Skip to main content

Mendel raises $18M to tease out data structure from medicine’s disparate document trove

The medical industry is sitting on a huge trove of data, but in many cases it can be a challenge to realize the value of it because that data is unstructured and in disparate places. Today, a startup called Mendel, which has built an AI platform both to ingest and bring order to that body […]

The medical industry is sitting on a huge trove of data, but in many cases it can be a challenge to realize the value of it because that data is unstructured and in disparate places.

Today, a startup called Mendel, which has built an AI platform both to ingest and bring order to that body of information, is announcing $18 million in funding to continue its growth and to build out what it describes as a “clinical data marketplace” for people not just to organize, but also to share and exchange that data for research purposes. It’s also going to be using the funding to hire more talent — technical and support — for its two offices, in San Jose, CA and Cairo, Egypt.

The Series A round is being led by DCM, with OliveTree and MTVLP, and previous backers Launch Capital, SOSV, Bootstrap Labs and Chairman of UCSF Health Hub Mark Goldstein also participating.

The funding comes on the heels of what Mendel says is a surge of interest among research and pharmaceutical companies in sourcing better data to gain a better understanding of longer-term patient care and progress, in particular across wider groups of users, not just at a time when it has been more challenging to observe people and run trials, but in light of the understanding that using AI to leverage much bigger data sets can produce better insights.

This can be important, for example, in proactive identifying symptoms of particular ailments or the pathology of a disease, but also recurring and more typical responses to specific treatment courses.

We previously wrote about Mendel back in 2017 when the company had received a seed round of $2 million to better match cancer patients with the various clinical trials that are regularly being run: the idea was that certain trials address specific types of cancers and types of patients, and those who are willing to try newer approaches will be better or worse suited to each of these.

It turned out, however, that Mendel discovered a problem in the data that it would have needed to enable its matching algorithms to work, said Dr. Karim Galil, Mendel’s CEO and founder.

“As we were trying to build the trial business, we discovered a more basic problem that hadn’t been solved,” he said in an interview. “It was the reading and understanding medical records of a patient. If you can’t do that you can’t do trial matching.”

So the startup decided to become an R&D shop for at least three years to solve that problem before doing anything with trials, he continued.

Although there are today many AI companies that are parsing unstructured information in order to extract better insights, Mendel is what you might think of as part of the guard of tech companies that are building out specific AI knowledge bases for distinct verticals or areas of expertise. (Another example from another vertical is Eigen, working in the legal and finance industries, while Google’s DeepMind is another major AI player looking at ways of better harnessing data in the sphere of medicine.)

The issue of “reading” natural language is more nuanced than you might think in the world of medicine. Gali compared it to the phrase “I’m going to leave you” in English, which could just as easily mean someone is departing, say, a room, as someone is walking out of a relationship. The “true” answer — and as we humans know even truth can be elusive — can only start to be found in the context.

The same goes for doctors and their observation notes, Galil said. “There is a lot hidden between the lines, and problems can be specific to a person,” or to a situation.

That has proven to be a lucrative area to tackle.

Mendel uses a mix of computer vision and natural language processing built by teams with extensive experience in both clinical environments and in building AI algorithms and currently provides tools to automate clinical data abstraction, OCR, special tools to redact and remove personal identifiable information automatically to share records, search engines to search clinical data, and — yes — an engine to enable better matching of people to clinical trials. Customers include pharmaceutical and life science companies, real-world data and real-world evidence (RWD and RWE) providers and research groups.

And to underscore just how much there is still left to do in the world of medicine, along with this funding round, Mendel is announcing a partnership with eFax, an online faxing solution used by a huge number of healthcare providers. Faxing is totally antiquated in some parts of the world now — I’m not even sure that people the age of my children (tweens) even know what a “fax” is — but they remain one of the most-used ways to transfer documents and information between people in the worlds of healthcare and medicine, with 90% of the industry using them today. The partnership with Mendel will mean that those eFaxes will now be “read” and digitized and ingested into wider platforms to tap that data in a more useful way.

“There is huge potential for the global healthcare industry to leverage AI,” said Mendel board member and partner at DCM, Kyle Lui, in a statement. “Mendel has created a unique and seamless solution for healthcare organizations to automatically make sense of their clinical data using AI. We look forward to continuing to work with the team on this next stage of growth.”

Data & News supplied by www.cloudquote.io
Stock quotes supplied by Barchart
Quotes delayed at least 20 minutes.
By accessing this page, you agree to the following
Privacy Policy and Terms and Conditions.