Development and Application of RNA Therapeutics Presentation PDF

Development and Application of RNA Therapeutics Kailene Simon, Ph.D. October 29, 2024 Continuation of last week’s lecture Gene and RNA Therapeutic Development  Drug Development is Risky…and Expensive The estimated a...

Development and Application of RNA Therapeutics Kailene Simon, Ph.D. October 29, 2024 Continuation of last week’s lecture Gene and RNA Therapeutic Development  Drug Development is Risky…and Expensive The estimated average pre-tax industry cost per new prescription drug approval is $2 billion IND Submissi on Drug Discovery Preclinical Clinical Trials FDA Review Post-Approval Discovery In Vitro lead ID Phase 1 Phase 2 Phase 3 Provide sufficient Establish large- Pre- Target ID and validation In Vivo potency, evidence for scale Compound Screening PK/PD & MTD 20-100 100-500 1000+ FDA/EMA to verify manufacturing volunteer volunteer volunteer Hit Identification Efficacy in disease s s s safety and efficacy & models Perform Phase IV 3-6 Years 1-2 Years 6-7 Years Total 0.5 – 2 years studies for long- term effectiveness 10,000 100-250 5 clinical 1 drug molecules candidate compoun s ds One Approved Drug For every 10,000 molecules tested in biopharma… one  The Drug Development Process Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt  The Drug Development Process Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Target selection Scientific and Medical Factors Strategic Considerations Practical Considerations  The Drug Development Process Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Target selection Scientific and Medical Factors Strategic Considerations Practical Considerations Target sequence screening Lead identification and Lead optimization Chemical modifications and delivery systems  The Drug Development Process Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Target selection Scientific and Medical Factors Strategic Considerations Practical Considerations Target sequence screening Lead identification and Lead optimization Chemical modifications and delivery systems Preclinical studies In vitro efficacy In vivo PK/PD, safety, toxicology, etc  The Drug Development Process Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Target selection Scientific and Medical Factors Strategic Considerations Practical Considerations Target sequence screening Lead identification and Lead optimization Chemical modifications and delivery systems Preclinical studies In vitro efficacy In vivo PK/PD, safety, toxicology, etc Submission of an Investigational New Drug (IND) application Planning, preparation and execution of a clinical trial Post-approval marketing and safety reporting  Target Selection Criteria and Considerations Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Scientific and Medical Factors 1. Target validation - Robust target validation is crucial to establish that modulating the target will have the desired therapeutic effect. Genetic evidence linking the target to the disease Preclinical studies showing efficacy of target modulation Biomarker research to measure target engagement 2. Druggability - The target needs to be amenable to modulation by a potential therapeutic. Presence of binding pockets (for small molecules) Cellular localization Protein structure information 3. Safety Profile - Potential safety issues related to target modulation need to be evaluated early. Assessment of target expression patterns Evaluation of on-target side effects Consideration of redundancy/compensation mechanisms  Target Selection Criteria and Considerations Target Validation Lead Applicatio Target Target selection is a critical& step in Screening Target the drug discovery Hit-to- process that requires Optimizati Preclinical careful consideration Clinical n& of multiple Marketing Identification Selection Lead Transition Trial factors. Here are some key considerations for target selection Assessme on in drug discovery Approval nt Strategic Considerations 1. Novelty vs Confidence- There is often a trade-off between pursuing novel, first-in-class targets versus established target classes Level of validation/confidence in the target Potential for differentiation from existing therapies Patent landscape and freedom to operate (FTO) 2. Commercial Potential – The market opportunity & unmet medical need should be evaluated. Size of patient population Competitive landscape Pricing and reimbursement outlook 3. Organizational Fit – The target should align with the company’s capabilities and vision Therapeutic focus areas Research Expertise Portfolio strategy  Target Selection Criteria and Considerations Target Validation Lead Applicatio Target Target selection is a critical& step in Screening Target the drug discovery Hit-to- process that requires Optimizati Preclinical careful consideration Clinical n& of multiple Marketing Identification Selection Lead Transition Trial factors. Here are some key considerations for target selection Assessme on in drug discovery Approval nt Practical Considerations 1. Feasibility of Drug Discovery- The likelihood of successfully developing a drug candidate needs to be assessed. Availability of screening assays and animal models Ability to achieve sufficient target coverage/occupancy Challenges in optimizing drug-like properties 2. Development Path – The clinical development strategy and regulatory pathway should be carefully considered. Availability of biomarkers for patient selection/stratification Potential for accelerated approval pathways Design of proof-of-concept studies  Target Selection Criteria and Considerations Target Validation Lead Applicatio Target Target selection is a critical& step in Screening Target the drug discovery Hit-to- process that requires Optimizati Preclinical careful consideration Clinical n& of multiple Marketing Identification Selection Lead Transition Trial factors. Here are some key considerations for target selection Assessme on in drug discovery Approval nt Practical Considerations 1. Feasibility of Drug Discovery- The likelihood of successfully developing a drug candidate needs to be assessed. Availability of screening assays and animal models Ability to achieve sufficient target coverage/occupancy Challenges in optimizing drug-like properties 2. Development Path – The clinical development strategy and regulatory pathway should be carefully considered. Availability of biomarkers for patient selection/stratification Potential for accelerated approval pathways Design of proof-of-concept studies  Lead Identification and Optimization Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Screening, Lead Identification (LI) and Lead Optimization (LO) 1. Target Identification and RNA Design - The first crucial step is identifying a suitable RNA target and designing the RNA molecule Selecting disease-relevant RNA targets through genetic studies, cell-based methods, and functional analyses Designing the RNA construct based on structural and functional insights Optimizing the RNA sequence, including codon optimization and incorporation of modified nucleotides 2. Chemical Modifications – What base and backbone modifications are necessary to accomplish the goal? Backbone mods like PS to improve nuclease resistance, or PMO to to create a steric blocking oligo Sugar mods will have a significant impact on binding and toxicity of the molecule Base mods to reduce immunogenicity (N1-methylpseudouridine) and end mods like 5’ caps to prevent degradation 3. Delivery System Development – Effective delivery is critical for success! Delivery mechanisms like LNPs and conjugation strategies like GalNAc and CPPs, etc Formulation of the drug to ensure minimal impact on delivery Optimizing delivery vehicle and ROA for the specific type of RNA and target tissue you are going after  Preclinical Candidate Development Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Preclinical Development 1. Rigorous Preclinical Studies In vitro studies to assess efficacy and mechanism of action Animal studies to evaluate pharmacokinetics, biodistribution and safety Toxicology studies to identify potential side-effects 2. Feasibility of Manufacturing and Scale-up Development of scalable synthesis processes Ensuring consistent quality and purity of large-scale batches Implementing appropriate storage and handling protocols 3. Preparing for IND Planning and execution of all IND-enabling studies GLP-level toxicology studies Proof-of-concept in non-human primates  Approval and Beyond Target Validation Lead Applicatio Target Target Hit-to- Preclinical Clinical & Screening Optimizati n& Marketing Identification Selection Lead Transition Trial Assessme on Approval nt Therapeutic Approval Process 1. Clinical Trial Phase 1 Phase 2 Phase 3 2. Application and Approval with the FDA, EMA, etc 3. Post-approval Marketing “Phase 4” marketing analysis Ongoing safety monitoring Patient support  Target of Interest Informs Platform Modifications Platform Where do we want to go? Sub-cellular target localization Development Where can we go? Specific organ systems, cell Platform Modifications types Receptor-mediated, cell specific How will we get there? Cargo Modifications Oligo for target type of interest Overall MOA Target Indication 10/28/24 15  Target of Interest Informs Platform Development DELIVERY METHOD BIODISTRIBUTION ADDED Where does parent compound go? Feasibility of synthesizing an siRNA or Intracellular localization ASO conjugated to delivery method Organ systems/tissues How will a non-neutral oligo impact Bioavailability with IV delivery? biodistribution and localization? Will formulation be sufficient? IN VITRO TOXICITY TARGET INDICATION How does treatment with compound + delivery system impact How is the disease modulated? inflammatory cytokines, Where is the target located? mitochondrial function, renal What dosing regimen is required? markers of stress, etc, Use primary RPTEC & HRCEpiC cells?  DEVELOPMENT OF FUTURE TARGETS Target of interest informs necessary peptide modifications NEXT TARGET INDICATION PLATFORM DEVELOPMENT Where do we want the drug to go? What delivery methods/conjugates are Where does the drug go? necessary to reach target location? INTRACELLULA COMPOUND TISSUES/CELL REQUIRED R BIOAVAILABILIT TYPES CARGO LOCALIZATION Y HOW WILL WE TARGET ROA HOW DO WE MEASURE DISEASE? SUCCESS? What type of oligo offers the best chance What key outputs are we focused on for successful target modulation? when deciding the right conjugate? PMO / ASO / siRNA  Core Oligo Therapeutic Development SAFETY/TOLERABILITY (CONJUGATES) DISTRIBUTION Evaluate inflammatory (OLIGONUCLEOTIDE) cytokines, mitochondrial RNAscope analysis to determine localization of conjugated function and creatinine output Distribution RPTEC and HRCEpiC compounds Safety Nuclear vs cytoplasmic (cortical) human in vitro Target dependent renal model Compound dose response to evaluate cell viability POTENCY & SELECTIVITY DURABILITY Potency & (OLIGO) Durability (CONJUGATES/OLIGO) Develop a method for analyzing Selectivity Stability ASO/siRNA engagement Intracellular depot Creation of a tool compound Clearance kinetics Can target either cytoplasmic or nuclear transcripts Will depend upon the target(s) INTELLECTUAL being considered IP PROPERTY RPTEC – Renal Proximal Tubule Epithelial Cells (MODELs/OLIGO) HRCEpiC – Human Renal Cortical Epithelial Patents/Publications Cells  Review available Bioinformati Compound development – ASO/siRNA Wet lab work data and cs literature SEQUEN SELECTI Determine Algorithm Primary/tiling Identify IC50 optimal screen for ON for potential CE determinatio oligo type sequence target sequence n for target selection engagement leads OPTIMIZATIO PLATFORM Identify Evaluate in Compare Identify potential vitro cellular potential conjugates N toxicity/poten uptake and conjugate for desired tial off-target localization leads oligo type effects Compare FEASIBILIT COMPOUN Evaluate Characterize passive conjugation / In vitro solubility and cellular complexation of D Y stability of uptake and POC conjugate + molecules localization oligo (HKG) IN VIVO POC In vivo POC  Preclinical Research Activities Required Assays Assay Development Needed Screening Compound screening / In vitro (cell culture) analysis Hit identification and secondary screening mRNA quantitation Secondary cell line evaluation/IC50 determination qPCR (ΔΔCt) – 96-well plate Test individual components in relevant cell lines separately Protein quantitation Evaluate for permeability and target engagement Western blot prep – 6-well plate Reporter cell lines when necessary ELISA prep - 96-well plate RNA-Seq in primary cells to rule out off-target Ex vivo tissue samples (mouse brain) perturbations mRNA quantitation Preclinical Biochemistry mRNA extraction for qPCR (ΔΔCt) Evaluate target protein and transcript reduction in ex Protein quantitation Western blot prep in Tris or RIPA buffer vivo tissues ELISA prep PK analysis of oligo in serum/plasma, brain tissue and siRNA quantitation peripheral organs using Hybridization ELISA or M/S Capture and detection probe generation is in-process Biomarker and immune marker analysis and assay Explore option of qPCR for siRNA quant with hairpin development primer Target Sequence Selection  Screening Workflow for Candidate Sequence Selection Primary Screening and Hit Secondary Screening / Lead Optimization In Identification Lead Candidate Vivo Target selection using algorithm Selection Acute tolerability Primary HTS for +/- target IC50 determination PK/PD engagement Secondary screening Potency Cell line analysis Protein analysis Duration of action Human cells Evaluation of cross-reactivity Mouse cells with NHP Good Sequence Selection Requires Correct Target Selection  Target Sequence Selection Assumes Access to Sequence Generator Target mRNA variant selection Create an alignment file of human mRNA variants in SnapGene/Geneious to identify any obvious discrepancies/differences; eliminate any redundant variants Start with National Center for Biotechnology Information (NCBI) to identify your target’s gene Different accession numbers indicate different molecule types NCBI Resourc es Adapted from: Chapter 18, The Reference Sequence (RefSeq) Database, The NCBI Handbook, McEntyre J, Ostell J, editors. Bethesda (MD): National Center for Biotechnology Information (US); 2002  Alpha-synuclein (SNCA) Alpha-synuclein (α-syn) is a 140 amino acid protein abundant and ubiquitously found in multiple brain regions such as the striatum, hippocampus, olfactory bulb, neocortex, thalamus and cerebellum It plays a key role in regulating neurotransmission and is involved in many functions, including neurotransmitter release, synaptic vesicle trafficking, membrane stabilization, dopamine release, & protein-protein interactions. Aggregation of a-synuclein is a major pathological driver of neurodegenerative diseases Dementia with Lewy bodies (DLB): Synuclein-related neuroinflammation. Lewy bodies contain high concentrations of nitrated a-synuclein, which is exacerbated by oxidative stress. Multiple system atrophy (MSA): Synuclein-related neuroinflammation Parkinson's disease: Gradual loss of nerve cells, causing symptoms like tremors, slowed movement, balance difficulties, & limb stiffness Organelle dysfunction (a, purple boxes), defects in inter-organelle contacts Nature Medicine (Nat Med) ISSN 1546- (b, blue box) and dysfunctional organelle dynamics (c, green box) have all 170X (online) ISSN 1078-8956 (print) been implicated in α-syn toxicity.  SNCA – Human Genomic Structure NCBI Gene ID 6622 NCBI Graphical Lege 9 transcripts annotated in NCBI nd NM_000345 selected based on exon inclusion; long isoform 6 exons, 3177 nt Additional 3’UTR encodes the full length 140 amino acid, 14.5 kDa protein heterogeneity  Target Sequence Selection Assumes Access to Sequence Generator Target mRNA variant selection Create an alignment file of human mRNA variants in SnapGene/Geneious to identify any obvious discrepancies/differences; eliminate any redundant variants Start with National Center for Biotechnology Information (NCBI) to identify your target’s gene Verify Ensembl transcripts of interest, particularly if anything is enriched in your target tissue Ensembl provides annotated genome information, primarily for vertebrates https://useast.ensembl.org/info/website/index.html Compare exon composition Decide whether your chosen accession number/variant for algorithm input should be more inclusive or more focused Determine whether any mutational variants can be eliminated from consideration (i.e. rare splice variants, etc) Run a literature search for most commonly occurring variants If no specific mutation has been identified as a target, use most encompassing sequence Any common (> 1%?) disease-associated SNPs that might be enriched in the target patient population? Plan to reflect in screening cell lines (check the Human Protein Atlas) Medical Genetics a NCBI Resourc nd Human Variatio es n  SNCA 3’UTR – Multiple Polyadenylation Sites At least 8 polyadenylation sites in 3’ UTR Literature suggests that the sites at 528-553 nt in the 3’UTR (1254 nt in the transcript) are the most prevalent in human tissues including brain Sotiriou, PMID 19540308 Marchese, PMID 29149290 Tseng, PMID 31338105 An expressed sequence tag (EST) is a short sub- sequence of a cDNA sequence. ESTs are a tool to help identify gene transcripts. They helped advance gene sequence identification in many cases. Sotiriou, PMID 19540308  Target Sequence Selection Assumes Access to Sequence Generator Target mRNA variant selection Cross-reactivity evaluation Transcript align Look for intraspecies cross-reactivity among human variants of interest ment Specifically look for XR with rodent (mouse and/or rat depending on the needs of in vivo toxicology) and NHP Run algorithm with the mouse sequence to look for hot spots for the purpose of an isotype control if no cross-reactive hits can be found Sequence selection for screening Identify top ~200 human sequences (assuming primary screen will be done in triplicate) Top 100 based on scoring from algorithm Top 100 when algorithm is sorted for cross-reactivity with mouse Run screen with the ~200 (maximum) sequences and proceed accordingly  Oligonucleotide Design “Algorithm” Experimental data Gene Target Functional Non-functional sequences sequences mRNA sequence Machine learning Algorithm 45 nt “walk” “Positional Weight Matrix” Get a score Homology between species: Homology within human: Indicating Sense and antisense Mouse Homology % GC Runs of bases Hits2gID likelihood of sequences Rat to miRNAs? Hits2Accessions success NHP Rank order the outputs Art Secondary structure predictions Science Filter and select desired number of ASOs/siRNAs Tedium Confirm that selected sequences don’t overlap with SNPs 30  Workflow for In Vitro Screening and Hit Identification Tile Around IC50 IC50 Conjugatio “Hot Determinat 50% target protein suppression at 6 months at a well-tolerated dose This dose is 8X lower than used in Nature Biotech publication 50  NHP Intrathecal-Lumbar Pilot PoC Study Objective: Demonstrate biodistribution and activity of oligo therapeutic dosed by IT-L ROA Endpoints Dose Level # of Route of Necropsy Time  48h Group Treatment (mg) Animals Administration points o siRNA quantitation (CNS regions, liver, kidney) 1 1 PBS N/A 48h  1, 2, 3 months o HTT mRNA and protein knockdown (CNS regions, liver, kidney) 2 1 Oligo - 48h 12.5 48h Slow bolus o siRNA quantitation (CNS regions, liver, injection through a kidney) 3 2 Oligo - 1m 12.5 pre-implanted 1 month o Inflammatory markers GFAP and Iba1 by intrathecal catheter, qRTPCR 2ml volume 4 2 Oligo - 2m 12.5 2 month o Histology (H&E, inflammatory markers GFAP, Iba1)  Plasma PK 5 2 Oligo - 3m 12.5 3 month o 15m, 30m,1h, 2h, 3h, 4h, 8h, 24h, 48h 51  Frontal Cortex HTT mRNA Huntingtin Protein Frontal Cortex Frontal Cortex 150 150 (Relative to Untreated) (Relative to Untreated) % Huntingtin Protein 125 125 %HTT Expression 100 100 75 75 50 50 25 25 0 0 1101 21032102 31013102 40014002 50015002 1101 21032102 31013102 40014002 50015002 kDa 460 268 238 Anti-Huntingtin Protein Antibody, a.a. 2146-2541, Millipore clone HU-2E8  Motor Cortex HTT mRNA Huntingtin Protein Motor Cortex Motor Cortex 150 150 (Relative to Untreated) (Relative to Untreated) % Huntingtin Protein 125 125 %HTT Expression 100 100 75 75 50 50 25 25 0 0 1101 21032102 31013102 40014002 50015002 1101 21032102 31013102 40014002 50015002 kDa 460 Hunting 268 tin 238 350kDa b-actin 44kDa Anti-Huntingtin Protein Antibody, a.a. 2146-2541, Millipore clone HU-2E8  Hippocampus HTT mRNA Huntingtin Protein Hippocampus Hippocampus 150 (Relative to Untreated) (Relative to Untreated) 150 % Huntingtin Protein 125 %HTT Expression 125 100 100 75 75 50 50 25 25 0 0 1101 21032102 31013102 40014002 50015002 1101 21032102 31013102 40014002 50015002 Hunting tin 350kDa b-actin 44kDa Anti-Huntingtin Protein Antibody, a.a. 2146-2541, Millipore clone HU-2E8  Spleen Liver Kidney 150 150 150 (Relative to Untreated) 125 (Relative to Untreated) (Relative to Untreated) 125 125 %HTT Expression %HTT Expression %HTT Expression 100 100 100 75 75 75 50 50 50 25 25 25 0 0 0 1101 21032102 31013102 40014002 50015002 1101 21032102 31013102 40014002 50015002 1101 21032102 31013102 40014002 50015002 Spinal Cord Cervical Spinal Cord Spinal Cord 150 Thoracic Lumbar 150 150 (Relative to Untreated) 125 %HTT Expression (Relative to Untreated) (Relative to Untreated) 125 125 100 %HTT Expression %HTT Expression 100 100 75 75 75 50 50 50 25 25 25 0 1101 21032102 31013102 40014002 50015002 0 0 1101 21032102 31013102 40014002 50015002 1101 21032102 31013102 40014002 50015002  Drug Development is Risky, Expensive…and Evolving Large companies are trending away from early discovery research efforts. Drug Discovery Preclinical Clinical Trials FDA Review Post-Approval Discovery In Vitro lead ID Phase 1 Phase 2 Phase 3 Provide sufficient Establish large- Pre- Target ID and validation In Vivo potency, evidence for scale Compound Screening PK/PD & MTD 20-100 100-500 1000+ FDA/EMA to verify manufacturing volunteer volunteer volunteer Hit Identification Efficacy in disease s s s safety and efficacy & models Perform Phase IV 3-6 Years 1-2 Years 6-7 Years Total 0.5 – 2 years studies for long- term effectiveness  Drug Development is Risky, Expensive…and Evolving Large companies are trending away from early discovery research efforts. Drug Discovery Preclinical Clinical Trials FDA Review Post-Approval Discovery In Vitro lead ID Phase 1 Phase 2 Phase 3 Provide sufficient Establish large- Pre- Target ID and validation In Vivo potency, evidence for scale Compound Screening PK/PD & MTD 20-100 100-500 1000+ FDA/EMA to verify manufacturing volunteer volunteer volunteer Hit Identification Efficacy in disease s s s safety and efficacy & models Perform Phase IV 3-6 Years 1-2 Years 6-7 Years Total 0.5 – 2 years studies for long- term effectiveness Universities and research institutes Larger, more established companies have the have the expertise to address the resources and expertise to effectively drive the later fundamental research questions stages of drug development. needed for early discovery. They are more aware of market needs, They tend to introduce new ideas & manufacturing and product development, drive innovation more readily than commercialization and cost optimization. large pharma R&D divisions  Drug Development is Risky, Expensive…and Evolving Large companies are trending away from early discovery research efforts. The Art of Outsourcing Contract Research Organizations (CROs) Contract Manufacturing Organizations (CMO) Drug Discovery Preclinical Contract Development & Manufacturing Discovery In Vitro lead ID Organizations (CDMOs) Pre- Target ID and validation In Vivo potency, Compound Screening PK/PD & MTD Hit Identification Efficacy in disease models 3-6 Years 1-2 Years Profits for contract organizations increased 13X between 1995 - 2005  The Best Drug Development is Collaborative There are many ways to drive early discovery innovation Academic-Industry Collaboration In-licensing the idea or technology to an established company Ongoing support for university or research consortium Novartis (NIBR) and Merck – good examples of large pharma that invests in university research. Sponsored Research Agreement A company funds a specific research project in a lab, which gives them an opportunity to negotiate a license to intellectual property (IP) that arises from the funded research Non-profit funding support Models like the Cystic Fibrosis Foundation provide sizable grants for drug discovery, with a significant ROI for the CFF when the work is successful Public-Private Partnership (PPP) Usually involves smaller companies that have more resources for the early stage/discovery side of things partnering with large companies that have later-stage resources.  Path to a Start-up Early discovery work has spawned hundreds of new companies backed by Venture Capital Funds In 2018, emerging biopharma companies represented 84% of early-phase research From 2019 to 2021, VC funding in biotech soared to $35 billion, signaling a momentum that shows no signs of slowing.  General Trends Driving Research Funding 1. Greater shift toward platform technologies Innovative delivery methods Predictive algorithms Novel chemical synthesis approach Gene editing tools Technology that is scalable and target agnostic 2. Machine Learning and AI-enabled drug design ML and AI are accelerating drug development through MD simulations, target identification, rational drug design, oligo sequence predicting and more Between 2019 – 2022, AI and ML-enabled drug discovery raised over $9 billion in VC funding 3. Gene and Oligonucleotide Therapies Translation inhibition – ASOs and siRNAs exon skipping – splice-modulating or steric blocking oligos increased or corrected protein expression – circular RNA and self-amplifying RNA Immunomodulators RNA editing - ADAR RNA-mediated transcriptome regulation Clinical Candidate ASO Examples Additional Information  IONIS/ROCHE’S TOMINERSEN (HTTRX / RG6042) 20 nucleotide 2’-O-(2-methoxyethyl) ASO. Binds mRNA, triggering Rnase H1-mediated degradation of the target mRNA The sequence of tominersen is (5′ to 3′) - ctocoaogTAACATTGACaococoac - in which capital letters represent 2′-deoxyribose nucleosides, and small letters 2′-(2-methoxyethyl) ribose nucleosides. Nucleoside linkages that are represented with a subscripted “o” are phosphodiester, and all others are phosphorothioate. 2’-MOE modification: more nuclease resistant, with lower toxicity, and slightly increased hybridization affinities Tabrizi et al 2019  BIIB080 (MAPTRX) Second-generation 2′-O-(2-methoxyethyl) ASO complementary to a nucleotide sequence in the human MAPT pre-mRNA transcript. The sequence of BIIB080 is: (5′ to 3′) ccogttTTCTTACCacocct Capital letters represent 2′-deoxyribose nucleosides, and small letters 2′-(2-methoxyethyl)ribose nucleosides. Nucleoside linkages represented with a subscript o are phosphodiester, and all others are phosphorothioate. Letters represent adenine, 5-methylcytosine, guanine and thymine nucleobases. Hybridization of BIIB080 to the cognate pre-mRNA via Watson and Crick base pairing results in ribonuclease H1-mediated degradation of the MAPT pre-mRNA, thus selectively preventing production of the tau protein61. Dose selection was guided by a preclinical model in mouse and monkey relating dose level to reduction in MAPT mRNA (model described by Tabrizi et al.). 2’-MOE modification: more nuclease resistant, with lower toxicity, and slightly increased hybridization affinities Mummery et al 2023  ASO-001933 ROCHE MAPT ASO LNA-modified ASO targeting MAPT 3’ UTR Targets exon 14, sequence 5’- gtaaaagtgaatttggaaat -3’, Accession ID: NM_001123066.4 or RefSeqGen record NG_007398.1 The sequence of ASO-001933 is: (5′ to 3′) AtTTCcaaattcactTTtAC Capital letters represent Locked Nucleic Acids, and small letters represent DNA. Nucleoside linkages are complete phosphorothioate backbones. Phosphorothioate Linker Easton et al 2022 LNA Monomer DNA Monomer Targeting huntingtin expression in patients with Huntington’s disease Tabrizi SJ, Leavitt BR, Landwehrmeyer GB, et al. N Engl J Med 2019;380:2307-16. DOI: 10.1056/NEJMoa1900907 66  Tabrizi et al, NEJM 2019 Bolus IT administration every 4 weeks X 4 doses Clinical end points Primary endpoint – safety Secondary end point – HTTRx PK in CSF Exploratory end points – HTTRx PK in plasma, concentration of mHTT and NFL protein in CSF Of 46 patients dosed, 34 received HTTRx Dose level ascending from 10 to 120mg 12 given placebo Predose (trough) concentrations of HTTRx in CSF showed dose dependence up to doses of 60mgs HTTRx treatment resulted in a dose-dependent reduction in the concentration of mutant huntingtin in CSF (-10% change in placebo; and −20%, −25%, −28%,−42%, and −38% in the HTTRx 10-mg, 30-mg, 60- mg, 90-mg, and 120-mg dose groups, respectively). 68  HTTRx IONIS – HTTRx (ISIS 443139) – 20 nucleotide 2’-O-(2-methoxyethyl) ASO. Binds mRNA, triggering Rnase H1-mediated degradation of the target mRNA The sequence of HTT is (5′ to 3′) - ctocoaogTAACATTGACaococoac Rx in which capital letters represent 2′-deoxyribose nucleosides, and small letters 2′-(2-methoxyethyl) ribose nucleosides. Nucleoside linkages that are represented with a subscripted “o” are phosphodiester, and all others are phosphorothioate. Letters “a” and “A” represent adenine, “c” and “C” 5-methylcytosine, “g” and “G” guanine, and “t” and “T” thymine nucleobases. 69  Patient Selection and Drug Characteristics Patients range between 25 and 65 years of age Had early Huntington’s disease defined as 36 or more CAG repeats in HTT and clinical stage 1 disease (defined as little to no fx impairment) Patients received either placebo or HTTRx given at one of five doses - (10, 30, 60, 90 or 120mgs); 4 bolus IT inj. 70  Statistical Analysis The treatment differences and 95% confidence intervals for changes in the mutant HTT concentration in CSF were Hodges–Lehmann estimations that were based on the Wilcoxon rank-sum test or were obtained with the use of analysis of variance, depending on the normality of the data. Relationships between reductions in the concentration of mutant HTT in CSF and clinical outcomes were explored in a post hoc analysis with the use of Spearman’s correlation coefficient, and the 95% confidence interval of the correlation coefficient was based on Fisher’s z transformation. Because of the exploratory nature of this trial, adjustments for multiplicity of testing were not used. Interpretation of HTTRx effects on mutant HTT in tissue was based on the extent of reduction of the mutant HTT concentration in CSF and a linked pharmacokinetic and pharmacodynamic clearance model that was based on data collected in human mutant HTT–transgenic mice and nonhuman primates (see the Supplementary Appendix). 71  Conc. of mHTT in CSF (fmol/liter) HTTRx Characterist Placebo All 10 mg 30 mg 60 mg 90 mg 120 mg ic (N = 12) (N = 34) (N = 3) (N = 6) (N = 6) (N = 9) (N = 10) Baseline 109±43 110±46 144±50 120±45 117±30 105±65 96±35 % change from -19.9 -25.0 -27.5 -42.4 -37.7 pre-dose to last 9.8 (31.4) (12.7) (13.1) (15.1) (13.0) (21.2) measurement Percent change from pre-dose Day 1 to the last available 28-day post-dose timepoint (latter of Day 85 and Day 113) 72  Exploratory Endpoints Secondary end point – HTTRx PK in CSF HTT was measurable in the CSF of most patients who Rx received doses of 30 mg or more. Trough concentrations increased with increasing dose, from below the limit of quantification at the 10-mg dose through the 60-mg dose, with a plateau in the concentration in CSF beyond the 60-mg dose (Fig. 2A). No accumulation of HTT in CSF was observed over Rx time. PKPD of ASO was reported as conc of HTT in CSF Rx (ng/mL) Median peak plasma concentration of HTT were Rx reached within 4 hrs post bolus IT admin and declined to