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    • Omics Assays
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OMICS
ASSAYS

VAIDR uses AI to help you
control for cell variability

When you study the effects of any type of treatment on your cells, you need to be sure that the differences between conditions and controls are due to your treatments, not due to differences in the cells before the treatments.

VAIDR gives you a cost-efficient, non-destructive way to detect variability in cell cultures. Use it to exclude outliers from your experiments or analysis, or take unavoidable variability into account when you analyze your assay results. VAIDR automatically tracks all primary data, metadata, and results, making post-hoc analysis and documentation a breeze.

OMICS
ASSAYS

VAIDR uses AI to help you
control for cell variability

When you study the effects of any type of treatment on your cells, you need to be sure that the differences between conditions and controls are due to your treatments, not due to differences in the cells before the treatments.

VAIDR gives you a cost-efficient, non-destructive way to detect variability in cell cultures. Use it to exclude outliers from your experiments or analysis, or take unavoidable variability into account when you analyze your assay results. VAIDR automatically tracks all primary data, metadata, and results, making post-hoc analysis and documentation a breeze.

OMICS
ASSAYS

VAIDR uses AI to help you control for cell variability

When you study the effects of any type of treatment on your cells, you need to be sure that the differences between conditions and controls are due to your treatments, not due to differences in the cells before the treatments.

VAIDR gives you a cost-efficient, non-destructive way to detect variability in cell cultures. Use it to exclude outliers from your experiments or analysis, or take unavoidable variability into account when you analyze your assay results. VAIDR automatically tracks all primary data, metadata, and results, making post-hoc analysis and documentation a breeze.

Workflow Example

omics assays vaidr tri

With VAIDR, you

  • you will know that your assay results are solid – and you will be able to show it.
  • you save on cell prep for cells that you will have to throw out in the end
  • you will produce results reliably by avoiding non-results due to process input variability
  • You secure your research, save labor and material costs
SEE OUR OFFER
vaidr artificial intelligence

Workflow Example

omics assays vaidr tri

With VAIDR, you

  • you will know that your assay results are solid – and you will be able to show it.
  • you save on cell prep for cells that you will have to throw out in the end
  • you will produce results reliably by avoiding non-results due to process input variability
  • You secure your research, save labor and material costs
SEE OUR OFFER
vaidr artificial intelligence

Workflow Example

omics addays vaidr mobile

With VAIDR, you

  • you will know that your assay results are solid – and you will be able to show it.
  • you save on cell prep for cells that you will have to throw out in the end
  • you will produce results reliably by avoiding non-results due to process input variability
  • You secure your research, save labor and material costs
SEE OUR OFFER

Common Challenges
in Omics Assays

Expensive prep, results lost in noise

You’ve spent budget for cell culture, for cell prep, for analysis… and it’s all for naught because your read-outs are all over the place. You can barely see a pattern, but it’s just below significance. You’re close, but the experiment is failed and the budget is wasted.

VAIDR helps you reduce noise in your read-outs by reducing noise in the cells going into your experiments: VAIDR uses non-destructive, high-throughput imaging and sophisticated machine learning algorithms to identify faulty samples. Get solid results by excluding these samples either from your analysis or even from cell prep.

Use VAIDR to image and analyze samples before and after treatment to derive changes in cell quality and integrate these additional read-outs with those of your main assay to make the most of your budget and increase your chance of finding the signal in the noise.

Uncertain reliability of results

You’ve done your experiments and got fascinating results. You know the prep and analysis were perfect because you’ve done them and checked them twice. But do you know that the results are even due to your prep? Have you checked that your cells were the same before you treated them, beyond a quick glance through the microscope? Would you be able to convince a reviewer or customer if they asked? That could be a question that might invalidate all your hard work.

VAIDR uses bright-field microscopy and sophisticated AI algorithms to objectively quantify quality in cell cultures. It automatically tracks image data, metadata, and quality-related read-outs so you can document and demonstrate that cells were the same before treatments and different after. You can rest easy and be sure of your results.

Late Project Failures

You’re nearing the end of a large omics research project. At 90% completion, while the results are being assembled, it becomes clear that the cells were much less morphologically uniform than in initial trials. Control wells are not really comparable across plates, casting doubt on the validity of the entire campaign.

VAIDR helps you spot trouble early on by establishing a morphological quality baseline. Any deviation is detected quickly and cost-efficiently by the combination of label-free imaging and powerful machine-learning analysis. Spot emerging problems early on and react quickly to either stop a doomed project or save a troubled project while there is still time.

Common Challenges in Omics Assays

Expensive prep, results lost in noise

You’ve spent budget for cell culture, for cell prep, for analysis… and it’s all for naught because your read-outs are all over the place. You can barely see a pattern, but it’s just below significance. You’re close, but the experiment is failed and the budget is wasted.

VAIDR helps you reduce noise in your read-outs by reducing noise in the cells going into your experiments: VAIDR uses non-destructive, high-throughput imaging and sophisticated machine learning algorithms to identify faulty samples. Get solid results by excluding these samples either from your analysis or even from cell prep.

Use VAIDR to image and analyze samples before and after treatment to derive changes in cell quality and integrate these additional read-outs with those of your main assay to make the most of your budget and increase your chance of finding the signal in the noise.

Uncertain reliability of results

You’ve done your experiments and got fascinating results. You know the prep and analysis were perfect because you’ve done them and checked them twice. But do you know that the results are even due to your prep? Have you checked that your cells were the same before you treated them, beyond a quick glance through the microscope? Would you be able to convince a reviewer or customer if they asked? That could be a question that might invalidate all your hard work.

VAIDR uses bright-field microscopy and sophisticated AI algorithms to objectively quantify quality in cell cultures. It automatically tracks image data, metadata, and quality-related read-outs so you can document and demonstrate that cells were the same before treatments and different after. You can rest easy and be sure of your results.

Late Project Failures

You’re nearing the end of a large omics research project. At 90% completion, while the results are being assembled, it becomes clear that the cells were much less morphologically uniform than in initial trials. Control wells are not really comparable across plates, casting doubt on the validity of the entire campaign.

VAIDR helps you spot trouble early on by establishing a morphological quality baseline. Any deviation is detected quickly and cost-efficiently by the combination of label-free imaging and powerful machine-learning analysis. Spot emerging problems early on and react quickly to either stop a doomed project or save a troubled project while there is still time.

Common Challenges in Omics Assays

Expensive prep, results lost in noise

You’ve spent budget for cell culture, for cell prep, for analysis… and it’s all for naught because your read-outs are all over the place. You can barely see a pattern, but it’s just below significance. You’re close, but the experiment is failed and the budget is wasted.

VAIDR helps you reduce noise in your read-outs by reducing noise in the cells going into your experiments: VAIDR uses non-destructive, high-throughput imaging and sophisticated machine learning algorithms to identify faulty samples. Get solid results by excluding these samples either from your analysis or even from cell prep.

Use VAIDR to image and analyze samples before and after treatment to derive changes in cell quality and integrate these additional read-outs with those of your main assay to make the most of your budget and increase your chance of finding the signal in the noise.

Uncertain reliability of results

You’ve done your experiments and got fascinating results. You know the prep and analysis were perfect because you’ve done them and checked them twice. But do you know that the results are even due to your prep? Have you checked that your cells were the same before you treated them, beyond a quick glance through the microscope? Would you be able to convince a reviewer or customer if they asked? That could be a question that might invalidate all your hard work.

VAIDR uses bright-field microscopy and sophisticated AI algorithms to objectively quantify quality in cell cultures. It automatically tracks image data, metadata, and quality-related read-outs so you can document and demonstrate that cells were the same before treatments and different after. You can rest easy and be sure of your results.

Late Project Failures

You’re nearing the end of a large omics research project. At 90% completion, while the results are being assembled, it becomes clear that the cells were much less morphologically uniform than in initial trials. Control wells are not really comparable across plates, casting doubt on the validity of the entire campaign.

VAIDR helps you spot trouble early on by establishing a morphological quality baseline. Any deviation is detected quickly and cost-efficiently by the combination of label-free imaging and powerful machine-learning analysis. Spot emerging problems early on and react quickly to either stop a doomed project or save a troubled project while there is still time.

“The VAIDR team was great at adapting their system to our specific research question. They are excellent collaborators.”

Prof. Dr. Kerstin KutscheInstitut für Humangenetik Universitätsklinikum Hamburg-Eppendorf
PreviousNext

“The VAIDR team was great at adapting their system to our specific research question. They are excellent collaborators.”

Prof. Dr. Kerstin KutscheInstitut für Humangenetik Universitätsklinikum Hamburg-Eppendorf
PreviousNext

“The VAIDR team was great at adapting their system to our specific research question. They are excellent collaborators.”

Prof. Dr. Kerstin KutscheInstitut für Humangenetik Universitätsklinikum Hamburg-Eppendorf
PreviousNext
vaidr artificial intelligence
vaidr artificial intelligence
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info@vaidr.de

+49 40 66894303

LET’S TALK
OMICS ASSAYS.
GET IN TOUCH.

info@vaidr.de

+49 40 66894303

LET’S TALK OMICS ASSAYS.
GET IN TOUCH.

LET’S TALK
OMICS ASSAYS.
GET IN TOUCH.

info@vaidr.de

+49 40 66894303

vaidr logo tri

VAIDR is a product of:

TRI Thinking Research Instruments GmbH
Große Freiheit 77
22767 Hamburg

+49 40 66894303 | info@vaidr.de

Legal disclosure / Impressum
Data privacy / Datenschutz

vaidr logo tri

VAIDR is a product of:

TRI Thinking Research Instruments GmbH
Große Freiheit 77
22767 Hamburg

+49 40 66894303 | info@vaidr.de


Legal disclosure / Impressum
Data privacy / Datenschutz

vaidr logo tri

VAIDR is a product of:

TRI Thinking Research Instruments GmbH
Große Freiheit 77
22767 Hamburg

+49 40 66894303 | info@vaidr.de


Legal disclosure / Impressum
Data privacy / Datenschutz

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