APIS Target Triage (ATTTM)

APIS Target Triage (ATTTM) is an innovative service that has been meticulously packaged as a product with a clear mission: to validate drug or biomarker targets effectively. By combining advanced AI tools (LLMs, ML models) with automated workflows, it empowers researchers to:

High-confidence targets

Find high-confidence targets faster

Reduce research costs

Reduce research costs

Experiment success rate

Improve experimental success rates

Path from discovery to clinical studies

Accelerate the path from discovery to preclinical studies

ATT Features

  • Comprehensive review and extraction of targets and related information from:

    • scientific publications

    • databases,

    • data & knowledge repositories

    Rapid extraction and analysis from millions of scientific articles and datasets using LLMs.

  • Evaluates potential targets using various biological and clinical parameters. Assesses target relevance through:

    • Disease Association

    • Expression & Pathway Analysis

    • Safety Inspection

    • Validation of Existing Studies, Cohorts & Drug Experiments

    • Provides interactive tools to visualise target data.

    • Allows users to filter, prioritise, and explore targets based on customisable parameters, improving decision-making and discovery workflows.

    • Assesses the potential binding interactions between targets and drug candidates.

    • Helps in ranking targets based on their likelihood to engage with specific molecules or therapeutic compounds.

    • Utilises advanced machine learning approaches to predict binding affinities, analyse molecular docking results, and identify potential off-target effects, improving accuracy and reducing false positives

    • Generates comprehensive, data-driven reports and summaries.

    • Offers insights and actionable recommendations to guide research, development, and decision-making processes.

    • Uses LLMs (Large Language Models) to generate concise summaries, highlight key insights, and assist in interactive result exploration.

Accelerated Target Discovery and Validation

Automated Data Mining: Rapid extraction and analysis from millions of scientific articles and datasets using LLMs

Faster Target Prioritization: Efficient filtering of >2.4 million candidates through automated scoring and ranking mechanisms

Quick Iterations: Reduces time from data collection to actionable insights

Benefits of ATT

Data-Driven Decision Making

Interactive Visualization & Smart Reports: Provides clear summaries and actionable recommendations using LLMs

Protein Target Profiling: Evaluates key protein attributes such as tissue specificity, RNA expression levels (TPM), and blood concentration

Machine Learning Predictions: Uses models for binding affinity predictions and supporting informed go/no-go decisions

Cost-Effective Research Operations

Reduces Wet-Lab Failures: Focuses only on high-confidence targets before experimental validation

Minimises Trial-and-Error: Computational modeling identifies potential failures early

Optimised Resource Allocation: Saves time and budget by prioritising the most promising candidates for laboratory testing

Scalable and Reproducible Process

End-to-End Automation: Reduces manual effort and human error in the discovery pipeline

Consistent Output: Standardises validation steps, ensuring reproducibility across projects

Customisable Workflow: Adjusts filtering criteria based on customer-specific inputs (e.g., disease area, mechanism of action)

How does ATT work?

ATT aims to accelerate the selection process and provide confidence in level of evidence of disease target association, prior to commencing wet-work

LLMs

Fast literature analysis, better insights.

Reduces manual effort in literature reviews and ensures no critical information is missed.

Performs natural language queries to answer complex research questions.

Technological Backbone

AI/ML Models

Accurate predictions and fewer false positives.

Assesses molecular docking results to predict interactions between drugs and targets.

Cloud Computing

Scalable, high-speed data processing.

Scales dynamically to handle large workloads.

Stores and retrieves large datasets efficiently.

Multi-Omics Integration

Holistic view of target relevance.

Combines data from genomics, transcriptomics, proteomics, and clinical studies.

Provides a comprehensive biological profile for each target.

Ordering Information

ProductCatalogue NumberPrice
APIS Target Triage (ATT)02601Available upon request

To order the APIS Target Triage (ATT) or to learn more about how we can elevate your bioinformatics capabilities, please contact us below.