Trusted Partners combines expert judgment, mechanistic validation and artificial intelligence

Our expert drug selection committee, led by Jack Scannell, picks treatments most likely to go smoothly through regulatory processes, have market fit and succeed in trials.

They evaluate data from our synthetic clinical trial platform. The platform evaluates each potential treatment in an independent mechanistic model. It predicts efficacy and side effects.

Candidate treatments are discovered using our unique wide data algorithms, which decipher the complex interplay between genes and thereby identify connections between drug targets and diseases that would otherwise remain unseen.

The tools our experts rely on solve long-standing problems in genomics-based drug development

Genomic data is not big data, the kind that most current machine learning algorithms, especially Deep Learning, rely on. It is the exact opposite, which makes it difficult to identify treatment candidates with a high sensitivity.

Big Data

Learning simple patterns from a huge number of examples.

Wide Data

Learning complex patterns from a small number of examples. This is the challenge with genomic data.

Solving complexity

We use knowledge graphs not for hypothesis generation, but to reduce the complexity of the hypothesis space. Then algorithms based on predictive power (which is not strongly affected by sample size, unlike p-values) discern meaningful interactions from the noise.

Synthetic Trials with millions of patients

We use human data driven hypothesis testing in an independent data set, which provides a mechanistic disease model and eliminates false positives. By focusing on disease causing biomarkers as endpoints (rather than the disease itself), we are able to use our entire biobank of 2 million genomes and medical records.

Proof of concept and in-vitro data: COVID19

In the first year of the pandemic, through our AI we were the first to discover an association between a combination of variants on the CDK6 gene and critical illness from COVID-19.

Our Synthetic Clinical Trial then revealed the disease mechanism and potential treatment: CDK6 drives count of neutrophils, a type of white blood cell, which through a process called NETosis cause cytokine storm, the auto-immune reaction found in critically ill COVID-19 patients.

Scientists at the University of Bristol have confirmed this connection through in-vitro testing.

We have a growing pipeline of clinical developments identified by our technology