Drug- & Toxicity Testing


Fast detection of cell reactions on drugs and toxins

You are looking for reliable methods to detect cell reactions, but...

  • you don‘t want to perform animal testing?

  • you can‘t get the right biomarker/read-out?

  • current analyses are too expensive?

  • you need reliable and sensitive results?

BioRam© provides you with:​

  • Fast

  • Easy

  • Reliable

  • Sensitive

  • Sample saving

  • Non-invasive

  • Fast amortizing device

  • Analysis of 2D and 3D tissues

  • Single Cell information

Analysis using BioRam is saving your money - giving you reliable results for your next steps!



Application – Analysis of an engineered 3D human airway mucosa model using Raman spectroscopy

Besides being ethically questionable, animal testing is highly cost intensive and time consuming. Therefore, increasing effort is put into evaluating alternative non-animal methods for studying diseases and testing products - resulting in more and more elaborated tissue models and a broad variety of cell analysing systems. However, analysis of these models is not trivial and there is an increasing demand for handy, fast and easy-to-use cell detection and characterization methods. Raman spectroscopy is a highly sensitive analytical method for marker-free and non-invasive identification and analysis of single cells. As Raman spectroscopy works within physiological environment and does not require any chemical staining or antibody-based markers, the examined cells remain entirely vital and undisturbed. Here, the huge capacity of the BioRam® technology is shown on the example of an engineered 3D humanairway mucosa model. 

Raman analysis of human airway mucosa model. Light micrographs of Calu-3 (A) and hTEC (B) at the Raman micro spectroscope. Red crosses show measuring positions in the cytoplasm; scale bars: 20 mm. Scores plot (C) shows cell type-specific data separation. (D) Mean spectra of hTEC (red) and Calu-3 datasets (blue). Framed areas indicate wave number ranges, which are relevant for data separation. (Figure 1, Steinke et al.)

In detail analysis of Raman data showing scores plots of wave number areas relevant for cell type-specific data separation. (Figure 2, Steinke et al.)

An engineered 3D human airway mucosa model based on an SIS scaffold. Maria Steinke, Roy Gross, Heike Walles, Rainer Gangnus, Karin Schütze, Thorsten Walles; Biomaterials. 2014 Aug;35(26):7355-62. doi: 10.1016/j.biomaterials.2014.05.031. Epub 2014 Jun 7.