Y Combinator: from disease prevention to precision treatment

By April 27, 2016
Y combinator : test sanguin et ADN unis pour lutter contre le cancer

A number of startups working in the health field were rubbing elbows at Y Combinator’s first season of 2016. We bring you a roundup of e-health trends from this crop of fledgling companies.

Among the 127 startups taking part in this year’s first season at Y Combinator, a large number of them – in fact around thirty, which is over 25% of the group – are working in the health field. We observe two main e-health trends among this first YC batch of 2016 – early detection of cancers and infectious diseases and precision medicine to treat them.

Blood sample analysis for early detection

L’Atelier has previously reported on the increasing number of new ventures using blood sample analysis for rapid detection of cancers, including Silicon Valley startup Guardant Health. X-Zell, a graduate of this first 2016 YC programme, has just joined the list. Explains co-founder Sebastian Bhakdi: “Fully 90% of all cancers can be treated successfully if they’re detected early enough”. His startup has developed a method of isolating healthy red blood cells from the presumed cancerous cells in record time. “Rapidly identifying cancerous cells is a difficult task, rather like looking for a needle in a haystack. A 10-milliliter blood sample might perhaps contain ten cancerous cells among 50 billion healthy red blood cells!” points out Bhakdi. Now X-Zell’s patented technology looks set to become an effective complement or even substitute for biopsies which, in addition to running a serious risk of complications, take at least two days and often more to come through with results. The X-Zell solution works as follows: the healthy cells are first removed from the blood sample which will then contain only the cancerous cells. These are then placed on a microscopic slide of the sort that can be found in any laboratory and sent off to a pathologist for examination, as would be the case with biopsy samples or smears for screening. The test costs under $100 and results can be delivered in under a day. Clinical testing conducted by the company in late 2015 achieved 90% accuracy, a highly encouraging result which comes very close to biopsy results.


In addition to detecting cancers, blood sample analysis can also be used to test for infectious diseases. YC graduate Unima has come up with a fast low-cost blood test for HIV and tuberculosis. Current lab tests cost on average $20 in the United States and it takes hours or even days to obtain the results from the lab. Taking this situation as their starting point, the Unima founders have drawn on biotechnology, artificial intelligence and machine learning to create a test for use by health centres which costs less than $1. Their solution delivers results in 15 minutes and Unima founder and CEO Jose Nuno claims an average accuracy of 96%, versus just 75% for current laboratory tests for HIV and tuberculosis. From a practical point of view, nothing could be simpler for healthcare personnel. All they have to do is take a drop of blood and put it on to a diagnostic paper strip impregnated with antibodies which will provoke a chemical reaction in the presence of pathogens. They can then take a picture of the diagnostic strip using the Unima application, which will launch an analysis and return the verdict about ten minutes later. Other infectious diseases such as Dengue fever and influenza are also on Unima’s radar screen; the company is currently carrying out clinical testing in seven US hospitals.

Les trois étapes du test de dépistage du VIH et de la turberculose mis au point par Unima

Unima solution: three-step screening for HIV and tuberculosis

Ultrasound is an alternative to blood sample analysis for early detection of cancers. This technique is used by iSono Health, a San Francisco Bay area startup which has developed a device that women can use at home to detect breast cancers. The statistics are striking. According to the NGO Breastcancer.org, one American woman in eight has a risk of developing breast cancer at some time in her life. Many women have an annual mammogram, but these are by no means infallible As iSono Health co-founder and CEO Maryam Ziaei points out, one in three cancers slips through undetected by this method. The device iSono Health has developed consists of a wearable electronic device which uses patented ultrasound technology. The images it generates are transferred to an imaging platform. As this technique avoids radiation, it can be used every month and only takes two minutes each time. “Fully 99% of all breast cancers can be successfully treated if caught in time (...) Today there are over 50 million American women at risk of developing breast cancer, and they need tools to detect it in time,” argues Maryam Ziaei. The iSono Health wearable is expected to be on the market by 2017.


The iSono Health solution: a wearable device coupled with an imaging platform

Precision treatment based on genome analysis

Alongside the illness prevention and detection solutions, some of this year’s YC graduates are focusing on precision treatment. There are currently many initiatives underway to provide more accurate medical treatments, plus faster and lower-cost care based on genome studies. One example is Perlstein Lab PBC (Public Benefit Corporation) which is rethinking the way researchers discover molecules to combat rare illnesses using a platform based on CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) technology. This allows researchers to edit, replace or inhibit one or more genes very precisely and rapidly. “Today there are about 7,000 illnesses classified as rare and for 95% of them no treatment has been discovered that has received FDA approval. Given the time it currently takes to develop a new molecules it would take us 400 years to find a remedy for all these illnesses,” underlines company founder Ethan Perlstein. His solution is to re-create genetic anomalies identified in a human genome in the genome of laboratory test organisms and animals – yeast, flies, worms and sometimes mice. Perlstein Lab is then able to rapidly test different molecules and identify those which are most effective on living organisms. This contrasts with the approach of the major pharmaceutical companies, which start by conducting experiments on cells cultured in Petri dishes. So PLab, as it is generally known, claims to be able to reduce both the development time and cost of discovering useful new molecules.

Another YC graduate, Loop Genomics, co-founded by three Ph.D students specialising in DNA research, is looking to ‘disrupt’ the development of medicines by providing new technology capable of reading and repairing damaged DNA sequences. There are different reasons why human DNA may be damaged. These causes include UV rays, carcinogenic molecules and DNA copying errors when cells divide. Molecular, i.e. natural, mechanisms are at work every day to stabilise our genetic material. Loop Genomics has set out to provide assistance here. With its technology, which is capable of reading 10,000 DNA letters at a time for the tiny cost of $2 per reading, the startup could well succeed in industrialising DNA reading and repair. Loop Genomics has already signed a $50,000 contract to run a pilot project with Twist Biosciences, one of the leading players in this field. “Twist Biosciences is working on an average of 1,000 DNA sequences a day, which constitutes a $21 billion market for us,” underlined Loop Genomics founder and CEO Tuval Ben-Yehezkel. His company has also entered into a partnership with the University of Los Angeles to work on another application of the technology, early cancer diagnosis.

Blood sample-based testing on the one hand and genome studies on the other are clearly two hot areas for e-health startups and may well be the source of the most exciting progress in early detection and treatment of cancers and rare diseases – fields which definitely seem to be stretching the boundaries of Y Combinator.

Don't miss our articles on this first 2016 season at Y Combinator on the subjects of Robotics and On-demand workers

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