Personalised biomedical insights empower patients with cancer, autoimmune or neurodegenerative diseases to live longer and better lives by discovering the most precise, effective and evidence-based treatment options.
Coremine Vitae is a CE-marked Medical Device MDD Class I intended to aid in personalised, shared decision-making.
Taking the patient’s medical data and preferences into account, it provides:
- Individual patient pathways in the context of international and national clinical guidelines;
- The value-based selection of molecular and genomic testing;
- Tailored standard of care and experimental treatment options with their rationale;
- Applicable clinical trials.
- Evidence-based behavioral, lifestyle interventions;
- World-leading experts in the field.
Coremine Vitae offerings
Individual Biomedical Insights Reports
Coremine Vitae individual reports are offered to patients, their treating clinicians, and other stakeholders.
Application Programming Interface (API)
How it works
The powerful combination of Human and Machine intelligence
Coremine Vitae is a digital health solution for personalised medicine. Artificial Intelligence such as text-mining, Natural Language Processing (NLP), rule-based and case-based reasoning harvests information from scientific and real-world data. Based on the principles of Evidence-Based Medicine and real-world research, it identifies relevant treatment options related to biomarkers. A web application and standard operating procedures (SOPs) provide multiple quality control checkpoints to bioinformaticians and subject matter expert’ users before reporting actionable insights to healthcare providers. The resulting personalised biomedical intelligence reports are designed for shared decision-making with the patient. A secure collaboration portal facilitates the data collection, incl. the monitoring of quality indicators, and digital communication between patients, the healthcare team, bioinformaticians and researchers. Coremine Vitae recently obtained the CE-mark Medical Device MDD Class I certification.
The impact of Coremine Vitae
Patients and next-of-kin
Patients with cancer, autoimmune or neurodegenerative diseases and their relatives should know that they are doing all that is feasible to explore treatment options and feel assured that they have exhaustive knowledge of their treatment options. They actively participate in planning and optimizing their treatment strategy, they reach a better understanding of their complex disease and make pro-active choices regarding diet and lifestyle.
The patient’s confidence in scheduled treatment program, the impact of knowing that they are doing all that is globally possible as well as being better informed and more actively involved in their treatment process is expected to improve the quality of life (HR-QoL) and will help patients to reach empowerment as a psychological and individual outcome.
Coremine Vitae enables clinicians to be updated on the optimal therapeutic roadmaps. Our system provides them with a unified, AI-assisted, and evidence-based process to leverage the availability of multi-omics technologies incl. next-generation sequencing (NGS), and to respond to the rapid growth of healthcare data. This will yield the reduction of unnecessary treatment and improvement of the effectiveness of the healthcare team.
Society and policy makers
More efficient treatments and less adverse effects will save time and resources in the healthcare system and reduce sick leave and increase productivity in society.
Coremine Vitae’s feedback loop and surveillance procedures collect information about why recommended treatments are not prescribed, which can provide valuable insights to policy makers.
Life-science research & development
Research and clinical practice are closely integrated in the development of personalised medicine. New clinical pathways that integrate clinical treatment and research will accelerate the translation of personalised medicine discoveries into clinical practice. Coremine Vitae promotes such pathways and the collection and usage of real-world evidence on overall survival and quality of life.
Clinician Domain Competence
Studies show that intervention providers with decision support are more likely to order the appropriate treatment or therapy.
Meta-analysis of 46 heterogeneous studies (Bright et al., 2012) showed that intervention providers with decision support were more likely to order the appropriate treatment or therapy (OR, 1.57 [CI, 1.35 to 1.82]). Most studies were good quality, and most were evaluated in multisite trials.
Patient Decisional Conflict and trade-off between various value preferences
Patient decision aids are effective to increase shared decision-making and physician communication. They efficiently decrease decisional conflict related to feeling uninformed.
Compared to usual care, decision aids decreased decisional conflict related to feeling uninformed (MD -9.28/100; 95% CI -12.20 to -6.36; 27 studies; N = 5707; high-quality evidence), indecision about personal values (MD -8.81/100; 95% CI -11.99 to -5.63; 23 studies; N = 5068; high-quality evidence) (D. Stacey et al., 2017).
Treatment outcome prediction, identification of risk groups
Biomarkers allow for classification of the patients likely to respond or resist to the treatment but also at risk of treatment toxicity (Balduzzi et al., 2014; Chan et al., 2017).
As an example, the table above shows biomarkers with high-quality evidence for the choice of treatments in patients with Non-small-cell lung carcinoma (NSCLC), which accounts for about 85% of all lung cancers.
Studies show improved survival on specific targeted therapies for cancer patient groups defined by their condition and specific biomarkers. Decision Aids that promote the right usage of such therapies for the right patient at the right time will contribute to improve survival.
In 2015, a comprehensive meta-analysis of 570 phase II single-agent studies published in the years 2010-2012 compared response rate (RR), progression-free survival (PFS), and overall survival in study arms that used a personalized treatment strategy versus non-personalized. The analysis demonstrated that the personalized approach consistently outperformed the non-personalized strategy (Schwaederle et al., J Clin Oncol 33:3817-3825).