulatory dsRNAs Ficoll gradient centrifugation Purified PBMC Normal blood donors • Freshly isolated hPBMC Cell Supt have complex set of TNFα/IFNα immune sensors • Protein and RNA-based assays allow sensitive detection of multiple Cell Pellet Multiplex PCR analytes 33
Slide 34: Chemical Modification Can Alter Immunostimulatory Profile of siRNAs
Chemical Modification Can Alter Immunostimulatory Profile of siRNAs 2’OMe, 2’F or deoxy PBMC assay In vitro IFNα In vitro TNFα 600 4000 500 Unmodified 3500 Unmodified 3000 400 TNFα [pg/mll] 2500 300 2000 IFNα [pg/ml] 200 1500 100 Modified 1000 Modified 500 0 Neg -100 Pos Controls 0 Control siRNAs Ne
Slide 35: Selecting for Immunosilent siRNAs
Selecting for “Immunosilent” siRNAs • Compare cytokine induction in in vitro PBMC and in vivo liposomal siRNA • Test 4 immunostimulatory siRNA (A-D) (A D) & 3 non non-immunostimulatory immunostimulatory siRNA (X-Z) (X Z) In Vitro PBMC Assay In Vivo Serum Cytokines 500 IFNα 400 i.v. bolus 4 mg/kg siR
Slide 36: Selecting Immunosilent siRNA is Crucial to Interpretation
Selecting Immunosilent siRNA is Crucial to Interpretation Some In Vivo Models are Sensitive to Immunostimulation Intranvitreal injection y Control siRNAs show anti angiogenic effect y Inhibition of neovascularization by siRNAs in AMD model is TLR3 dependent Kleinman et al. (2008) Nature 452, 591 - 5
Slide 37: RNAi Silencing is Independent of Toll-Like Receptors
RNAi Silencing is Independent of Toll-Like Receptors RNAi efficacy is achieved in Toll-Like Receptor (TLR) knock-out mice • Demonstrates unambiguous distinction of RNAi effects from TLR-related biology • Addresses concerns raised by Ambati et al. paper (Nature, 452:591-7, Apr. 2008) TLR 3 Knock-Out
Slide 38: RNAi Lead Discovery Summary
RNAi Lead Discovery Summary • RLD at Alnylam has developed into a robust and industrialized process » Identification of cross-reactive and specific siRNAs y » Small scale synthesis of modified compounds in 96-well format enables tiling across genes » Rapid efficacy/potency screens routinely identify
Slide 39: RLD Platform Supports Collaborations
RLD Platform Supports Collaborations • The RLD capability supports an extensive collaboration ll b ti network t k where h Al Alnylam l can supply l top quality siRNAs to partners: » Multiple academic groups specializing in disease areas – Metabolic/CV: Brown Brown, Goldstein Goldstein, Horton Horton
Slide 40: Future Directions
Future Directions • Refinement of design paradigm built off expanded datasets and evolution of field • Increased automation • Continued optimization of secondary screens » Potency » Off-target effects » Mechanism of action 40
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