Lonestar VOC Analyzer
An easy to use analyzer for the detection of VOC biomarkers in clinical samples
- Rapid, sensitive and selective VOC detection and quantification
- Versatile disease biomarker analysis with wide-ranging applications
- Cost-effective and easy to use for both clinicians and researchers
Volatile organic compounds (VOCs) are the end product of metabolic processes in the body that are related to diseases. VOCs have been collected from various sample types including breath, blood urine and feces, they can also be collected from in vitro cell samples or ex vivo tissues.
Using Field Asymmetric Ion Mobility Spectrometry (FAIMS), the Lonestar VOC Analyzer can analyze VOCs to aid in the detection of disease biomarkers related to a range of illnesses including infections, inflammatory diseases and cancers. Our customers include GSK, Samsung, and the UK National Health Service, among many others.
Parts per billion detection levels combined with inlet control for high dynamic range
Ideal for rapid screening of samples
Compatible with breath, urine, stool, blood, sweat, sputum and other VOC sources
Cost-effective and easy to use for both clinicians and researchers
Software-adjustable selective screening for target compounds
Integrated temperature, flow and humidity sensors for stable, closed-loop operation
Network and wireless connectivity for remote monitoring and operation
Easy integration of other sensor data and control of third party systems
Powerful custom software for data visualisation, real-time control and offline analysis
How it works
Lonestar is designed to accept samples from a range of inputs. For solid or liquid samples as well as in vitro or ex vivo VOC sources, VOCs can be collected via the ATLAS Headspace Sampler.
The FAIMS chip inside Lonestar separates and identifies VOCs by means of their relative ion mobilities. When using ATLAS, samples can be fed directly from ATLAS into Lonestar.
As a new FAIMS user, we can support you to develop your own effective sample and data analysis methodologies. The Lonestar VOC Analyzer uses an open data format, allowing users to also use off-the-shelf multi-variate analysis tools. Raw FAIMS spectra are multi-dimensional and extremely rich in information and a wide range of tools can be applied to their interpretation.
A model (such as the OPLS-DA model, left) or classification algorithm is then developed and applied to the reduced data set to group samples into medically relevant categories. The form of the classifier depends upon the dataset, but random forest, sparse logistic regression and support vector machines have all been successfully deployed. These models require thorough independent validation before being put into widespread use.
We have worked with a number of eNose platforms for medical breath research and we have found Owlstone’s FAIMS technology and Lonestar instrument to provide very good accuracy.
We have been using FAIMS for almost five years and have found it able to non-invasively detect a broad range of diseases, including cancer, with high sensitivity and specificity
Lonestar VOC Analyzer Technical Specifications
Field Asymmetric Ion Mobility Spectrometry
Positive and negative ions
Inlet / Outlet
1/8 Swagelok compression fittings
Volatile Organic Compounds
User adjustable inlet dilution for ppb - %
Required Gas Supply
Clean, dry air (there is an integrated, replaceable scrubber)
Max Heater Temperature
0% - 95%
Temperature, humidity, flow and pressure
Inbuilt tracker ball
Real-time chemical spectra and stored data
Inbuilt PC running Windows
Custom online control software
383 x 262 x 195 mm