1928 Diagnostics

Preguntas y respuestas

• Expert support
  1928 has a skilled team ready to help with bioinformatics analysis and interpretation.
• Virulence factors
  1928 studies the factors that make bacteria harmful.
• Clustering analysis
  The SaaS groups bacteria based on genetic similarities to understand their spread.
• Resistance profiling
  The SaaS analyzes how bacteria resist antibiotics.
• Transmission analysis
  1928 analyzes how infections spread using additional data.
• Cloud based technology
  1928 uses cloud technology to help fight antibiotic resistance.
• Sample quality control
  The SaaS ensures that samples are of high quality for accurate results.
• Species identification
  1928 can identify different types of bacteria from samples.
• Bioinformatics platform
  The SaaS uses DNA data to help control infections and identify superbugs.
• Whole genome sequencing
  1928 uses whole genome sequencing to track and prevent outbreaks of infections.
• Community responsibility
  Everyone has a role in fighting antibiotic resistance, just like in climate change.
• High precision detection
  1928 provides accurate detection and analysis of dangerous germs in hospitals.
• Sample reference library
  The SaaS creates a library of sample references for better analysis.

• DNA sequencing data
  Provides detailed information about germs, helping to understand how they spread and how to fight them.
• Resistance profiling
  Identifies how germs resist treatment, which helps in choosing the right medicine for patients.
• Improving world health
  Fighting antibiotic resistance helps ensure that antibiotics remain effective for everyone.
• Quality control of samples
  Ensures that the data used for analysis is accurate, leading to better decisions in infection control.
• Virulence factors identification
  Understanding how harmful germs are helps in developing better prevention strategies.
• Tracking and controlling outbreaks
  By identifying superbugs, healthcare providers can prevent future infections and keep patients safe.
• Creating a sample reference library
  Builds a database that can be used for future research and infection control efforts.
• Saving costs for healthcare systems
  Controlling infections reduces the need for expensive treatments and hospital stays.
• Clustering and transmission analysis
  Helps track how infections spread, allowing for quicker responses to outbreaks.
• High precision detection of pathogens
  This helps hospitals find dangerous germs quickly, which can stop infections from spreading.

• Patients
  They can benefit from safer hospital environments and better care through improved infection control.
• Researchers
  They can analyze DNA data to learn more about superbugs and how to fight them effectively.
• Policy Makers
  They can use the data to make better decisions about health policies and fight antibiotic resistance.
• Hospital Staff
  They can get support and training to understand how to prevent the spread of infections.
• Healthcare Providers
  They can use 1928 to find and control dangerous germs in hospitals, helping to keep patients safe.