Digital Ether Computing LLC
Digital Ether Computing (DEC) is a Florida–based company that develops adaptive AI for drug discovery, functional genomics, and defense health applications. DEC's proprietary platforms (Liquid Adaptive AI, LC-JT-VAE generative molecular design, and the Dynamicasome genomic atlas) identify hidden (cryptic) binding pockets and design novel therapeutics against targets once considered undruggable, from computational prediction through partner-led synthesis and validation. DEC's technology is described in peer-reviewed publications and protected by four provisional patents, and the company currently performs under a Florida Department of Health Cancer Innovation Fund contract. DEC is SAM.gov registered (CAGE 131L8, UEI R8TDWGCLKUH1) and U.S./Canada Joint Certification Program (JCP) certified for access to DoD export-controlled technical data, and welcomes prime and subcontractor teaming on MTEC and federally funded research programs.
Industries
Nr. of Employees
small (1-50)
Digital Ether Computing LLC
Products
Drug Discovery-Design-Optimization Platform (D3OP)
AI-driven drug discovery platform combining DEC's proprietary LC-JT-VAE generative model with cryptic-pocket discovery to design novel, synthesis-aware drug candidates. Integrates molecular docking, molecular dynamics, and ADMET prediction, with partner synthesis and in vitro validation, to move from target to testable compound quickly.
Liquid Adaptive AI (LAAI) for Defense and Health Applications
Continuously learning AI that adapts to sparse and shifting data at the edge. Fuses wearable, physiological, and environmental sensor data into real-time decision support for predictive health monitoring, prolonged field care, and human performance, with uncertainty quantification and operation in communications-denied environments.
Nexomorph therapeutics platform
A new class of AI-designed therapeutic compounds that target hidden (cryptic) binding pockets to reshape protein-complex dynamics, opening "undruggable" targets in oncology, neurodegeneration, and other high-need diseases. Designed with DEC's LAAI and LC-JT-VAE platforms.
Dynamicasome: Functional Genomics & Pathogenicity Prediction
AI platform for genetic variant scoring, pathogenicity prediction, and biomarker discovery, supporting target identification and precision-medicine research.
Translational Validation (In Silico to In Vitro)
End-to-end validation support that carries AI-designed candidates from computational prediction into laboratory testing, including assay design, ADMET modeling, organoid profiling, and coordination of partner synthesis and CRO studies.
Drug Discovery-Design-Optimization Platform (D3OP)
AI-driven drug discovery platform combining DEC's proprietary LC-JT-VAE generative model with cryptic-pocket discovery to design novel, synthesis-aware drug candidates. Integrates molecular docking, molecular dynamics, and ADMET prediction, with partner synthesis and in vitro validation, to move from target to testable compound quickly.
Liquid Adaptive AI (LAAI) for Defense and Health Applications
Continuously learning AI that adapts to sparse and shifting data at the edge. Fuses wearable, physiological, and environmental sensor data into real-time decision support for predictive health monitoring, prolonged field care, and human performance, with uncertainty quantification and operation in communications-denied environments.
Nexomorph therapeutics platform
A new class of AI-designed therapeutic compounds that target hidden (cryptic) binding pockets to reshape protein-complex dynamics, opening "undruggable" targets in oncology, neurodegeneration, and other high-need diseases. Designed with DEC's LAAI and LC-JT-VAE platforms.
Dynamicasome: Functional Genomics & Pathogenicity Prediction
AI platform for genetic variant scoring, pathogenicity prediction, and biomarker discovery, supporting target identification and precision-medicine research.
Translational Validation (In Silico to In Vitro)
End-to-end validation support that carries AI-designed candidates from computational prediction into laboratory testing, including assay design, ADMET modeling, organoid profiling, and coordination of partner synthesis and CRO studies.
Services
Licensing of DEC's proprietary AI and computational drug-discovery platforms, including LAAI, LC-JT-VAE, and Dynamicasome, to pharmaceutical, biotech, and research partners.
Collaborative research and platform co-development with industry, academic, and government partners in AI-enabled drug discovery, translational research, and adaptive AI for health and defense.
Expert guidance on AI-enabled drug-discovery workflows, computational biology, platform integration, and secure AI system design for research and government programs.
Development of adaptive AI solutions tailored to partner requirements in drug discovery, biomedical research, and mission-critical applications.
Rapid prototyping and demonstration of adaptive AI solutions for medical and defense use cases, from proof of concept through prototype validation.
Target-to-candidate discovery for partners: cryptic-pocket identification, virtual screening, generative molecular design, hit-to-lead optimization, and ADMET prediction, delivering prioritized, synthesis-ready compounds.
Licensing of DEC's proprietary AI and computational drug-discovery platforms, including LAAI, LC-JT-VAE, and Dynamicasome, to pharmaceutical, biotech, and research partners.
Collaborative research and platform co-development with industry, academic, and government partners in AI-enabled drug discovery, translational research, and adaptive AI for health and defense.
Expert guidance on AI-enabled drug-discovery workflows, computational biology, platform integration, and secure AI system design for research and government programs.
Development of adaptive AI solutions tailored to partner requirements in drug discovery, biomedical research, and mission-critical applications.
Rapid prototyping and demonstration of adaptive AI solutions for medical and defense use cases, from proof of concept through prototype validation.
Target-to-candidate discovery for partners: cryptic-pocket identification, virtual screening, generative molecular design, hit-to-lead optimization, and ADMET prediction, delivering prioritized, synthesis-ready compounds.
Expertise Areas
- AI-driven drug discovery and development
- Adaptive artificial intelligence architectures
- Computational biology
- Pharmacokinetics and ADMET prediction
Key Technologies
- Deep learning
- Molecular docking
- Structure-based drug design
- Ligand-based drug design
Key People
News & Updates
Published in Biomolecules, DEC's Ligase-Conditioned Junction Tree Variational Autoencoder (LC-JT-VAE) generates novel, synthesizable molecular glues that target Alzheimer's-associated amyloid beta-42 for degradation, demonstrating AI-driven design against difficult neurological targets.
Dr. Thomas Caulfield co-authored this NIH-funded Science Advances study applying structure-based computational design to achieve selective inhibition of a serine protease, work that underpins DEC's cryptic-pocket drug discovery approach.
Published in the journal AI, this paper presents the mathematical framework for Liquid Adaptive AI (LAAI), a continuously self-improving AI architecture built on adaptive knowledge graphs, runtime self-optimization, and multi-agent learning. LAAI is the foundation of DEC's adaptive AI platforms.
DEC's Dynamicasome combines molecular dynamics simulation of every possible missense variant in a gene with AI to predict pathogenicity, published in Nature Portfolio's Communications Biology. It provides a scalable approach to variant interpretation and precision-medicine target discovery.
DEC is now JCP certified by the Defense Logistics Agency, authorizing access to DoD export-controlled unclassified technical data in support of defense research and prototype programs.
DEC brings AI-driven drug discovery, functional genomics, and adaptive AI for military health to the MTEC community and is seeking prime and subcontractor teaming on current and upcoming solicitations. Contact Ryan King, COO, at ryan@digitalethercomputing.com.
Published in Biomolecules, DEC's Ligase-Conditioned Junction Tree Variational Autoencoder (LC-JT-VAE) generates novel, synthesizable molecular glues that target Alzheimer's-associated amyloid beta-42 for degradation, demonstrating AI-driven design against difficult neurological targets.
Dr. Thomas Caulfield co-authored this NIH-funded Science Advances study applying structure-based computational design to achieve selective inhibition of a serine protease, work that underpins DEC's cryptic-pocket drug discovery approach.
Published in the journal AI, this paper presents the mathematical framework for Liquid Adaptive AI (LAAI), a continuously self-improving AI architecture built on adaptive knowledge graphs, runtime self-optimization, and multi-agent learning. LAAI is the foundation of DEC's adaptive AI platforms.
DEC's Dynamicasome combines molecular dynamics simulation of every possible missense variant in a gene with AI to predict pathogenicity, published in Nature Portfolio's Communications Biology. It provides a scalable approach to variant interpretation and precision-medicine target discovery.
DEC is now JCP certified by the Defense Logistics Agency, authorizing access to DoD export-controlled unclassified technical data in support of defense research and prototype programs.
DEC brings AI-driven drug discovery, functional genomics, and adaptive AI for military health to the MTEC community and is seeking prime and subcontractor teaming on current and upcoming solicitations. Contact Ryan King, COO, at ryan@digitalethercomputing.com.