Overview
Loka's Drug Targets Identification, Clinical Proof & Patent Screening program is designed to streamline the identification and prioritization of potential drug targets using agentic workflows. The program also allows companies to perform robust data mining of clinical and patent databases to validade discoveries.
The three-phase program begins by collaboratively defining discovery objectives with stakeholders, followed by identifying relevant data sources—such as public databases or internal knowledge graphs—that span various data modalities (e.g., genomics, proteomics, clinical data).
The implementation phase deploys an agentic framework for querying relevant data sources, pre-processing and retrieving outputs in an appropriately structured format, and applying evaluation mechanisms to prioritize targets identified from these sources.
The final validation phase ensures the reliability of our discoveries through rigorous benchmarking and optimization, culminating in a Proof of Concept report that aids strategic decision-making.
AWS Tools Used
- Bedrock
- DynamoDB
- RDS
- Fargate
- Route52
- Lambda
- EC2
- ECR
- S3
- Secret Manager
- Amazon Cognito
Highlights
- Comprehensive Multi-Modal Insights: Integrates genomics, proteomics, clinical data, and text-based information to offer a 360° view of potential targets, enriched by AI and NLP to reveal hidden patterns in scientific literature.
- Strategic Target Prioritization: Features a customizable scoring framework that tailors prioritization to disease-specific criteria and evaluates intellectual property data to assess novelty and commercial viability.
- AI-Enhanced Discovery Pipeline: Harnesses advanced algorithms and natural language processing to surface non-obvious connections, accelerating and sharpening the drug discovery process.
Details
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To schedule a rapid 30-minute consultation email jorge.sampaio@loka.comÂ