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AI-powered bioinformatics solution for infectious disease diagnostics


Infectious disease diagnostics platform / 12-month engagement 

Drug response prediction platform development case study

About the project

Our client is a biotech company that focuses on developing solutions for infectious disease diagnostics to improve the way antimicrobial-resistant infections are diagnosed , prevented or treated. The platform combines genomic analysis with artificial intelligence to detect outbreaks in clinical settings and to provide accurate and rapid predictions of drug susceptibility for bacterial infections helping healthcare providers, clinicians, and microbiologists to make more informed antimicrobial treatment decisions.

Product features

Genomic sequencing

The platform uses whole-genome sequencing data to analyze bacterial and fungal pathogens allowing healthcare providers to identify the specific strain of the pathogen and determine its drug susceptibility profile.

Epidemiological surveillance

This feature allows healthcare professionals to track the prevalence and spread of antibiotic-resistant bacteria which can help to identify outbreaks and prevent the spread of resistant strains. The platform can also be used to monitor changes in resistance patterns over time, which can inform public health strategies and interventions.

AI & ML algorithms

The solution uses machine learning algorithms that have been trained on large datasets of genomic data to analyze the genomic data and predict the susceptibility of bacteria to different antibiotics. This helps to identify which antimicrobial drugs are most likely to be effective against a particular strain.

Data management and reporting

The platform provides a detailed chemical data reporting that includes information on the genetic markers associated with drug resistance, as well as recommendations for the most effective treatment options. 

Efficiency and cost savings

Using subscription-based models, cost optimization is achieved through predictability and scalability. Fully automated bioinformatics solutions save time and allow to process extensive outbreak datasets within hours.

AWS infrastructure

To enable labs globally, the client developed a cloud-based data interpretation system. AWS Amplify and AWS Batch were used to setup frontend and backend functionality, connectivity and dataflow for processing and interpreting data in a streamlined and automated manner. A CLIA-compliant workflow and cloud-based system automates pathogen identification, AMR characterization, and genotyping-assisted outbreak analysis.


Software Engineering


  • Frontend: Vue, Amplify, TypeScript, Vuetify

  • Backend: NodeJS, Python REST API, AWS Lambda 

  • Data: DynamoDB, AWS RDS, Alembic, Cognito, Sqlalchemy

  • Cloud: AWS, Docker

Product Team

 1 engineer

Drug response prediction platform_AMR annotation and profiling dashboard view

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Let's talk 

Interested to learn more on how Radency can bring value to your business? Drop us a line! 

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