Maze's Compass Platform - A data fabric for drug discovery and development

1. CONFIDENTIAL
Maze’s Compass Platform
A data fabric for drug discovery and
development
October 26, 2022

2. Overview
• Maze Therapeutics and the Compass Platform
• Informatics framework for target discovery and validation
• Sightline Data architecture
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3. Mazehasbuiltapowerfulenginefordrugdiscovery
SinceitsfoundinginOctober2018
Pipeline programs established
7 wholly-owned, 2partnered
First program completing phase I: target to clinic in 3 years
Second program expected to enter clinic in 2H2023
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2018 2019 2020 2021 2022
MZE-001
IND
171 Oyster Point
MZE-001 Phase 1
10+
Additional identified targets, genetic insights
in research validation
Key therapeutic areas of focus in renal, cardiology, neurology, metabolic diseases
Scientists and top talent brought into Maze
Housed in state of the art 65,000+ sq ft lab & office HQ in
South San Francisco
120+

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5. Translate genetic insights into medicines
MAZE COMPASSTM PLATFORM
V A R I A N T T O F U N C T I O N F U N C T I O N T O T H E R A P Y
V A R I A N T D I S C O V E R Y
Mazeappliesaunifiedapproachto
May 2022 | 5

6. V A R I A N T D I S C O V E R Y V A R I A N T T O F U N C T I O N F U N C T I O N T O T H E R A P Y
Clinical
Data
Clinical Phenotype
Proteinuria
Hypertension
eGFR
Potassium Level
Serum Creatine
Level (sCR)
Fluid Overload
Rapidly advance from genetic signal to drug program
Our Compass Platform is designed to
GWAS
Analysis
Genetic Variants
CATGACTG
CATGCCTG
…hundreds more
…differentiated,
interesting
GWAS Hits
Mapping to Genes
Variant Location
Exon
Intron
Enhancer
Promoter
Single Cell
Analysis
Cell Type
Endothelium
Proximal Tubule
Podocyte
Loop of Henle
Distal Convoluted Tubule
Lymphocyte
Macrophage
Functionalization
Multimodal Profiling
Functional Assays
Localization
RNAseq
Proteomics
Protein Levels
In Silico Modeling
Translation
Drug Discovery to Mimic Variant
Function
CryoEM Screen
15 Billion
Compound DEL
Traditional HTS
in parallel
Novel Assays
EX.
CKD
4+ Y E A R S F O R P C S K 9 T O E N T E R D R U G D I S C O V E R Y
1.5M+
Individuals
200+
Loci
Thousands
of variants
Millions of data points
and petabytes (1015) of data
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Prioritized Drug Project
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7. The Compass Data Map supports evolving knowledge
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V A R I A N T T O F U N C T I O N F U N C T I O N T O T H E R A P Y
V A R I A N T D I S C O V E R Y
External Data (Pay-to-Play and Open Access) Experiment Data Drug Discovery Data
ELN
Data Lake: Summary Stats (50+ billion records) Analyses (100+ results)
Analysis Results
Project Compounds (16k+ w/data)
pheno
variant
disease
gwas
target
concept allelic
series
joint
analysis qpcr
screen crispr
analysis
md
analysis
weekly
assay
business
intel
exper.
design
program
results
protein
struct
compound
clinic
Assay Data

8. SIGHTLINE is Maze’s new portal into our Data Map
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V A R I A N T T O F U N C T I O N F U N C T I O N T O T H E R A P Y
V A R I A N T D I S C O V E R Y
Data Lake: Summary Stats (50+ billion records) Analyses (100+ results) Project Compounds (16k+ w/data)
pheno
variant
disease
gwas
target
concept allelic
series
joint
analysis qpcr
screen crispr
analysis
md
analysis
weekly
assay
business
intel
exper.
design
program
results
protein
struct
compound
clinic
SIGHTLINE

9. Sightline Data Architecture
• What is a data lake, lake house, warehouse?
‒ Structured, Semi-structured, and unstructured data in object storage
• Leveraging cloud-native data formats formats (e.g., parquet)
‒ Breaks up data into smaller chunks with compression
‒ A variety of compute engines enable parallel processing
‒ Storage is cheap, compute can be serverless (e.g., Athena)
• Lifting data out of the lake
‒ Open graph data formats enable linking data lake tables
‒ Statistical relationships within/between tables are modeled using a graph
‒ Provides a conceptual model for understanding how questions are answered
• Data-centric appli
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10. Sightline presents a global overview of Maze’s R&D portfolio
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11. Insights from multiple sources increase confidence in a target concept
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Effect
Size
CommoneQTLvariant
Rareprotein- altering variants
Wildtype / referenceprotein
Protein function
<redacted> in CKD
Population and disease datasets

12. Sightline’s MVP release focuses on allelic series
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13. Sightline’s MVP release focuses on allelic series
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14. More modules are in progress
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15. The Maze Data Architecture and Sightline Teams
Data Science:
‒ Nolan Nichols (Lead Platform Architect)
‒ Juan Arrivillaga
‒ Matt Brauer
‒ Michel Dumontier, Maastricht University, advisor
‒ Developers
• Datavisyn: Dominic Girardi, Vanessa Stoiber, Daniela Moitzi, Zach Cutler
• Keitaro: Blagoja Stojkosk
Human Genetics:
‒ Sahar Mozaffari (genetics project lead)
‒ Robert Graham (project visionary)
‒ Karol Estrada
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