Wednesday, July 26, 2017

Brain in engineering schools

Teaching life sciences in engineering schools has become more and more common in these last years. Indeed, medicine and technology are deeply correlated. With these two disciplines quickly evolving, this relationship is getting even stronger. Among the thousands of possibilities from this collaboration, neurology receives a special attention due to brain’s complexity and its essential role in the human body.


The brain is a central organ that controls functions, movements, sensations and thoughts. This results from the millions of simple mechanisms occurring every second in a biological body. This complexity has always attracted engineers and has sometimes created passion. With the evolution of medical treatments, the study of brain - from a technical point of view - becomes extremely relevant.


Technology has so much to give to the medical sector but the reverse is also true! Medical imaging to better understand the internal structures, or neuronal connections to inspire machine learning, electronic devices to trigger body reactions and movements, and biological bodily reactions applied to sensors for product detection… The list is not exhaustive and the collaboration is starting just now.


In this article, I will describe one of the most relevant collaborations between medicine and technology in neurology and I hope to convince you that innovation is not possible without gathering knowledge from many sciences.


During my masters, I had the chance to spend one year at EPFL (Swiss Federal Institute of Technology in Lausanne), an advanced school of engineering in Switzerland. They have dedicated an entire faculty to the relationship between life sciences and technology and have a particularly high proportion of their work linked to the local hospital, CHUV.
There, I have discovered efficient research. The finances are never really a problem, which gave me the opportunity to work on one of the best MRI machines in Europe, on very interesting projects involving image analysis in a top lab, in addition to meeting famous genius professors from all over the world.


On top of that, they host an important European collaboration called the Blue Brain Project.
The project aims to build a biologically-consistent computer model of the human brain and focuses on understanding the structure and the functions of this important organ. Following the founder of the project, Prof. Markram, “more than 35 000 articles are published every year but a researcher can only read about 100 per year”. The project has the ambition of integrating - in one model - the knowledge that is currently spread all over the world.


It all started in 2005 when a researcher from EPFL convinced IBM to create the project with a team of 35 biologists, physicists, mathematicians and programmers that quickly became dozens of partners from many institutions. Three years later, they had been able to reproduce the behavior of 10000 neurons and connected to more than 30 million of synapses by studying tissues slices, electrical records, and brain images.


Brain fibers.png
Figure 1: Brain network


In 2013, a second project was created, the Human Brain Project, to specifically focus on humans, where there were multiple objectives to be achieved. First is studying the function and structure of the brain from different levels and perspectives. Second is to create a platform to test digital models of diseases and improving diagnosis. The final goal is the application of the new knowledge on this structure to information and communication technologies.
The group expects innovations in energetic efficiency management, improvements of the reliability of the code and the machine, and more complex and efficient programming procedures.


Nevertheless, Human Brain Project project is not approved by all in the scientific community. Some people point out the waste of money – €1 billion – for a project that may not achieve the fixed goals.
At the launch of the second project in 2013, the opponents criticized the lack of results from the first project and its scientific strategy. Markram responded to these attacks by publishing two years after an article in Cell where he described the simulation of the rat brain. This almost immediately quashed the multiple rumors and critics on the project’s ethics.


The evolution and success of such project rely mainly on multidisciplinary teams, and the integration of engineers in scientific developments. On one hand, engineers provide the capability to adapt to situations, to find solutions, and to implement them. On the other hand, scientists bring their deep knowledge on the subject and their capability to understand and discover new mechanisms.
More and more, the synergy between the biologists, medical doctors, and engineers becomes crucial to achieve the ambitious objective of solving the mysteries of human brain.   

Tuesday, July 4, 2017

It has been four years

In the beginning of 2013, when I finished my bachelor in electrical engineering with a specialization in image processing, we were in the middle of the “app boom”. The market was getting overwhelmed with apps and companies were investing a lot of resources, so it was a good opportunity at the time in order to quickly find a job. A friend of mine in the university was learning how to program apps and I joined him in the computer lab of the university for several afternoons to get acknowledged with the new SDKs. I was very excited and had (too) many ideas, but then it happened: I got stuck, I could not get things done, time passed and the excitement went away. I needed something for long term so, in the meantime, I was learning and experimenting with python. And I kept doing that for long time.


The chosen one

Interviews came and went but I could not see myself in a big consultant company. “It is what everybody is doing”. I felt awkward and not sufficiently motivated.

After a break in the search of my destiny at the university cafeteria, I went to see a grant presentation which offered working in a startup. They were a startup incubator growing different small companies from the emerging smart-IT sector. When the talks finished, they put an exam in front of me. The exam was about mobile apps! I smirked. On the other hand, that was really not my thing. Anyway, I went for it.

A week after, I started to do interviews with the different startups. There were a dozen, but I could have stopped right in the second one. Most of them were offering a job for web development (frontend, backend), app development or marketing. Their ideas were good and innovative but, in general, the job I was going to perform in each would have been the same. The challenge, let’s say, was not different. Probably I would get bored after three months. However, in the second interview, I was asked to produce a map of connectivity of the brain, a thing called connectome, and to visualize it in 3D using MRI scans. How could I say no to that?

Brainiac


Copyright: drawmatthewdraw

It has been four years since that day. I found myself sprouting out as a professional inside a startup without even realizing, like learning how to survive in a jungle or finding the way out of a maze. It has a really fast learning and growing cycle, and you get to face problems by yourself and find your way out as you can. And that is basically the challenge: dance to the startup beat.

Uncertainty, reasoning, flexibility, and rapidness were some of the skills I developed in the early days. I was writing all sort of scripts for brain image processing and getting familiar with the newest open source tools. With no one to review the code or help in its testing, it was quite challenging to build that complex pipeline system myself.

We are now more than six people working with the same code and it has changed a lot. With all the experience gathered through the years, thanks to the team-work and solving problems with strange datasets, now, the pipelines are more robust and have a better structure. When you want to show something that only you could understand, that existed only in your mind, you have to strive and brake it down into little pieces, so other people can arrange them together in a way that they can read and understand.

Beginnings are hard, but as you keep moving on and try your best, you will grow. And whatever you do will improve.


Tuesday, June 20, 2017

Marketing in Healthcare: a rewarding challenge



I’ve experienced first hand that it is very difficult to do marketing in healthcare, especially for an innovative or disruptive product of a startup. 

And why is that the case? There are two sides to be analyzed for this case: first the product being in healthcare, then it being a creation of a startup.

Healthcare marketing is not at all like marketing an FMCG product, for instance a lipstick. Generally what they do is just mass market it to almost all women by choosing a brand ambassador (someone very famous and beautiful of course), and share the ads everywhere, from magazines to Instagram.
Now I imagine us doing that, for instance working with Candice Swanepoel, shooting a video with her while she uses our state-of-the-art platform to visualize 3D brains and checking the regions of interest around a tumor: a) I’m not sure if she would actually accept it, b) I’m sure our current customers would be very upset, c) It would be impossible for us to reach our targets with this kind of mass marketing.

Healthcare Marketing: Traditional? Maybe not.


So what do we do in healthcare? We follow trends and customers. The two leading trends are: aging population and rise of medical data - and all issues related to that.

The demographics of different countries, especially in the EU, demand solutions for the aging population and the most recurrent diseases they suffer from. One of the most critical areas here is neuroscience as millions of elderly suffer from burdensome diseases like Alzheimer’s and the bottom line is billions of euros for the healthcare systems.

On the other side, we have a rapidly rising amount of medical data. Customers demand more insight from this data, thus turn to “big data”. The analysis of medical data is critical to, for example, see which treatments are the most effective for specific conditions, and of course, to reduce costs.

A critical issue related to this is of course the security of this data - protected health information. There is still not a widely-used, simple, and secure way to share data among parties. Rigorous regulations have to be followed, which comes with a high cost of compliance. Investigators know that it is vital to have all the data in one place to efficiently run big data analytics as big data is potentially very powerful to resolve the problems of diagnosis and prognosis thus crave for solutions.

Another vital issue in healthcare is that what you do has an actual impact on patients’ and prospective patients’ life. You are contributing to making their lives healthier and better. But what is involved is their health! So you cannot just -  in our case - say: “Use our platform, it’s 3 in 1.”, it’s not a shampoo.

It’s a medical device. Thus, the product at hand is extremely technical and complex. Nevertheless, as the marketer, you have to be as concise as possible while communicating all the necessary information so your targets can easily grasp its value.

To wrap-up, healthcare marketing is not traditional.
It’s more personal thus requires you to share informative and educating content on the problem itself.
Providing accurate and transparent information on the product and its benefits via scientific content like white papers, articles, and video tutorials is key.
You engage and build relationships with different stakeholders to understand them and better respond to their needs. You build a network, a community.
It is dire to present substantial value and clearly communicate how this value is critical in overcoming your customer’s problem.
Easy, right? No, not at all.

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Nevertheless, up for the challenge, all the healthcare problems above and more have pushed our co-founders to transform their expert knowledge into a marketable product. They have created a secure and privacy-regulations-compliant cloud platform to aggregate and analyze imaging and related data in the field of neuroscience.

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Startup Marketing: Why so difficult?


So now, we run into the issue that we have a startup at hand. How do we overcome the barriers and successfully market an innovative solution?
To be honest, it has been and still is a trial and error process for us, as is for most startups.

On one hand there is the economic aspect as funds are limited. It is expected that the impact is higher with less investment - a higher ROI. As a tech company, you incorporate as much digital practices as you can to be efficient while not drifting away from your focus and reaching your niche targets.

In our case, the targets are forward-thinking researchers and doctors in the field of neuroscience and pharmaceutical investigators. You cannot just run into these guys, they are very busy - either saving lives or conducting research to save more lives - and they don’t trust new technologies.

Thus, what you do first is to build a consistent and strong brand image.
You raise awareness to the problem and your existence while clearly communicating your value proposition to help and support them; in our case, how big data analytics and image processing offers invaluable insight to them.
A very engaging content-based marketing strategy helps.
Listening to your customers, hearing about their issues is vital to understand them and their decision-making, and also to adapt yourself.
You then try to figure out what are the best channels to reach them and share different & targeted content for each segment.
Nope, not easy at all…

So why do we do it?


Why go through all this trouble?
The reward is that your solution reaches those that need it the most.
For us - indirectly, we will help save millions of lives if our customers find a cure to devastating diseases with the help of our product.
It’s worth it.

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You can support our efforts by canalizing your projects to our platform.
  

Monday, June 12, 2017

The neuroimaging industry goes open - My experience in ODINE

ODINE promotes the use of Open data



Mint Labs completed the ODINE (Open Data Incubator Europe) program, a startup acceleration program with €100,000 grant to promote the use of open data. (Ref: Mapping the brain with open data). Open data can be freely used and redistributed by anyone. There are many examples of open data, such as geography, public transformation, corporate registration and so on. The data is beneficial for scientists and companies to get detailed insights. Also, the data becomes transparent because the data owner and users are careful to keep the data quality, security and privacy.

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Reference: Pixabay

Big data in Neuroscience



As Marc Andreessen famously said that “software is eating the world.”, I would say “Big data is eating the Neuroimaging industry”. IBM researchers estimate that medical images account for 90% of all medical data and they are the largest and fastest-growing data source in the healthcare industry. (Ref: IBM Unveils Watson-Powered Imaging Solutions at RSNA) The research on mining the medical data to get a better diagnosis or find a biomarker for brain disease has been a hot topic in the Neuroimaging industry.

A lot of Neuroimaging data has been shared publicly

A lot of Neuroimaging datasets are published to the scientific community as Open data including Human connectome project, ADNI, ADHD-200 among others. There are some reasons for this trend. First, Neuroimaging studies need a huge cost because MRI machines need a huge budget to install and maintain and patient selections are very difficult for a specific stage of brain diseases. The acquired medical images are quite beneficial for scientists. Second, openly shared data tend to be more accurate and have more statistical power. (Ref: A Practical Guide for Improving Transparency and Reproducibility in Neuroimaging Research). It improves reproducibility of Neuroimaging researches.

Workflow creates additional value compared to original data source

The ODINE program was a great opportunity to encourage us to work on Open data. My personal favourite activity was an interview with other matured Open data companies from different industries; Unigraph, Viomedo and OpenCorporates, . We learned from them about how to aggregate data and how to build their business. The most critical part of their business model is “added value” to users. The value added features include workflow, user interface and visualization, which drive users to visit their services rather than original Open data sources.

After completing the ODINE program, we continue to build our Open data business model by collecting more Open data and develop more features to take advantage the massive amount of Neuroimaging data. I am excited about showing it to the community soon.

Wednesday, December 14, 2016

A bully's brain: new research on the maladaptive reward system

Once thought to be a rite of passage when coming-of-age, bullying has come under the scrutiny of researchers, policy makers, educators, and parents as concerns rise over the long-term effects of a bullied brain.

While the neurological effects of the bullied brain have been studied extensively, less is known about the neurological cohorts of a bully's brain. New research published by Mount Sinai's Icahn School of Medicine in New York is attempting to find the neural correlates of bullying behavior.

Aggressive and violent behaviors are thought to be linked to inappropriate activation of the brain's reward systems when exposed to aggressive stimuli. The ventromedial hypothalamus, amygdala, and limbic system are involved in initiating aggressive behaviors, but little is known about the mechanisms behind the motivation to perform aggressive or violent acts, such as bullying.