Decoding
Decoding
Cancer
Cancer
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Decoding
Cancer
Nexomic uses frontier AI to decode
the hidden biology driving treatment response, resistance, and disease evolution.
What we do
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
Our Approach
Our Approach
Our Approach
Our Approach
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
DeepOmic®
DeepOmic®
DeepOmic®
The Discovery Engine
The Discovery Engine
The Discovery Engine
A Multi-Omic foundation model purpose
built to decode the biology of cancer
A Multi-Omic foundation model purpose
built to decode the biology of cancer
A Multi-Omic foundation model purpose
built to decode the biology of cancer
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
8000D
High-dimensional biological embeddings that capture complex multi-omic disease signals.
High-dimensional biological embeddings that capture complex multi-omic disease signals.
High-dimensional biological embeddings that capture complex multi-omic disease signals.
Embeddings
Embeddings
Embeddings
1000s
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validation
Validation
Validation
One
A unified AI representation of disease biology across omics, patients, and cancer types.
A unified AI representation of disease biology across omics, patients, and cancer types.
A unified AI representation of disease biology across omics, patients, and cancer types.
Representation
Representation
Representation
Human
Therapeutic Model
Human
Therapeutic Model
01
Learned from humans
Trained on real patient tumours and what happened to them. Not cell lines. Not mice.
02
Sees where the drug acts
Locates the drug’s effect inside tumour biology: which programmes it hits, and in which tumours.
03
Predicts response before the trial
Ranks every tumour by predicted benefit, so the trial enrols the ones most likely to respond.
04
Explains resistance
Names the biology behind non-response, and what to combine with it to overcome it.
05
Runs across every cancer type
Finds where the drug works beyond its first indication, including cancers no one tried.
06
Becomes a test
Its signature distils into a patient-selection test, and on to a companion diagnostic.
Solutions
DECODE
DECODE
DECODE
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
View Project
View Project
De-risking Clinical Development
DEEP360
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
DEEP360
View Project
View Project
Patient Response Prediction
Resources
Browse our library of trusted resources,
expert insights, and informative articles
whenever you need them.
Browse our library of trusted resources,
expert insights, and informative articles
whenever you need them.
Contact Us
Get in touch with us to discuss your project and start building something extraordinary.
Contact Us
Get in touch with us to discuss your project and start building something extraordinary.
Decoding
Cancer
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Human
Therapeutic Model
01
Learned from humans
Trained on real patient tumours and what happened to them. Not cell lines. Not mice.
02
Sees where the drug acts
Locates the drug’s effect inside tumour biology: which programmes it hits, and in which tumours.
03
Predicts response before the trial
Ranks every tumour by predicted benefit, so the trial enrols the ones most likely to respond.
04
Explains resistance
Names the biology behind non-response, and what to combine with it to overcome it.
05
Runs across every cancer type
Finds where the drug works beyond its first indication, including cancers no one tried.
06
Becomes a test
Its signature distils into a patient-selection test, and on to a companion diagnostic.
DeepOmic®
The Discovery Engine
A Multi-Omic foundation model purpose
built to decode the biology of cancer
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
8000D
High-dimensional biological embeddings that capture complex multi-omic disease signals.
Embeddings
1000s
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validation
One
A unified AI representation of disease biology across omics, patients, and cancer types.
Representation
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
1M+
Harmonized features per patient
100M+
Molecular features modeled
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Data Foundation
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
1M+
Harmonized features per patient
100M+
Molecular features modeled
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Greenway, Block C,
112-114 St Stephen's Green,
Dublin 2, D02 TD28
Dublin, Ireland
Decoding
Decoding
Cancer
Cancer
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Decoding
Cancer
Nexomic uses frontier AI to decode
the hidden biology driving treatment response, resistance, and disease evolution.
What we do
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
Our Approach
Our Approach
Our Approach
Our Approach
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
DeepOmic®
DeepOmic®
DeepOmic®
The Discovery Engine
The Discovery Engine
The Discovery Engine
A Multi-Omic foundation model purpose
built to decode the biology of cancer
A Multi-Omic foundation model purpose
built to decode the biology of cancer
A Multi-Omic foundation model purpose
built to decode the biology of cancer
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
8000D
High-dimensional biological embeddings that capture complex multi-omic disease signals.
High-dimensional biological embeddings that capture complex multi-omic disease signals.
High-dimensional biological embeddings that capture complex multi-omic disease signals.
Embeddings
Embeddings
Embeddings
1000s
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validation
Validation
Validation
One
A unified AI representation of disease biology across omics, patients, and cancer types.
A unified AI representation of disease biology across omics, patients, and cancer types.
A unified AI representation of disease biology across omics, patients, and cancer types.
Representation
Representation
Representation
Human
Therapeutic Model
Human
Therapeutic Model
01
Learned from humans
Trained on real patient tumours and what happened to them. Not cell lines. Not mice.
02
Sees where the drug acts
Locates the drug’s effect inside tumour biology: which programmes it hits, and in which tumours.
03
Predicts response before the trial
Ranks every tumour by predicted benefit, so the trial enrols the ones most likely to respond.
04
Explains resistance
Names the biology behind non-response, and what to combine with it to overcome it.
05
Runs across every cancer type
Finds where the drug works beyond its first indication, including cancers no one tried.
06
Becomes a test
Its signature distils into a patient-selection test, and on to a companion diagnostic.
Solutions
DECODE
DECODE
DECODE
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
View Project
View Project
De-risking Clinical Development
DEEP360
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
DEEP360
View Project
View Project
Patient Response Prediction
Resources
Browse our library of trusted resources,
expert insights, and informative articles
whenever you need them.
Browse our library of trusted resources,
expert insights, and informative articles
whenever you need them.
Contact Us
Get in touch with us to discuss your project and start building something extraordinary.
Contact Us
Get in touch with us to discuss your project and start building something extraordinary.
Decoding
Cancer
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Human
Therapeutic Model
01
Learned from humans
Trained on real patient tumours and what happened to them. Not cell lines. Not mice.
02
Sees where the drug acts
Locates the drug’s effect inside tumour biology: which programmes it hits, and in which tumours.
03
Predicts response before the trial
Ranks every tumour by predicted benefit, so the trial enrols the ones most likely to respond.
04
Explains resistance
Names the biology behind non-response, and what to combine with it to overcome it.
05
Runs across every cancer type
Finds where the drug works beyond its first indication, including cancers no one tried.
06
Becomes a test
Its signature distils into a patient-selection test, and on to a companion diagnostic.
DeepOmic®
The Discovery Engine
A Multi-Omic foundation model purpose
built to decode the biology of cancer
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
8000D
High-dimensional biological embeddings that capture complex multi-omic disease signals.
Embeddings
1000s
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validation
One
A unified AI representation of disease biology across omics, patients, and cancer types.
Representation
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
1M+
Harmonized features per patient
100M+
Molecular features modeled
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Data Foundation
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
1M+
Harmonized features per patient
100M+
Molecular features modeled
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Greenway, Block C,
112-114 St Stephen's Green,
Dublin 2, D02 TD28
Dublin, Ireland
Decoding
Decoding
Cancer
Cancer
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Decoding
Cancer
Nexomic uses frontier AI to decode
the hidden biology driving treatment response, resistance, and disease evolution.
What we do
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
At Nexomic, we have built a large-scale patient multiomic data foundation that reflects the diversity and complexity of tumour biology.
Enhanced by our proprietary computational deep profiling approaches and state-of-the-art, tumour-agnostic AI foundation model, it powers solutions that advance precision oncology from discovery to patient care
Our Approach
Our Approach
Our Approach
Our Approach
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
DeepOmic®
DeepOmic®
DeepOmic®
The Discovery Engine
The Discovery Engine
The Discovery Engine
A Multi-Omic foundation model purpose
built to decode the biology of cancer
A Multi-Omic foundation model purpose
built to decode the biology of cancer
A Multi-Omic foundation model purpose
built to decode the biology of cancer
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
8000D
High-dimensional biological embeddings that capture complex multi-omic disease signals.
High-dimensional biological embeddings that capture complex multi-omic disease signals.
High-dimensional biological embeddings that capture complex multi-omic disease signals.
Embeddings
Embeddings
Embeddings
1000s
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validation
Validation
Validation
One
A unified AI representation of disease biology across omics, patients, and cancer types.
A unified AI representation of disease biology across omics, patients, and cancer types.
A unified AI representation of disease biology across omics, patients, and cancer types.
Representation
Representation
Representation
Human
Therapeutic Model
Human
Therapeutic Model
01
Learned from humans
Trained on real patient tumours and what happened to them. Not cell lines. Not mice.
02
Sees where the drug acts
Locates the drug’s effect inside tumour biology: which programmes it hits, and in which tumours.
03
Predicts response before the trial
Ranks every tumour by predicted benefit, so the trial enrols the ones most likely to respond.
04
Explains resistance
Names the biology behind non-response, and what to combine with it to overcome it.
05
Runs across every cancer type
Finds where the drug works beyond its first indication, including cancers no one tried.
06
Becomes a test
Its signature distils into a patient-selection test, and on to a companion diagnostic.
Solutions
DECODE
DECODE
DECODE
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
Decoding Latent Biology to Understand Heterogeneity and Resistance for Better Clinical Development Design
View Project
View Project
De-risking Clinical Development
DEEP360
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
Running Large Scale AI-driven Simulations to Reveal Accurate Patient Response Predictions
DEEP360
View Project
View Project
Patient Response Prediction
Resources
Browse our library of trusted resources,
expert insights, and informative articles
whenever you need them.
Browse our library of trusted resources,
expert insights, and informative articles
whenever you need them.
Contact Us
Get in touch with us to discuss your project and start building something extraordinary.
Contact Us
Get in touch with us to discuss your project and start building something extraordinary.
Decoding
Cancer
Nexomic uses frontier AI to decode the hidden biology driving treatment response, resistance, and disease evolution.
Human
Therapeutic Model
01
Learned from humans
Trained on real patient tumours and what happened to them. Not cell lines. Not mice.
02
Sees where the drug acts
Locates the drug’s effect inside tumour biology: which programmes it hits, and in which tumours.
03
Predicts response before the trial
Ranks every tumour by predicted benefit, so the trial enrols the ones most likely to respond.
04
Explains resistance
Names the biology behind non-response, and what to combine with it to overcome it.
05
Runs across every cancer type
Finds where the drug works beyond its first indication, including cancers no one tried.
06
Becomes a test
Its signature distils into a patient-selection test, and on to a companion diagnostic.
DeepOmic®
The Discovery Engine
A Multi-Omic foundation model purpose
built to decode the biology of cancer
4B
Large scale self-supervised pretraining to be used for downstream tasks applications.
Parameters
8000D
High-dimensional biological embeddings that capture complex multi-omic disease signals.
Embeddings
1000s
Validated across diverse patient datasets to support robust and clinically relevant insights.
Validation
One
A unified AI representation of disease biology across omics, patients, and cancer types.
Representation
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
1M+
Harmonized features per patient
100M+
Molecular features modeled
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Data Foundation
The Data Foundation
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
6 layers
Genomics, transcriptomics, epigenomics, immunomics, proteomics and metabolomics, with clinically linked outcomes
Every tumour comes with the treatment given and how the patient responded
40+ cancer types
Common and rare, learned together rather than one cancer at a time
40+ cancer types
Common and rare, learned together rather than one cancer at a time
30+ countries
Data from around the globe, including rare subtypes
30+ countries
Data from around the globe, including rare subtypes
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
3 sources
Nexomic’s own proprietary cohorts, unique and rare cases sequenced everyday and public datasets harmonized into one
1M+
Harmonized features per patient
1M+
Harmonized features per patient
100M+
Molecular features modeled
100M+
Molecular features modeled
1 model
DeepOmic, one multi-omic foundation model learning from all of it
1 model
DeepOmic, one multi-omic foundation model learning from all of it
The Greenway, Block C,
112-114 St Stephen's Green,
Dublin 2, D02 TD28
Dublin, Ireland