ARTIDIS rapidly diagnoses cancer, detects its aggressiveness and predicts the probability of a patient developing metastases based on the nanomechanical biomarker for cancer. The ARTIDISNET platform combines the nanomechanical biomarker with the patient’s clinical data to guide the best therapy choice for each individual patient.
The problem we are solving
ARTIDIS creates confidence for patients and clinicians through exact diagnosis and effective treatment optimization
Current cancer diagnosis is slow and inefficient
While waiting for a diagnosis over several days, patients have to deal with high anxiety and a challenging emotional experience. Healthcare professionals are dedicated to cure their patients but are challenged by the lack of automated and accurate tools supporting their decision-making. ARTIDIS provides a data-based diagnosis in less than three hours.
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Cancer is a global problem. Today, there is a 20% chance that cancer will be diagnosed in the course of a lifetime. Therefore, regular screening and the consequent biopsy procedure when exhibiting suspicious lesions have meanwhile become standard of care for different cancer types like breast, lung, colon or skin. Nevertheless, the current cancer diagnosis process remains slow and inefficient. Centralized labs require complex infrastructures and have high workflow maintenance costs. Moreover, the agonizing wait verifying that the detected lesion is benign or malignant can take up to several weeks. This causes unnecessary and extreme anxiety for the patient. The fact that more than 70% of patients who undergo a biopsy of suspicious lesions have a benign condition does not make waiting any better.
Insufficient tools for cancer treatment optimization
For every one life saved during cancer treatment, there are 3 to 10 patients who are overtreated since there are no reliable biomarkers supporting the doctor’s decision-making. This creates unnecessary emotional burden and financial inflation. ARTIDIS evaluates cancer aggressiveness and enables the development of personalized cancer treatment plans based on the nanomechanical biomarker.
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Another major issue in the current clinical workflow is a lack of accurate optimization tools for patients diagnosed with cancerous lesions. These tools would prevent under- or overtreatment and improve patient outcomes. In the area of breast cancer, for example, we currently count 3-10 overtreated patients for every patient life saved (Marmot et al., 2012).This has a massive impact on the patient’s quality of life due to the severe side effects accompanying the cancer treatment. In addition, there is a high cost burden for the entire health ecosystem.
