Genomic Risk Prediction of Complex Diseases
Seamlessly in the Cloud
Allelica allows the computation of Polygenic Risk Score based on Thousands or Millions of genetic variants. Upload genotype data and Allelica performs QC, imputation, risk modelling and results visualisation.

For Clinical Genetics Labs

Offer your customers the latest PRS for clinical grade risk prediction. Upload your SNP array or NGS data and our software performs PRS analysis in a cloud architecture that is fully automated, GDPR-HIPAA compliant and certified as a Medical Device. Differentiate your clinic from the crowd, embrace data-driven healthcare and generate a new source of revenue.

For Researchers

You’re just two clicks away from your next PRS paper. Use our platform to perform the entire PRS pipeline, QC and imputation, without writing a single line of code. Run and compare the performance of the most cited PRS methods, such as LD-Pred and Clumping and Thresholding. Focus only on what really matters for your research project without the hassle of informatics.

For Pharmas

Stratify participants of your clinical trials according to their genomic diversity. Use our software to identify individuals at with different underlying risk so that you can target your trial population saving your company money and time while having a better trial outcome. A simple genotyping array unlocks precious information on your cohort, invaluable to follow up decision-making in the modern area of drug development.

Trusted Translational Genomics

Allelica has built the first cloud platform that allows you to perform Polygenic Risk Score (PRS) analysis without writing a single line of code. The cloud architecture is a secure and trusted environment that has been certified as a Medical Device and is GDPR and HIPAA complaint. We work with leading clinical genetics labs, pharmaceutical companies and research institutes to improve health care prevention for a large number of complex diseases. The cloud platform accepts as input genotyping array and NGS data, performs genomic prediction analysis with published PRS or with your newly developed PRS.

Validation and testing on the UKBiobank is performed with just two clicks.

"With this agreement, Merck confirms its strong commitment in advancing Science and Technology in the therapeutic area of cardiovascular disorders"

Antonio Messina, Merck General Manager

Development of data-driven cardiovascular disease prevention tools

Allelica is partnering with Merck, a leading global healthcare and life sciences company, to develop a suite of tools designed to help cardiovascular disease patients. Whilst cardiovascular diseases are the leading cause of mortality worldwide, there is a growing number of patients who survive initial cardiovascular events and require secondary prevention measures. Allelica's work with Merck is aimed at improving the patient journey by exploring how technology can be used to identify patients who may have unknowingly suffered heart failure and those at high risk of a secondary cardiovascular event.

The Latest from Allelica

Why you should choose Allelica

Made by scientists

Allelica software and algorithms have been developed thanks to a collaboration between scientists who carried out resarches at Oxford University and the University of Rome “La Sapienza”.

Software as a Service
Use our SaaS for easy and fast data analysis and report. Use our pipelines to safely scale your genomic anaysis.
Privacy and Security
We give absolute priority to the privacy of your data. The genetic data are encoded through a secure protocol and encrypted in a single tenant node.

What we do


Perform Risk Prediction Analysis

Use the Allelica in Cloud software to perform Polygenic Risk Score Analysis in a fast and safe way.


Preventive Healthcare

Provide the latest clinical grade Polygenic Risk Score for complex diseases published on high impact factor journals.

Appeared on


Allelica founders carried out research at the University of


Funded by

The European project for innovation in Health

The Seed Fund

The Italian Pree-Seed grant to support Research Spin-Off