Transparent data science
for precision medicine
Modern medicine faces formidable data analysis challenges. The increasing complexity of medical data, with numerous variables for each patient, like genomic data, imaging data and biomarkers, demands new approaches. Disease interactions and patient heterogeneity further complicate the landscape, as no two patients with the same disease respond identically to treatment.
There is an urgent, unmet need for innovation. Many analytical tools currently used in medicine date back to the 1970s. To achieve true personalized, data-driven precision medicine, we must develop and implement cutting-edge mathematical and statistical methodologies. Now is the time for action and advancement.
Saddle Point's Solutions
spsSIGNATURE pipeline
Data Features
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Datasets with numerous covariates per patient and a corresponding clinical outcome
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Clinical outcome variables could be e.g., time to event, ordinal classes, or treatment response.
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Covariates could be e.g., clinical variables, genetic data, imaging data.
Results Obtained
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Reliable multivariate risk and outcome signatures, with replica-based overfitting correction.
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Insights into covariate-outcome and response-covariate-outcome relationships
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Ideal for complex clinical and biomedical analyses
Utilizing Results
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Identify key predictors for developing targeted treatments, in spite of small sample sizes.
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Understand complex data relationships to guide future research
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Stratify patient cohorts by risk profiles to enhance personalized medicine
Beunders, R., et al. (2023). Assessing GFR with proenkephalin. Kidney International Reports, 8(11), 2345–2355. https://doi.org/10.1016/j.ekir.2023.08.006
Why partner with Saddle Point Science Europe?
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Cutting-Edge Mathematical and Statistical Techniques:
Stay ahead with the most advanced tools in the industry. -
Customized Biomedical Modeling:
Tailored approaches that fit your specific needs. -
Addressing Latent Heterogeneity and Informative Censoring:
Tackle complex data challenges head-on. -
Algorithms to Reduce Overfitting in Small or Complex Data Sets:
Ensure reliable and reproducible data insights. -
On-Demand Data Analysis, Consultancy, and Software Licenses:
Get expert support and advanced software whenever you need it.
Dr. Paul Barber,
Kings' College London
"We now use Saddle Point Signature for all survival and risk prediction analyses and we find it robustly produces multivariate models that generalise to other data sets better than other methods."
Dr. Christel Häggström,
Umeå University
"I really enjoyed working with team and the SaddlePoint-Mosaics software. I have gained a deeper understanding of the drawbacks of conventional survival analysis and found that Mosaics' innovative approaches have been very useful and applied in different clinical settings, particularly when investigating personalized medicine.”
