We’ll find that needle – but only if it’s there
Target Analytics helps answer mission-critical questions in life sciences, pharmaceutical, financial, and all other industries faced with ever-larger data haystacks and ever more elusive needles. Our products use unique patented methodology to improve precision and reliability of causal inference, the analysis of cause and effect relationships in data.
TargetDiscovery
For each potential causal factor in a given list, TargetDiscovery performs a separate targeted maximum likelihood estimate of the effect on the outcome, controlling for confounding variables.
In addition, it provides a reliable measure of the signal-to-noise ratio in the dataset. For example, consider a study to evaluate the effect of genetic markers on progression free survival in cancer patients. (more)
TargetImpact
TargetImpact performs automated targeted maximum likelihood estimate of the causal effect of time-point treatment interventions in longitudinal observational as well as randomized studies.
TargetImpact builds on the framework of counterfactuals and the corresponding in-depth statistical theory and methodology for marginal structural models. (more)
Target Analytics Advantage
Building on a rich academic research foundation involving top institutions and scientists in the areas of semi-parametric models and causality, including the work of the company's founder, Dr. Mark van der Laan at UC Berkeley, the Target Analytics product line utilizes novel, proprietary methodology of causal inference and targeted maximum likelihood analysis to improve precision and reliability over best existing tools. Target Analytics super-learning algorithms automatically arrive at the best combination of input models based on the cross-validation within each particular dataset, eliminating the need for high levels of domain, statistical, and programming expertise. (more)
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This software is very impressive.
Professor Dr. A. Chambaz
University of Paris, France
News
Resources
- Mark van der Laan
- Targeted Maximum Likelihood (TMLE)
- TMLE and Biomarker Discovery 1
- TMLE and Biomarker Discovery 2
- TMLE and Clinical Trials
- Targeted Adaptive Designs
- Other Research Papers
- Causal Inference: Judea Pearl
- Causal Inference: James Robins
- Causal Inference: Donald Rubin
- FDA: Critical Path Initiative
- FDA: Presentation on Causality
- FDA: Safety Analysis
- FDA: Drug Safety
- 60 Minutes: Safety Analysis
- Adaptive Seamless Design
- Adaptive Sample Size
- Adaptive Trials
- Confirmatory Trials
- Salford Systems
