Comprehensive Treatment Decision Support of More Than 1,000 Patients by the Medical Device Molecular Health Guide®

Background: Comprehensive characterization of the cancer genome provided important insights for development of new therapies. Current NGS based personalized medicine requires the combination of the patientś molecular information with suitable databases and the identification of relevant publications to enable creation of a clinical report. Here we report on more than 1,000 cancer patients analyzed with MH Guide and highlight the importance of assessing the safety of suggested treatments for solid tumors. Methods: We constructed an integrated database, the Dataome®. Based on that, we developed and registered the in vitro diagnostic medical device MH Guide in Europe for clinical treatment decision support (TDS). Results: MH Guide identified potential drug responses based on effective (> 14.1k), ineffective (> 4.8k) and toxic (> 2.3k) biomarker information in 1,352 cancer patients with different solid tumors such as lung, breast, pancreatic, and ovarian cancer. On average, 17 actionable data points from annotated variants were identified for each patient. MH Guide classifies variants as germline or somatic and assigns them to one of three levels of clinical validity: 1. clinically endorsed (approved by FDA), 2. clinically observed (predictive effect observed in clinical trials), or. 3. translational (supported by pre-clinical or computational evidence). Conclusion: MH Guide enables efficient variant interpretation using curated data, including evaluation of quality parameters. Molecular Health (MH) technologies can assist clinicians in making informed decisions about the benefits of established therapies. On this basis, MH has signed contracts with statutory health insurances in Germany. The aim is to reduce the overall cost of treatment while improving clinical outcomes and quality of life. Primary endpoint will be the change of the therapy recommendation in the tumor board after comparing the MH Guide analysis results with the prior recommendation.