Using our precisionlife platform, we have analysed a range of complex diseases identifying novel targets for conditions with high, unmet clinical need.
Our TargetBank contains over 100,000 significant disease signatures and a portfolio of in silico validated targets.
Our internal focus is on neurological, cardiometabolic, oncology and respiratory indications, areas of significant unmet need and we have a number of products accelerating through our pipeline.
We are actively developing early-stage partner-ready assets with full biological data packages that document their clinical and commercial disease relevance.
The analysis of large population datasets is a very scalable, automated process resulting in a comprehensive biological data package containing:
- Novel targets with testable mechanism of action hypothesis and appropriate tissue expression profile
- Drug-like tool chemistry and screened repurposing opportunities
- Patient stratification biomarkers
- Information on assays, models, IP and clinical trials landscape
A number of the most promising targets will be taken into in vitro/vivo screening for validation of impact on phenotype.
precisionlife finds innovative targets and leads using multi-omic analysis. We have developed a pipeline of targets, candidates and clinical decision making tools for diseases with high unmet need, including those below.
Click on the images to find out more about the science behind our success stories.
Around 35 genes have previously been associated with ALS, but there are no effective therapeutic options for this devastating disease. We set out to identify all disease related genes to be able to prioritize and select new disease targets for drug repurposing and/or novel drug development.
We found 33 novel genes that were strongly associated with ALS and have selected 10 targets of significant interest for drug discovery screening. Within just 3 months of analyzing the ALS genotypes of more than 20,000 people, we are identifying potential new drugs for this debilitating disease. In a traditional drug discovery process, this usually takes 3-5 years.
precisionlife performed a study to identify combinatorial genomic signatures associated with Alzheimer’s disease (AD), which can be used for better stratification of patients into sub-groups and the development of more effective and personalized therapeutic interventions.
We identified almost 35,000 SNP networks strongly associated with AD. Clustering of the SNPs by the patients in which they occur enabled us to build a detailed architecture and stratification of the disease population. We identified 8 clusters of networks representing 8 patient sub-groups that differ in their disease associated genes and pathways.
Asthma is a broad diagnostic label given to a diverse set of conditions that exhibit similar clinical features – chronic airway inflammation, reversible airflow obstruction, wheezing, shortness of breath, chest tightness etc. Most asthma patients continue to be treated using a one size-fits-all approach.
We analyzed the differences between Th2-mediated and non-Th2 asthma at a genetic level. We constructed a cohort of 7,500 Th2-mediated and 15,000 non-Th2 asthmatics with 75,000 age and sex matched controls. precisionlife identified clear differences in the SNPs, genes and pathways associated with Th2 and non-Th2 disease.
precisionlife performed a study on BRCA2 positive patients (contrasting those affected by breast cancer at < 40 years old) and “healthy” individuals (not affected by age of 40 years old).
We found 3,045 disease signatures and 750 novel disease associated SNPs, as well as:
- Novel drug targets: genes not previously associated with breast or other cancers
- Drug repurposing candidates: compounds showing strong potential for drug repurposing
- Key genetic modifiers: BRCA2 positive cases whose breast cancer risk is normal
- Patient stratification biomarkers