The Promise of AI/ML for Drug Discovery

The costs of drug discovery continue to rise, with estimates exceeding $2 Billion and 10-12
years in research and development. AI/ML in Drug Discovery holds a key to the promise of
reducing these costs and timelines

Reduce costs
Reduce timelines

The Challenge

1

Data Scarcity Slows the Adoption of AI in Small Molecule Drug Discovery and Novel Biology Exploration due to

  • iconCostly data generation
  • iconComplexities of data sharing
  • iconSlow and expensive ML model validation cycles
2

Because of this data scarcity, exploration of novel biology lags behind technological capability

  • iconPharma: High-risk of pursuing novel protein targets is not justified without target validation
  • iconAcademia: High cost of data prevents ID of tool molecules to validate targets
  • iconResult: redundancy of proteins targets pursued
  • iconMissed opportunity to impact disease in 90+% of under-explored proteome

The Proteome is Underexplored

graph
  • Biology studied, no tools
  • Unknown function
  • Current Drugs
  • Tool Compounds

Source: Oprea et al., 2018
https://www.nature.com/articles/nrd.2018.14

Citadel Discovery was launched in 2021 with the purpose of democratizing access to the data and technology that will drive the future of biological exploration, drug discovery and health technologies.

Citadel Drives Disruption

Democratizing Predictive Drug Discovery

Problem
Data Scarcity

Disruption:

Low-cost access to data & data generating technologies (e.g. DEL)

Invest in novel technologies for cost-accessible data generation

Problem
Slow AI-Model Validation Cycle

Disruption:

Build an industry enabling rapid chemical synthesis and testing capability for model validation

Enable drug discovery model validation at pace of high-tech

Problem
Data Sharing

Disruption:

Build data sharing & commercialization platform

Generate proteome-wide data set for drug discovery, diagnostics and precision medicine

Problem
Underfunding of Industry Enabling Capabilities

Disruption:

Enable new and Underutilized technologies to drive down costs

Align funding sources with public benefit

Citadel Discovery Timeline

2022

  • icon50-100 Data Sets
  • iconSharing Platform
  • iconEnable DEL/DEL-ML
  • iconRapid DMT POC
  • iconOutreach:
    Industry, Foundation, Academic

2023

  • icon250-500 Data Sets
  • iconInternalize DEL
  • iconScale-Up Rapid DMTA
  • iconRe-Investment into Novel Biology Exploration

2024

  • icon500-1000 Data Sets
  • iconEnable industry for rapid DMTA
  • iconExpand to Clinical & Diagnostics Data
  • iconEnable 2-5 Drug-Discovery Projects

Discover with Citadel

Enabling Data Access

  • Access to data, models and results, discounted for academics
  • Data commercialization and sharing platform
  • Expanding lists of targets
  • Accelerates DEL-ML target exploration

Enabling Data Generation

  • Custom model generation
  • Rapid chemical validation services
  • Enable DEL capability in-house to biotechs and institutions

Enabling Opportunity

  • De-risk biotech efforts at concept phase
  • Frontline visibility into novel biology
  • Lead AI/ML with access to unprecedented proteome-scale data
  • Investment in data and data-generation technology for health and drug discovery