Ai-MicroCloud^® for Life Sciences

Zeblok Computational's 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 HPC orchestration, optimization for heterogeneous architectures, and production 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:

1. Within mission-critical processes
2. Into your proprietary research platform, financial modeling and valuation methodology
3. To make more informed decisions
4. To differentiate and personalize product offerings
5. Bring to life your most challenging data-driven strategies

How Ai/ML can help Life Sciences, Pharmaceuticals, BioTech Companies

There are multiple areas ripe for data-driven initiatives within the categories of revenue growth, cost reduction, operational improvement, risk management and compliance.

New Drug Discovery

Developers need a high-performance computing platform to run simulations to understand how proteins fold and how proteins bind to other proteins – actions, mechanisms and binding affinities – to enable design of drugs for high-affinity binding to proteins. Ai/ML modeling using 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.