Mindera Health SkinAtlas™: The Dataset for Dermal Intelligence™

At Mindera Health, we are developing the SkinAtlas™, an expansive repository of skin data. This database is comprised of multiple data streams including molecular data from our dermal biomarker patch, as well as imaging data and patient metadata. The SkinAtlas™ contains samples both from various skin diseases, as well as across time from a single individual. The Mindera Health platform drives the generation of skin data and molecular content, uniquely positioning it to shape an era of skin analytics where the power of AI/machine learning can be applied across sectors (e.g., psoriasis/inflammation, skin cancer, consumer/beauty, microbiome).

The Mindera Health platform is the world’s first scalable technology to extract RNA data for healthcare decision making

The skin is our largest organ and our primary interface with the world. When skin becomes diseased, it can seriously impact both our physical and emotional well-being. It is a dynamic, constantly evolving organ, yet despite significant advances in the scientific understanding of the skin and the characteristic signatures of skin disease, diagnosis largely remains predicated on a subjective visual exam. This may be followed by a skin biopsy and histological examination. Typically, these procedures are known to have poor sensitivity, and in certain cases, such as inflammatory diseases, highly invasive biopsies are not medically justified.

A New Era of Predictive Skin Analytics

Mindera Health has developed a proprietary platform that allows for simple, rapid and painless extraction of RNA from the skin using a dermal biomarker patch. Subsequent Next-Generation Sequencing of the extracted RNA allows Mindera Health scientists to take a genetic and transcriptomic snapshot of the skin at the exact moment of the test. This rich patient-specific data set is then analyzed by machine learning algorithms to ask sophisticated questions of the data, for example, predicting the appropriate biologic drug for a patient prior to therapeutic selection and treatment.

Given the wealth of molecular information that is currently available and the pace at which new data continues to be acquired, the Mindera Health platform allows for a dramatic improvement in how patients are diagnosed and treated.

RNA Biomarker Analysis: An Actionable, Data-Driven Decision Platform

Analysis of biomarkers is quickly becoming the preferred method for early detection of disease, patient stratification and monitoring efficacy of treatment. Biomarkers can be used in clinical practice to identify risk for or diagnose a disease, stratify patients, assess disease severity or progression, predict prognosis, or guide treatment. In drug development, biomarkers may be used to help determine how a drug works in the body, to determine a clinically effective dose of a drug, to help assess whether a drug is safe or effective, or to help identify patients most likely to respond to a treatment and are least likely to suffer an adverse event. Biomarkers can sometimes be used as part of the approval process for a drug or treatment as part of regulatory decision-making. However, rapid and highly sensitive detection of changes in a biomarker is often technically impossible, or may require a cumbersome procedure involving multiple processing steps, necessitating large sample volumes and a prolonged diagnosis/prognosis timeline. The sample from a patient is often of a limited volume and not amenable to extensive processing or to procedures requiring multiple steps that extend the processing time.

Hardware + Software = Integrated Approach to Better Patient Outcomes

The Mindera Health platform solves these problems using a simple patch that only takes minutes to extract biomarkers, is minimally invasive, and painless for patients. Furthermore, the ability to collect patient data at scale, combined with high precision molecular testing results in a powerful platform with improved sensitivity and specificity, translating into huge cost savings for healthcare systems, particularly when applied to the prediction of response to hyper-expensive treatments. Biomarkers captured using the Mindera Health platform include DNA, RNA, protein, and small molecules; in particular, the role of RNA in chronic skin diseases is well characterized.

Artificial intelligence and machine learning methods have revolutionized how meaning can be derived from complex multidimensional data sets. Using this approach, a “training set” with known phenotypes is used to teach an algorithm how to differentiate between the groups. For example, the known phenotypes can be as simple as diseased skin and normal skin.

Once trained, the algorithm can be used to interrogate new samples and classify the data; hence, the algorithm is known as a “classifier”. As new samples are acquired, the training set grows and the algorithm can be continuously retrained.

Mindera Health technology can clearly detect biomarkers associated with psoriatic skin, and is building SkinAtlas to include biologic drug response as measured in dermal RNA.

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