From Drug Discovery to
Drug Possibility

Pending AI is pushing the boundaries of traditional drug discovery, targeting new diseases with speed afforded by artificial intelligence and accuracy inherent in quantum mechanics.

From Drug Discovery to Drug Possibility

From Drug Discovery to
Drug Possibility

Pending AI seamlessly integrates scalable quantum mechanics and artificial intelligence to create a platform capable of unlocking new drug discovery possibilities.

Pending AI is pushing the boundaries of traditional drug discovery, targeting new diseases with speed afforded by artificial intelligence and accuracy inherent in quantum mechanics.

Three Scientific Pillars, One Unified Platform

Our platform starts with a bioinformatics-driven approach to identify the most promising disease targets amenable to quantum mechanical improvements, providing Pending AI with a truly differentiated approach to drug discovery that is unavailable to others.

Quantum-Based Structural Biology

Quantum mechanical calculations combined with experimental datasets from either x-ray crystallography or cryo-electron microscopy generates higher-quality crystal structures for interesting disease targets, as confirmed by crystallographic metrics and physically correct non-covalent interactions. High-performance computing clusters and bespoke divide-and-conquer techniques enables quantum-level accuracy for traditionally intractable protein structures.

Quantum-Based Structural Biology

Quantum mechanical calculations to x-ray crystallography and cryo-electron microscope datasets (electron density maps) generates higher-quality crystal structures of interesting disease targets, as confirmed by crystallographic benchmark metrics (e.g. clashscores) and mapping of non-covalent interactions. Artificial intelligence model training on these calculations maintains quantum-level accuracy, all while using a thousand-fold less resources (cost and time).

Quantum-Based Structural Biology

Artificial Intelligence-Guided Drug Libraries

Our ultra-high-throughput generative artificial intelligence capabilities build trillion-scale drug libraries, exploring pharmaceutical space at an unprecedented level. These molecules are benchmarked against gold-standard pharmacological criterion, including but not limited to: drug-likeness, diversity, novelty, synthetic accessibility and absorption, distribution, metabolism, and excretion (ADME) properties.

Artificial Intelligence-Guided Drug Libraries

Drug Profile Optimization

Top candidate molecules undergo iterative optimization through similarity searching, reinforcement and transfer learning, as well as quantum mechanical interaction modelling. This feedback loop enables fine-tuning of drug properties such as binding affinity and target inhibition efficacy.

Drug Profile Optimization

85%

Human proteome considered undruggable by traditional method.

1000x

Reduction in cost/time of calculations, using a hybrid data-driven and physics-informed platform.

1 Trillion+

Novel drug candidates searchable (similarity distance) within our virtual library.

Trusted by our partners

Built for Scale. Tuned for Precision.

Pending AI’s platform is rethinking how computational drug discovery should be performed – using physics-informed intelligence and scale-first architecture, the engine is pushing into uncharted therapeutic territory.