Ai-MicroCloud™ for Life Sciences

Drug Discovery,  Therapies for Rare Diseases, Clinical Trials,

Disease Identification & Diagnosis

Study des.JPG



Zeblok Computational’s accelerated Ai-MicroCloud™ for is uniquely suited to AI/ML development in Biotech/Pharma/Life Sciences markets, providing everything your team needs, including high-performance computing (HPC) orchestration to develop, train, deploy and manage AI applications, transforming AI projects into real-world business solutions. Zeblok’s Ai-MicroCloud™ is an enterprise-ready turnkey AI Platform-as-a-Service, including curated algorithms, accelerated data lake, seamless high-performance computing (HPC) orchestration and runtime environment, that helps data scientists and data engineers develop, customize, and deploy AI projects quickly, generate new insights and enhance decision-making capabilities.


Zeblok can help you ingest and evaluate the value of data more efficiently, to integrate AI:

  • Within mission-critical processes

  • Into your proprietary research platform for drug discovery, clinical trial patient identification, disease identification & diagnosis and finding therapies for rare diseases

  • To make more informed decisions

  • To differentiate and personalize product offerings


Bring to life your most challenging data-driven strategies.   

How AI/ML Can Help Life Science, Pharma, Biotech Companies:

There are multiple areas ripe for data-driven initiatives within the categories of drug discovery, therapies for rare diseases, identifying patients for clinical trials and product research..

New Drug Discovery: 

High Performance computing platform is needed to run simulations to understand how proteins fold and how proteins bind to proteins – actions, mechanisms and binding affinities – to enable design of drugs for high-affinity binding to proteins. AI/ML modeling, that uses physics-based methods to examine motions, forces and free energies within biological mechanisms help accelerate new drug discovery.

Therapies for Rare Diseases:

Insufficient knowledge of the disease pathophysiology and natural history combined with the insufficiency of validated outcomes and disease-specific biomarkers delays establishing new therapies. AI/ML models such as genomic analysis by means of next generation sequencing (NGS) and other “omics technologies” has boosted Rare Disease diagnosis and molecular understanding. 

Identify Patients for Clinical Trials:

Traditional methods of identifying patients for clinical trials has many short coming resulting in delays and increasing cost. AI/ML models can help target patients with rare conditions needed for a specific drug clinical trial based on public and private healthcare data.

Diagnosis and Disease Identification:

The biggest challenge in medicine is correct diagnosis and identification of diseases. AI/ML models help medical professionals from initial identification of disease to predicting mortality rates and tracking treatment effectiveness in subsequent patient visits. 

Take a 21 Day Trial


Full implementation of an Explainable AI algorithm on a virtualized notebook, in concert with Zeblok's GPU-powered data lake in our


Use Cases


Ai-MicroCloud™ for Life Sciences

AI Data Workshop

The Journey from Data to Insights 

5 day, Hands-on Session