Partnerships

Lifestyle Behavior Change 

Cardiovascular diseases cause 31% of all global deaths. In recent studies, and including available data from the current COVID-19 pandemic, it has been shown that patients with cardiovascular co-morbidities such as hypertension, diabetes, and other cardiovascular diseases are at a significantly higher risk of fatality. In addition, behavioral risk factors including unhealthy diet, physical inactivity, tobacco use, and harmful use of alcohol can cause the onset of cardiovascular disease as well as disease progression.

This year, we are looking for companies that are developing behavior change solutions that empower people to reduce their risk of cardio-metabolic conditions (such as hypertension, chronic artery disease, etc.) by changing lifestyle habits. 

Track: Open to both Growth and Advanced

Patient Monitoring

Considering the current COVID-19 pandemic, patients worldwide living with chronic cardiovascular disease will not only be at risk for severe complications, many will not be able to receive timely treatment through office visits or physical therapy, and can put caretakers at risk. To improve patient care and reduce risk of death, patients and care teams can be empowered by patient-focused monitoring solutions that can track progression of the patients’ conditions and effectiveness of treatment as well as support early diagnosis of related conditions.  

We are looking for solutions which would allow a convenient and effortless way of longitudinally monitoring patients inside and outside the traditional healthcare setting, especially people with or at risk for cardiometabolic and renal diseases especially hypertension, coronary artery disease (CAD), congestive health failure (CHF) and chronic kidney disease (CKD). 

Track: Open to both Growth and Advanced

Biomarkers and Algorithms

Digital tools allow for a streamlined way of generating, collecting and analyzing data that can be used to explain or predict health-related patient outcomes, giving rise to new biomarkers. These biomarkers could play a valuable role in facilitating risk and event prediction, timely diagnosis and improved treatment of cardiovascular diseases. 

We are looking for companies developing novel biomarkers (digital, biological or in combination) and algorithms to predict the risk, progression or start of acute events in cardiovascular and renal diseases especially for hypertension, coronary artery disease (CAD), congestive heart failure (CHF) and chronic kidney disease (CKD).  

Track: Open to both Growth and Advanced

Risk-stratification and Decision Support

Predictive tools are opening new ways of assessing disease risk and providing informative, actionable healthcare advice. These tools can bring together and synthesize information from various sources to provide relevant insights, empowering physicians and healthcare providers to make decisions for achieving better healthcare outcomes for patients. 

We are looking for solutions that can predict risks for cardiovascular patients (such as risk of disease progression, risk of readmissions, etc.) and provide insights to better manage their condition throughout their disease journey.  We are especially looking for solutions for hypertension, coronary artery disease (CAD), congestive heart failure (CHF) and chronic kidney disease (CKD).  

Track: Open to both Growth and Advanced

Patient Identification (Prostate Cancer)

Cancer is the second leading cause of noncommunicable disease deaths in the world and the number of new cancer cases per year is expected to rise to 23.6 million by 2030. Prostate cancer is the second most common form of cancer in men in the United States representing 19% of newly diagnosed cancers and the third leading cause of cancer death in 2018.

While most of early-stage prostate cancer is curable, a subset of men will progress with biochemical recurrence.  New advances in analyzing clinical, imaging, pathological, and genomic data can possibly identify the best therapy option for survival while minimizing the risk for adverse events.

We are looking for easy-to-use solutions to identify patients who could benefit from specific prostate cancer therapies. We are looking for solutions that can capture, aggregate and analyzes data from disparate sources to identify prostate cancer cases in the United States, Germany, and France.

Track: Advanced Only

Patient Identification (NTRK Gene Fusion)

Cancer treatment is changing, and precision oncology is a new evolving modality. Today’s precision oncology treatment options could require verifying patient’s genomics in order to verify if they carry a key alteration that could be treated; alterations that include EGFR, ALK, ROS1, NTRK gene fusion and BRAF among others. The need for identification of these patients is crucial so that they can benefit from this tailored treatment approach.

We are looking for easy-to-use solutions to identify patients who could benefit from specific biomarker testing for NTRK gene fusions. We are looking for solutions that can capture, aggregate and analyze data from disparate sources to identify cases in the United States, Germany, and France.

Track: Advanced Only

Quality of Life and Performance Status Measurement 

Patient Performance Status (PS) is one of the key outcomes considered in cancer care. PS is a score that estimates a patient’s ability to perform activities of daily living (such as eating, sleeping, working, doing housework, etc.). PS plays an important role both in estimating prognosis and selecting the appropriate treatment for patients. Although many scales for PS are available, all of them depend on subjective interpretations by patients, caregivers, and doctors.

Another important outcome is a patient’s Quality of Life (QoL), which is measured using questionnaires and interviews covering several categories including: general, physical and psychological well-being, familial relationship, sexual and personal ability, optimism and belief and economic well-being.

We are looking for solutions that can utilize currently available technologies to measure parameters such as sleep pattern, daily activity (steps, exercise, duration and intensity), breathing pattern, body temperature, heart rate, and other parameters relevant for cancer patients. These could be used to calculate PS in a timely and objective way and also provide valuable information on outcomes like QoL that could be validated and may replace or supplement the standard questionnaires.

Track: Advance only 

Health of Women

Natural changes or diseases related to women’s reproductive health can have a wider impact on the overall health of women such as affecting their cardio-metabolic, mental and bone health. Some gynecological conditions are linked to increased risk of infertility and cardio-metabolic diseases. After menopause, women have a higher risk of developing cardiovascular disease and osteoporosis.

We are looking for solutions that aim to improve the overall health outcome of women in a holistic manner. We are especially looking for companies that are developing novel methods for managing overall needs of women with gynecological diseases such as Polycystic Ovarian Syndrome (PCOS) and endometriosis or needs of women during life stages such as menopause.

Track: Open to both Growth and Advanced

Adverse Event Detection  

Patient and drug safety are of paramount importance. Case processing of drug safety information can be a challenge as information is scattered across multiple sources, including internal platforms, social media, chatbots, and digital assistants. Some of the challenges include: 1) accurately clarifying side effects from previous illness symptoms; 2) dealing with rhetoric language such as irony, metaphor and sarcasm; 3) properly addressing negations and conditional/hypothetical constructions. 

We are seeking solutions for an accurate, efficient machine learning method (accessible as a REST API) to manage detection of all potential incoming drug-event combinations, regardless of how a user contacts the portal/application. We are looking to implement a single engine that can be deployed over different types of texts, providing reliable results. The approach must have the ability to detect drug-event combinations and map the identified information to corresponding well known ontologies, such as Medical Dictionary for Regulatory Activities (MedDRA) and WHO Drug Dictionary (WHO DD).

Track: Advanced Only