Data2life built an AI-powered health data collection, processing, and analysis platform. Its proven proprietary software utilizes AI methods like NLP (Natural Language Processing) and big data analytics to capture real-world data (RWD) from multiple distinct platforms and seamlessly integrate it with existing life-science datasets, medical taxonomy (Dictionaries), creating unique real-world evidence (RWE) insights.

Real-World Evidence as defined by the FDA is effectively data that's gathered in everything that happens outside a traditional clinical trial ,and for years the FDA's used real-world evidence, in the form of online reporting systems, to help them essentially understand safety and efficacy of drugs once they have been put into market however they've understood that with the cost of clinical trials, the time of clinical trials,  RWE could actually be used to help speed up time to market speed up greater indicators of medications and more importantly speed up the understanding of how drugs can have a greater impact on the population.

While identifying this radical power shift across the Healthcare ecosystem; Digitization, Data democratization, Patient empowerment and centricity alongside with the explosion of Web 2.0 creating new data generators (e-patient). All of these, were Data2Life enabling landscape to then go ahead and executed its Patient-centric RWE vision.

The Data2life platform automatically scans and collects data from a huge variety of sources – from structured public and internal datasets and institutional sources (medical literature, electronic health records, medical claims, and regulatory databases) to unstructured, patient-generated testimonials from online patient communities, groups & social media platforms– to create one standardized and easy to analyze, holistic database for any substance, molecule or treatment. Data2Life is about automating the way we gain insights in healthcare, faster, affordable and holistic – "the Nex-Gen of RWE".

Data2life's insights are enabled by its one of a kind 'diagnostic-NLP' that can interpret and connect multiple types of texts and ontologies. Just like an attentive human MD, the company's machines can "read" and infer causality, history, symptoms and treatment pathways from unstructured patient's posts, automatically translating the layman patient testimonial into structured and formatted medical jargon, one can then analyze and compare.

Proven Products and Services for R&D Pioneers

Five years in the making, Data2life's solution has been developed and piloted with leading CROs (life sciences service providers) and Bio-Pharma companies, and recently growing its traction with innovative Canna-Pharma companies.

Data2Life platform is built in a way that it is 'source-agnostic' to execute this health intelligence-agency approach.

It is able to continuously harvest and digest a variety of data formats whether they are based on medical coding systems (like electronic medical record's diagnosis, lab tests, and other procedures) or scientific free text articles (summarizing clinical trials finding) as well as the patient's spontaneous and unstructured reports written in a non-standardize jargon ("Brain fog" "bee sting bites at my fingertips", "rollercoaster in my belly").

The second element within Data2Life's platform is where all the AI comes into play. The team at the company teaches the machines to understand the medical and pharmaceutical realm of context with more than 250 clinical coding systems and dictionaries and then let them identify patterns in the text, relationships and causal inferences that are statistically significant. Once the machines do their part, the team can package its solutions into Data Interaction Tools (SaaS).

Data2Life aims these solutions to those who are developing and designing drugs and other new therapies, to accelerate this necessary data-driven process and at the same time making this process more holistic and inclusive of patients.

Once the customers better distill the characteristics of a group of patients that would greatly benefit from new development, they can better define their target market and their clinical (very expensive) trial. They will be able to better manage the risk of their new product (and the risk of it falling in the market), as well as complying with the growing standard of personalized health.

Collecting and aggregating many patient journeys and their treatment pathway broadens their understanding beyond the narrow science/ molecular, statistical outcome orientation that is practiced today.

Experienced Leadership

The company is led by its two founders Itzik Lichtenfeld, Ph.D., a certified psychologist, Risk Management professional and seasoned executive with a track record of success in Health IT entrepreneurial endeavors. Limor BH Epstein, MedSc, MPH, a Public Health advocate versed in medical informatics ventures for over a decade.

Limor BH Epstein refers to herself as 'Skipper of this Yacht', in this her forth yacht (start-up) she is investing her talent and hard work. Limor has a Bachelors in Emergency Medicine (Medical Sciences) and practiced as a paramedical and PA while working in the ER (Emergency Room) and at the national EMS system. She has a Master's degree in Epidemiology, a Master's in Public Health, and is about to conclude her Ph.D. in Augmenting Evidence-Based Medicine by harnessing the patient spontaneous reports, that is to drive better decision making across the healthcare ecosystem. Currently, she is specializing in the medical informatics and Data Science her practice entails.

She has dedicated the past 12 years in training machines to automate medical-related research, medical informatics, and big data analytics, including handling and understanding health-related databases, and decoding complex contexts of pharmaceuticals and medicine.

While talking about her background, Limor shared that after her medical corps (Captain) service in the Israeli Defence Force (IDF), she started her career being an academic. She was a lecturer and clinical instructor at the Ben Gurion University (Faculty of Health Sciences) and in American Heart Association programs.

The Pursuit of Innovation

Limor believes that Data2Life's claim to fame is being Patient-centric in its data analytics! That is, the company is always including this important stakeholder reports when analyzing how a drug/treatment is performing in real –life, or what is the real burden of the diseases the patient is resonating in their daily struggle.

Additionally, Real-World Evidence (RWE) is the new holy grail of Innovation, Research and Development.  With the proven potential to accelerate drug development, marketing, and safety processes, yet it is notoriously hard to properly collect and analyze – especially patient-generated data.

While big pharma companies and CROs (Clinical Research Organizations- Pharma's outsourcing services) are treated to a variety of expensive RWE tools, no one is addressing the RWE needs of the upstarts spearheading medical innovation, despite clear market needs and demands except Data2Life. Moreover, the company is significantly driving decision making today in healthcare and in the sizzling cannabis market.

Limor believes that there are people who 'talk the Health AI talk' and then there are quite a little few who walk the walk. She takes pride in Data2Life being one of the latter.  Having a mature, automated, AI-powered RWD-platform. The main major differentiation that Data2Life has today is its high-grade medical machine learning, and even more so for non-professional users (patient) texts.

The machines Data2Life has trained for the past five years are already independent in identifying entities in unstructured data (free text). As of now, Data2Life trained its machines applying a good mix of supervised and unsupervised machine learning as well as the use of deep neural networks, letting the machines do some 'real Artificial intelligence'.

Remarkable Early-Existence Recognition

The Data2Life platform was formally released in early 2016, been validated and used by multiple 'tier 1' life sciences companies. The recent joint publication with Sanofi Pharma, released during 2018 showcased the use of Data2Life platform to detect months and weeks earlier safety signals (adverse events) of drugs out in the market. Some additional major achievements of the company are going to be published in the Pharmacoepidemiology and Drug Safety Journal in the upcoming month.

Cannabinoids medicinal purpose is another avenue of analytics the company is now immersed in and seeing promising results and impact.

The company has marked its impression on Tier 1 Pharma companies and proved that using its NLP technology to analyze patients reports from the social platform is superior to any other. Additionally, Data2Life was selected and graduated IBM's Accelerator, early on its existence. Data2Life had a lot of chances to compare its AI algorithms performances to the famous Watson supercomputer and gain publications over the years.

Newly exciting accomplishment has been Data2Life leadership of a novel project for depicting state of the art multi-dimensional and multi-national oncology database applying a very new approach to medical data gathered in this space, who will support a very patient-centric approach and personalized-medicine models.

Tackling the Challenges

Describing the challenges faced in the journey, Limor quoted that even that her target industries are on the verge of revolutionizing, there is still a lot of market education needed and healthcare and life sciences markets are notorious for slow adoption and not moving as fast to other industries.

"This whole data play is still new, she says, and very challenging to most organizations where Big Data technology is not part of their core business"

By slow-moving industry, she implied towards the sheer fact of the slow-moving sales cycle of the industry which is unbearable for the young and small startup. Consequently, to make a deal with a Pharma company or a big operation like a CRO (clinical research organization), it could take from 9 to 18 months before a deal is closed.

To be up to the new RWE standards and be holistic, one has to include the patient perspective. The key to doing so is very challenging (technology-wise) because one needs to take and understand this very complex data coming out of patient lingo /jargon written in an unorganized format (aka unstructured data).

To be personalized one has to add to the mix more dimensions of (traditional) data, like clinical records, research or even regulatory submitting (FDA, for e.g).

Although, all these (tech & data) practices are quite challenging to the healthcare industry, across the board (Drug manufactures, Healthcare providers, Health policymakers, Health payers), Data2Life took this challenge and cracked with its RWE platform.

Aspiring for Evident Future

The company aspires of being the Ground Truth in its respective industry, be synonymous to the gold standard in RWE practice. In her progressive vision, Limor sees that Data2Life will be as impactful in healthcare as similar AI solutions impacted Finance and other industries. Data2Life practice will be a solution embraced which contemporary organizations haven't adopted yet.