InsightRX Data Science

Combining expertise in pharmacology, statistics, and software engineering

Our team designs and develops the numerical backends (APIs) for individual treatment optimization for InsightRX Nova and the calculation of clinical and pharmacological metrics for InsightRX Apollo.

Our goal is to advance the science of precision dosing through research and development of new models, software tools, and statistical methods.

Experts in Research and Development

Explore the latest from our Data Science team:

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Scientific Publications

Manuscripts, presentations, and posters by the InsightRX Data Science team

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Thought Leadership Blog Posts

Expert commentary and analysis from the Data Science team on trends shaping drug development and patient care

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How to Cite InsightRX Nova

Recommended citation formats for researchers and clinicians referencing InsightRX Nova

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R Packages

The InsightRX Data Science team also maintains the following R packages:

Provides equations commonly used in clinical pharmacokinetics and clinical pharmacology, such as equations for dose individualization, compartmental pharmacokinetics, drug exposure, anthropomorphic calculations, clinical chemistry, and conversion of common clinical parameters.

Simulates dose regimens for pharmacokinetic-pharmacodynamic (PK-PD) models described by differential equation systems.

Allows estimation of individual MAP Bayes estimates, based on population PK-PD models and collected clinical data.

Easily simulates pharmacokinetic/ pharmacodynamic (PK/PD) endpoints in response to dose adaptation.

Evaluate predictive performance of PK/PD models in historical datasets, in the context of model-informed precision dosing (specifically Bayesian updating).

Provides convenience functions around Stan, Torsten, and PKPDsim. The goal of the package is to make it easier to perform full-Bayesian inference in the context of model-informed precision dosing.