Advances in modern computational technologies enabled capturing and analyzing large amounts of high-quality information with unprecedented resolution. Such data are the prerequisites for enabling personalized healthcare, a concept that holds a great promise for improving the diagnosis and treatment of many diseases.

Recently, artificial intelligence (AI) has transformed industries around the world and has the potential to radically alter the field of healthcare by providing a platform for faster delivery of personalized medicine. Most importantly, this will have a huge impact on the healthcare delivery and will put a patient in the centre. AI and personalized healthcare will in addition to patients transform daily life of diagnostic labs, healthcare providers, regulators, healthcare system and societies.

From chronic diseases and rare diseases to image and risk assessment, there are nearly endless opportunities to leverage AI technology to deploy more precise, efficient, and impactful interventions at exactly the right moment in a patient’s care.

Chroma is transforming diagnostics of a wide range of chromosomal abnormalities in individuals by employing AI technology in simplifying and further developing karyotyping procedure.

Karyotype tests are widely used in clinical diagnostics to detect chromosomal anomalies that could lead to infertility, birth and development anomalies defects, anomalies that individuals could pass down to their children, certain disorders of the blood or lymphatic system. As such, karyotyping is widely used in clinical diagnostics.

Clinical cytogeneticists analyze karyotypes in the process of pairing and ordering all the chromosomes of a cell. This process provides a genome-wide snapshot of an individual's genome and is used to detect gross genetic changes. Karyotypes can reveal changes in chromosome number associated with aneuploid conditions, such as trisomy 21 (Down syndrome). Careful analysis of karyotypes can also reveal subtler structural changes, such as chromosomal deletions, duplications, translocations, or inversions. In fact, as medical genetics becomes increasingly integrated with clinical medicine, karyotypes are becoming a source of diagnostic information for specific birth defects, genetic disorders, and cancers.

Despite being relatively affordable, karyotyping is time consuming and requires highly-trained and skilled personnel in detecting genetic anomalies. Often, clinical cytogenetic specialists spend hours analyzing patient samples under the microscope. Shortening turnaround times is of high importance to enable genetics-based conclusions to inform clinical diagnosis at treatment.

AI has the potential to transform clinical cytogenetics by shortening turnaround time, providing more precise and standardized workflow.

Potential benefits:

Clinical cytogenetic specialist:

Timely and precise AI-based karyotyping would provide clinical cytogenetics to analyze more samples in a given time frame and inform treating physician about diagnostic findings.

Patient benefit: Reduced turnaround time by AI-based karyotyping, would provide benefits for patients by reducing under-diagnostics (shortening waiting lists)and provide faster results for situations when time matters.

Treating physician: Precise, standardized and faster diagnostics enables treating physician to start treatment and make informed decision more timely.

Healthcare system: Shortened turnaround time increases diagnostic capacity of clinical cytogenetic labs resulting in reduced / diminished waiting lists

Standardized and digitalized karyotyping procedure enables data collection at scale for future analysis.

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