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

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.

Four 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 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).

If your research could benefit from higher-accuracy modelling for crystal structures and intermolecular interactions, whether for drug discovery campaigns or investigating catalytic mechanisms, you should contact us for more information.

Multilanguage

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).

If your research could benefit from higher-accuracy modelling for crystal structures and intermolecular interactions, whether for drug discovery campaigns or investigating catalytic mechanisms, you should contact us for more information.

Multilanguage

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).

If your research could benefit from higher-accuracy modelling for crystal structures and intermolecular interactions, whether for drug discovery campaigns or investigating catalytic mechanisms, you should contact us for more information.

Multilanguage

Artificial Intelligence-Guided Drug Libraries

Our ultra-high-throughput generative artificial intelligence capabilities build trillion-scale virtual 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.

If your research is struggling to identify novel drug-like compounds for your target of interest, and/or you wish to explore new areas of chemical space beyond what is available in the public domain (or those expanded with known synthesis steps), you should contact us for more information.

Multilanguage

Artificial Intelligence-Guided Drug Libraries

Our ultra-high-throughput generative artificial intelligence capabilities build trillion-scale virtual 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.

If your research is struggling to identify novel drug-like compounds for your target of interest, and/or you wish to explore new areas of chemical space beyond what is available in the public domain (or those expanded with known synthesis steps), you should contact us for more information.

Multilanguage

Synthetic Accessibility Assessment

Our artificial intelligence-driven synthesis prediction (retrosynthesis) capability, trained on tens of millions of chemical reactions acquired through several dataset partnerships, is one of the world’s most powerful synthesis prediction platforms. Trusted by over 100 organizations, ranging from multi-national pharmaceutical companies to academic institutions, our models have been engineered to unlock value for medicinal/process chemists (detailed assessment of query compounds), and computational chemists (ultra-high-throughput synthetic accessibility assessment of virtual libraries).

If your research would benefit from synthesis pathway discovery and optimization, or pre-screening large-scale virtual chemical libraries for synthetic accessibility, you should contact us for more information.

Multilanguage

Synthetic Accessibility Assessment

Our artificial intelligence-driven synthesis prediction (retrosynthesis) capability, trained on tens of millions of chemical reactions acquired through several dataset partnerships, is one of the world’s most powerful synthesis prediction platforms. Trusted by over 100 organizations, ranging from multi-national pharmaceutical companies to academic institutions, our models have been engineered to unlock value for medicinal/process chemists (detailed assessment of query compounds), and computational chemists (ultra-high-throughput synthetic accessibility assessment of virtual libraries).

If your research would benefit from synthesis pathway discovery and optimization, or pre-screening large-scale virtual chemical libraries for synthetic accessibility, you should contact us for more information.

Multilanguage

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.

If your research is currently blocked in its structure-activity relationship optimization cycle and would benefit from accounting for unique parameters (e.g. quantum mechanics-informed structural properties), you should contact us for more information.

Multilanguage

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.

If your research is currently blocked in its structure-activity relationship optimization cycle and would benefit from accounting for unique parameters (e.g. quantum mechanics-informed structural properties), you should contact us for more information.

Multilanguage

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.

Quantum mechanical refinement of target proteins

Trillion-scale virtual screening libraries tailored to maximise discovery

End-to-end integration from target selection to lead optimization

Capable of identifying both first-in-class and best-in-class candidates

Cloud-native drug discovery platform

Our artificial intelligence and quantum mechanical workloads run in public or private clouds, and can be run on high-performance computing clusters.

Data security is our top priority

ISO27001 certified and SOC2 audited highlights our commitment to cybersecurity best practices.