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PozeSCAF Inc.

AI-powered preclinical drug discovery combining generative AI, computational chemistry, and synthesis.

Preclinical drug discovery CRO combining proprietary generative AI platform AxDrug with computational chemistry, synthetic chemistry, and in vitro biology to accelerate hit discovery and lead optimization for biotech and pharma clients.

Phases

Services

Modalities

About this organization

Overview

PozeSCAF Inc. (formerly Immunocure Inc., founded 2019) is a preclinical drug discovery CRO that integrates its proprietary AxDrug AI platform with computational chemistry, medicinal chemistry synthesis, and in vitro biology services. The company serves biotech and pharmaceutical clients seeking to accelerate small-molecule drug discovery from target validation through lead optimization.

Core Capabilities

Computational Chemistry & AI Services:

  • Target validation and druggability prediction
  • Hit identification via virtual screening of 20+ billion compound databases using generative AI and consensus docking models
  • Hit-to-lead generation with scaffold hopping, enumeration, and binding affinity prediction based on quantum mechanics
  • Lead optimization using multi-parameter AI protocols, molecular dynamics simulations, and free energy perturbation (FEP) studies
  • ADME and toxicity prediction models
  • Off-target prediction and polypharmacology assessment
  • Custom AI model generation (data curation, preparation, and integration)

Synthesis & Chemistry:

  • Small-molecule synthesis (milligrams to kilograms)
  • Custom peptide synthesis
  • PROTAC design and synthesis
  • Molecular glue design
  • Medicinal chemistry optimization and structure-activity relationship (SAR) insights

In Vitro Biology (New):

  • Biochemical assay services
  • Cell-based assay services
  • Advanced in vitro models for drug discovery

Differentiation

PozeSCAF emphasizes seamless integration between AI-driven design and in-house synthesis, eliminating handoffs and delays. The company leverages a 20+ billion compound database generated through generative AI and commercial libraries, advanced machine learning and deep learning frameworks, and molecular dynamics with enhanced protocols. The team combines computational expertise with experienced medicinal and synthetic chemists to reduce R&D costs and timelines for clients.

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