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Kasparov's Law

Author: Ron Keizer

At InsightRX we are trying to improve the practice of medicine with computational solutions. As a team of scientists and engineers we are obviously very excited about the huge leaps forward in artificial intelligence (AI) and machine learning (ML) seen in the last decade. We obviously want to apply such solutions wherever possible in the precision medicine tools we are building.

Read the entire article here, or visit science.insight-rx.com to learn more of the science behind the InsightRX platform.

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A Learning Health System Paves the Way For Precision Medicine

Author: Sirj Goswami

Drugs and medical treatments are typically designed for the “average patient.” Individual patient variability is usually not taken into account, sometimes leading to undesirable clinical outcomes for patients. The goal of precision medicine is to address this unmet medical need by finding the right medication and the right dose for each patient every time. Precision medicine takes into account individual variability when optimizing a patient’s treatment strategy.

The primary goal of precision medicine has not yet been realized. We are still unable to effectively predict treatment regimens that will maximize treatment benefit in different patient populations.

For example, an underweight neonate with poor kidney function does not fall into the spectrum of what is clinically defined as "average", and simply accounting for simple demographic characteristics such as the patient's age and body weight may lead to suboptimal outcomes.

A data-driven framework that creates a mechanism to continuously improve and tailor treatment strategies in real time may be the catalyst to address this knowledge gap and bring precision medicine to the forefront of healthcare....

Read the rest of this article here, or visit sirjgoswami.com to read more related articles.

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Overcoming Adption Barriers of Cloud-based Precision Dosing in Healthcare

Author: Sirj Goswami

Recently I gave a talk about adoption barriers of precision dosing software — such as the InsightRX platform — in healthcare. In the talk, I highlight several of the barriers that we have encountered in integrating our platform with several US hospitals. I also give some directions for future opportunities in this space. I've posted the slides for my presentation on our science blog.

On my personal website you will also find a short article detailing some of my thoughts on the issue.

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Model-based TDM in Oncology

Author: Ron Keizer

I recently gave a talk at the 2nd International Workshop on Clinical Pharmacology of Anticancer Drugs in Madrid on the topic of Model-based TDM in Oncology.

In the talk I provided some background on model-based dosing in general, and presented some specific case studies in oncology (mainly around imatinib and busulfan). I also pointed at some future opportunities in model-informed precision dosing in oncology.

The slides of this talk are provided here, or visit science.insight-rx.com to learn more of the science behind the InsightRX platform.

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Stanford Children's CMIO Talks Home-grown Clinical Decision Support

"Our hospital is located in Silicon Valley, which is a very fortunate position to be in. As part of the Stanford University campus, we have the opportunity to partner with both students in the biomedical informatic program, computer science programs, as well as multiple local startups."

"Another type of advanced clinical decision support tool, again [one that's] web-based, and EHR-integrated, is a product that we have been collaborating on with a small startup company called InsightRX."

Read the entire article here.