Medical treatments are typically designed for the “average patient”. This “one-size-fits-all” approach often results in treatments being successful for some patients but not for others. The emergence of precision medicine aims to change this, by taking into account individual differences in people’s underlying biological characteristics. Precision medicine gives healthcare practitioners better tools to improve understandings of complex mechanisms underlying a patient’s health or disease, and to better predict which treatments will be most effective.
The technology underlying the InsightRX platform incorporates the principles of quantitative pharmacology and machine learning to provide an individualized understanding of a patient’s response to treatment. Quantitative pharmacology describes in mathematical and statistical language the relationship(s) between disease, drug action, and individual variability, which enables patient specific quantitative decision-making. The InsightRX platform delivers this technology in the form of easy to use clinical decision support tools at the point of care to help guide treatment decision-making.
The InsightRX platform guides treatment decisions at both the individual level and the population level. At the individual level, drug concentration and biomarker data are collected over-time to learn about the patient response and optimize treatment. At the population level, as more data is collected in larger patient populations, or in infrequently encountered patient populations, our pharmacological models and clinical algorithms that guide treatment recommendations will learn and will become more precise.
InsightRX leverages clinically validated pharmacokinetic models, patient physiology, pharmacogenomics, drug concentrations and biomarkers to optimize dosing. Real-time patient data and machine learning are combined to understand individual patient pharmacology and inform dose optimization.
InsightRX leverages disease-based pharmacodynamic models to inform treatment decision making. Real-time patient data and machine learning are combined to simulate treatment and disease trajectories and inform treatment decision making.
InsightRX clinical analytics platform functionality ties together treatment strategies with patient outcomes. The data collected on the platform is leveraged to continuosly learn about patient populations, and provide patient benchmarking and dose/response metrics.
|July 7th, 2016||InsightRX welcomes new CTO Elena Scheiner! Elena is joining from Salesforce where she was a software architect working on UI, mobile and machine learning projects.|
|Mar 9th, 2016||InsightRX CSO Ron Keizer wins award from American Society for Clinical Pharmacology and Therapeutics (most-cited journal article).|
|Jan 14th, 2016||InsightRX partnering with UCSF and St. Jude's to individualize busulfan chemotherapy dosing for Gene Therapy trial in neonates.|
|Dec 10th, 2015||InsightRX presents at Plug&Play IoT/Healthcare EXPO See the presentation here.|
|Dec 8th, 2015||InsightRX featured in UCSF magazine, "The right dose: how pharmacy researchers are making medicine more precise" Read the article here.|
|Nov 6th, 2015||Insight selected to Exhibit at the 2015 ADA Healthtech Showcase.|
|Feb 4th, 2015||InsightRX featured in Vatornews highlighting up-and-coming healthcare companies. Read the article here.|
|May 31st, 2015||InsightRX raises Seed funding round from Launchpad Digital Health and Plug&Play|
Please apply or request more info at email@example.com
Lead engineer with passion for backend systems, databases and infrastructure. As part of our engineering team you will be building new features from ground up and improving existing ones. You will be moving fast and releasing often. You will be innovating and collaborating on new ideas with engineering and scientific team.
You will be in charge or quality control, test planning, test automation and some build and deployment automation.
You will be innovating and collaborating on new ideas with engineering team and some of the best quantitative pharmacology scientists in the field.
As part of our data science team you will be building and extending the scientific infrastructure that forms the basis of our precision dosing and clinical analytics platform, as well as performing data (“big” and “small”) analyses on biomedical data from partners in hospitals and pharmaceutical industry in the US and abroad.