What Can AI Do For Health?

Algorithms help diagnose and treat diseases, discover new drugs and personalize prevention. Thus, the potential of artificial intelligence has been recognized not only by the medtech industry but also by health systems, pharmaceutical companies, patients and even the World Health Organization. What’s the state of AI in healthcare?

The DayOne team facilitates healthcare innovation and collaboration

Talk to us


Gaps in data/information access have many negative consequences: medical errors, delayed diagnoses, rising healthcare costs, low quality of care


In order to fix broken healthcare systems, smart integration of new technologies into the current health ecosystem is needed.

SOLUTION: AI can support this new paradigm shift by accelerating research, reducing the administrative burden on doctors, improving policy-making and enhancing health literacy;
IN PRACTICE: Developing trustworthy AI/ML algorithms that meet the needs of patients/healthcare workers requires close collaboration between science and business as well as adequate funding.

In 2009, Hiroshi Kobayashi, a scientist from the Tokyo University of Science, presented the world’s first robotic teacher Saya. According to Kobayashi, machines are better than human teachers. The AI-powered robot knows the answers to all questions – it monitors and analyzes childs’ behavior to individualize the learning process and support their hidden talents.

This utopian vision of education has a lot to do with healthcare. Of course, nobody would like to be treated by artificial intelligence wearing a doctor’s coat – like no parent would prefer a robot over a human teacher. Human social empathy cannot be replaced by a rational machine. However, a lack of data causes medical errors, delays diagnosis and worsens the treatment prognosis. Humans make irrational health decisions, getting lost in conflicting recommendations and random advice.

AI’s capabilities to memorize the medical records of millions of patients, analyze data, monitor, forecast and make decisions based on facts are now becoming a critical transformational power in medicine.

Impact of AI in healthcare. New Challenges require contemporary approaches

Doctors are drowning in administrative tasks, and the patient’s journey through the system is like a labyrinth. Healthcare professionals waste up to 1/3 of their time on administrative tasks. While WHO forecasts a shortage of 9.9 million doctors, nurses and midwives by 2030, such a waste of medical staff resources cannot be afforded.

There are many more statistics showing that healthcare needs radical changes: approx. 250,000-440,000 people die each year in the US due to medical errors. This is the third cause of death, right after cancer and cardiovascular disease. Cancer treatment delayed by one month increases the risk of death by approx. 10%. Non-communicable diseases generate 80% of healthcare costs. Paradoxically, 80% of heart conditions, heart attacks and diabetes can be prevented by modifications in lifestyle.

AI is a necessity, not just an addition to healthcare. Imagine the scale of the benefits when algorithms start reducing the number of medical errors by analyzing patient data and comparing treatment scenarios with the outcomes of millions of other people, relieving doctors of paperwork by automatically sorting information and collecting data in electronic records with voice processing systems.

How medicine, life sciences, healthcare professionals and patients benefit from AI

Released in September 2021 by the US Food & Drug Administration (FDA), the list of AI/ML-based (artificial intelligence/machine learning) medical devices already includes 343 items. By 2016, there were 15 items on the list. The largest number of medical algorithms certified by the FDA in the USA and CE-marked in Europe go to radiology. It is followed by cardiology, hematology, and neurology.

The advancement of digital and AI technologies in healthcare has led to a rapid increase in research in the field of AI and ML. So much so that in 2019, the prestigious scientific magazine The Lancet decided to release a separate version devoted solely to digitization – The Lancet Digital Health.

Scientists from around the world publish research on (among others) the effectiveness of algorithms in healthcare (e.g., the one from April 2022 confirming the reduction in the incidence of colorectal cancer in the case of colonoscopy using AI tools.

Such a rapid development of algorithms is a logical consequence of the digitization of healthcare, cultural changes, and favorable legislative solutions. Systematically developed IT architecture in healthcare facilities and digitization of patient files facilitate the exchange and re-use of data by research centers and commercial companies.

Yet, it is no longer about advances in medicine – the competitiveness of the future economies will be measured by the scale of innovation and digitization maturity. The European Commission is aware of this and, at the beginning of May 2022, presented the European Health Data Space project. EHDS is intended to facilitate the secondary use of data, including supporting research and health policy goals.

The potential of AI in life sciences is being recognized by the pharmaceutical industry. Pharma leaders are working with startups developing so-called ‘digital therapeutics’ – platforms and mobile applications supporting patients in managing chronic diseases.

“AI will bring the most significant benefit to patients and doctors by becoming the new member of the medical team. Automated solutions will assist physicians in medical decision-making, interpret radiology images and treatment plans, and even take over repetitive tasks. AI will help analyze a vast amount of patient data collected by health sensors, wearables and direct-to-consumer tests. In the future, patients will provide insights from AI-supported systems to their doctors. It will further facilitate their relationship with caregivers.”

Damien EvéquozCo-founder and Scientist at Alpha Anomeric

The range of potential applications is much broad. Novartis has partnered with a Chinese technology giant to develop AI Nurse – an intelligent platform that supports patients, doctors and nurses in managing heart disease. The program covered 500 hospitals. BioNTech, known for developing an mRNA vaccine for COVID-19, recently announced a multi-year partnership with InstaDeep Ltd., aiming to apply the latest advances in artificial intelligence and machine learning technologies to develop new immunotherapies for cancer and infectious diseases. And recently, Fujitsu has begun research to develop AI for early pancreatic cancer detection in Japan.

Big tech companies are also eager to enter the healthcare market. Alphabet, Google’s parent company, announced the launch of Isomorphic Laboratories in November 2021. The company aims to introduce an “AI-driven approach” to bio-pharmacy research by becoming a commercial partner for drug manufacturers.

Last but not least, public health has started to explore the power of AI. As a result of the COVID-19 pandemic, the WHO created the Hub for Pandemic and Epidemic Intelligence. By using AI to analyze health data, the WHO wants to prevent and limit future pandemics.

The gradual adaptation of AI by health and pharma organizations is an opportunity for digital health startups. Healthcare facilities are increasingly open to co-developing and implementing innovative solutions. Patients are also eager to use modern mobile apps to manage chronic diseases or optimize their lifestyles to stay healthy.

same as above

Before the technological revolution gains momentum, some AI-related challenges must be tackled.

One of them is a low quality and limited availability of data used to train the algorithms. There are legitimate concerns about bias in data sets, which could lead to algorithms failing in populations not represented in the practice data—the so-called ‘black box’ (i.e., the way algorithms make decisions). Nobody knows how AI makes decisions, so it isn’t easy to verify the correctness of the entire process.

Citizens have concerns about data security and privacy. The use of diagnostic algorithms that are cheaper than human labor can potentially lead to two-speed healthcare, where diagnostic services provided by bots will be the standard, while contact with a human doctor will become a premium option, available beyond standard health insurance.

Doctors look at AI-based health systems with hope but fear. There are ethical dilemmas regarding professional liability for medical errors caused by algorithms. A mistake by an AI system suggesting the purchase of new clothes, a book or displaying the most exciting content on social media has no such consequences as an incorrect diagnosis or imprecise selection of a drug. Imagine such a bug in mobile apps used by millions of patients.

The legislation does not keep up with the rapid development of technology – many potentially beneficial solutions for patients are not scaled up on the market because health insurers do not reimburse them. However, this is also changing. In 2019, Germany adopted a new law that allows doctors to prescribe certified apps to their patients. Now France will implement a similar legislative framework.

The adoption of new technologies also requires a change in the work culture in healthcare. The case of IBM’s Watson Health proves that we are still far from balanced cooperation between doctors and AI. Neither the technology nor the doctors were ready. As a result, Watson Health was accused of making inaccurate and unsafe recommendations, prompting many hospitals to sever their cooperation with Watson. IBM eventually sold Watson Health.

AI advances will be strongly related to advances in hardware. Solutions enabling the processing of large data sets and the detection of correlations in data invisible to the human eye (or rather, traditional statistics) have only become popular in the last decade. We are talking about so-called ‘deep learning/machine learning’ (DL/ML). And although the history of neural networks dates back to 1943, DL/AM entered practical use in this century. AI needs not only data, but also computing power. And this – according to Moore’s Law – grows exponentially: the number of transistors on a single microchip doubles every two years.

Yet, another innovation will fuel the development of AI – quantum computers with computational power incomparably higher than traditional computers. Google says its laboratory version of a quantum computer is 100 million times faster than any classic computer. Its performance can be compared to the strength of 5 million laptops. In tests, Google’s 54-qubit computer was able to complete a task in 200 seconds that would take over 10,000 years on traditional computers. Such machines can speed up, hundreds or thousands of times, the time it takes for AI systems to search for new molecules for potential drugs.

In 2017, a Chinese AI-based robot passed a medical exam. But even in China, with ambitions to become an AI leader by 2030, robots have yet to replace doctors. Instead, they support them. And one group will benefit most: patients.

Advances in healthcare and life sciences need a favorable ecosystem that fosters collaboration and supports the most brilliant ideas of young entrepreneurs. One place where these growth drivers can be found in Europe’s leading healthcare and life sciences hub is the Basel Area – a hotspot for progress in life sciences and medicine.

The people, culture of inventiveness, and location make it an excellent place to co-shape the future of healthcare. Based in Basel (Switzerland), it’s within walking distance from leading pharma companies working on breakthroughs in life sciences and – for a few years – also applying AI across their value chain. Here, Novartis cooperates with Microsoft within AI Innovation Lab, IBM plans a new center for quantum computing, while numerous international startups find symbiosis with the local supportive environment for entrepreneurship.

“AI will bring the most significant benefit to patients and doctors by becoming the new member of the medical team. Automated solutions will assist physicians in medical decision-making, interpret radiology images and treatment plans, and even take over repetitive tasks. AI will help analyze a vast amount of patient data collected by health sensors, wearables and direct-to-consumer tests. In the future, patients will provide insights from AI-supported systems to their doctors. It will further facilitate their relationship with caregivers.”

Damien EvéquozCo-founder and Scientist at Alpha Anomeric

The future, AI-driven healthcare starts from ideas that can grow in the right ecosystem. The DayOne initiative represents a great example of the need to invest in ecosystem activators to achieve healthcare transformation.

One example is Zoundream which uses AI to monitor baby cries to identify infants’ needs, emotions, well-being, and physical and neurological status. Another of its companies, Rekonas, has developed AI for EGG analysis to assess brain health, current, future cognition, and sleep macro/micro-structure. Or Nutrix, which applies AI to analyze molecules and biomarkers in saliva samples for health monitoring.

Do you have a question? Get in touch

Private and shared labs

Research in the realm of biology, chemistry, or biotechnology often starts at the university laboratory. But as soon as research turns into a business, the university lab will not be sufficient anymore.

Startup founders will need to look for a laboratory to verify their findings. Let’s assume as a startup founder you are not blessed with tons of money. Your income is meager as you are still proving your science to potential investors. Buying lab space and equipping it on your own is out of the question.

Why? Because equipping a laboratory can prove to be very costly, especially if you need top-of-the-line analytical equipment. Not to mention high instrument maintenance costs or finding a suitable location that meets the legal restrictions for laboratories. Hold that thought for a later point in time.
For now, let’s focus on renting lab space. There are two different categories of lab space:

Private labs

You and your team are working alone in a private lab, and you use it on your own terms – you also need to buy the equipment by yourself. It usually is more expensive than a shared lab as you need to invest first before you can start working.

Shared labs

Several research teams share a lab. Some, but not all shared laboratories also provide and share the instruments. Rent is usually less expensive than for private lab space.

When should you rent a private science lab?

There are some reasons to consider renting a private lab for exclusive use:

  • Your expectations regarding confidentiality are high.
  • You work with dangerous chemicals like nitroglycerine.
  • You need animal facilities.
  • You need more than 100 square meters for your science and have special machine requirements.
  • You need a cold room and a dark room.
  • You start with more than six laboratory workers.
  • You need lots of storage for your samples.

In this case, the best decision would be a private lab.

Find out if sharing a laboratory with other individuals and teams is the way to go. Ready?

A guide to find out if you should consider renting a shared lab.

Your funds are limited.

That’s the way things are for most startups. This is why some shared labs offer the benefit of using some very expensive infrastructure together. That way, you don’t need to buy everything on your own. Facilities that cater to startups often rent infrastructure at affordable rates.

You are an organized and thorough person.

While this should be a given for people working in the lab, these skills are even more important when you share a work environment with others. Landlords and other teams expect you to book slots in the lab or the office space and to clean up after use.

Working in an environment with like-minded people suits you.

Good news! There’s no way to avoid running into the other teams. They most likely face similar challenges. Working in a shared lab is not that different from working at a university lab so transitioning from university to a shared laboratory should be smooth.

You want to spend your precious time working – not maintaining sensitive and costly infrastructure.

That’s probably the best part: You can, and you should focus on your science. Safety installations, waste management, infrastructure maintenance, – it’s all taken care of in a shared laboratory.

Alpha Anomeric is focusing on developing therapies for Duchenne muscular dystrophy. The disease causes muscle loss and shortens life expectancy.

But wait, what if you’d only stay for a limited time because your startup grows and you need a bigger lab for more people?

Shared labs often cater to teams and projects who are just starting. You start small, you grow, you leave for a private lab – that’s how it should be. That is also the reason why leases are quite flexible in a shared lab and tenants can choose lease periods that suit their needs.

Do you want to use certain instruments for only two weeks? In some laboratories, this is possible, e.g. at the Switzerland Innovation Park Basel Area in Allschwil.

We are here when companies start. I am always happy when they become too successful for the shared facilities and move into a bigger private lab.

Luigi SolinesManager Laboratory, and Facilities at Switzerland Innovation Park Basel Area

What about privacy? How do you protect your IP in a shared lab?

If you have been part of an academic group at a university lab before, communication hygiene between members of different groups is known to you. Protecting intellectual property is not an issue at all as long as teams follow the basic rules of laboratory communication.

Labs of the Basel Area

Research in Europe’s life sciences hub

As a researcher in biology, chemistry, or biotechnology, your natural habitat is the laboratory. Fume hoods, dry rooms, benches with vials, and colleagues in white coats – that’s your turf. But where do you want that work environment to be?

All over Switzerland, you will find laboratories for rent. However, if you are in biotech, no place matches the Basel Area, home of Novartis, Roche, Johnson&Johnson, Idorsia… We cannot even name all of the exciting established companies that are active in the region.

Partners for laboratory workers: from ten23 health to Lonza and SKAN

Startups are equally drawn to the Basel Area. Not only do they find suitable labs for their research, but also interesting partners, and service providers specialized in delivering drugs. Among the service providers in the Basel Area is SpiroChem. The CRO SpiroChem offers chemistry solutions for life science companies.

Ten23 health in Basel acts as a CDMO. They are specialized in injectables. And you surely know Lonza, the company that manufactures the Moderna vaccine. The manufacturer produces big and small molecules and plays an important role in the production of pharmaceuticals in the region and beyond.

Probably, you will also come across instruments from SKAN: The company is based in Allschwil. They are a global market leader for isolators and cleanroom devices. If you produce biopharmaceutical substances, your facilities are most likely outfitted with SKAN infrastructure.

From lab project to funding

Startups also find funding: Biotech startup Cimeio received 46 million francs in funding, Engimmune acquired 16.7 million US dollars in 2022, and Anaveon raised 110 million francs in 2021 to pursue their research.

To make things even better, one of the best established/most relevant biotech programs in Europe is located here: BaseLaunch has helped numerous projects launch and grow their business and get funding since 2016. Nine of their portfolio companies raised 450 million dollars from venture funds in Switzerland and the US.

If you are a biotech startup or wish to become one, apply now. If you are a match, you will get coaching but you will also get access to fully equipped labs in the Switzerland Innovation Park Basel Area at its site in Allschwil.

Application cycle is now open!

The next deadline for 2022 is September 1st.

Renting your science lab in the Basel Area

In Switzerland, safety levels for biology labs are defined with BSL – biology lab level. To work with cell cultures, you need BSL 2. In the Basel Area, most bio labs are accredited for BSL 1 or BSL 2.

There are also differences in the equipment and in the services that are on offer. “Shared lab” can signify that you share a certified lab fitted with workbenches and bio hoods. Whatever equipment you need, you have to bring yourself. Others, like the shared labs at the Allschwil site of Switzerland Innovation Park Basel Area, come fully equipped with all necessary instruments. Let’s take a closer look at some labs in the Basel Area.

Fully equipped labs at Switzerland Innovation Park Basel Area

Some of the science lab equipment that comes with the shared biology lab at Switzerland Innovation Park Basel Area, site Allschwil:

  • Biohood
  • Cold storage with -20 C and -80 C freezer
  • Centrifuges
  • Rotors
  • Mixers
  • PCR machines
  • Glassware
  • Glassware washer
  • HPLC
  • Image systems
  • Fluorescent absorbance plate

Teams can also use the working stations to note down their findings. There are more fixed and flex desks in the open coworking space.

Luigi Solines, Manager Laboratory and Facilities at Switzerland Innovation Park Basel Area, helps teams to accommodate in the labs. He is also responsible for the supply of usables and takes care of the waste management and the CO 2 supply. If a problem with the infrastructure occurs, he takes care of it.

Need help with finding lab space? Talk to us.

We’re the go-to agency for every question or request about launching in or relocating to the Basel Area. Either we know the answer, or we know the people who do. We help you solve questions about commercial real estate and lab space.

Fabio MarelliManager Business Affairs at Basel Area Business & Innovation

Lucky for the teams working on-site, Luigi’s love for machines runs deep, and he is eager to help when a plate reader doesn’t work properly. He also makes room for the instruments that the teams want to bring in addition to the existing equipment.

Luigi also knows suppliers of secondhand infrastructure if teams require special instruments at a reduced price.

Switzerland Innovation Park Basel Area will move to a new building in 2022. Tenants can choose between shared and private labs at the Main Campus in Allschwil. They also can rent fix or flex desks in the coworking zone.

Monthly rates for the shared labs start at 2300 francs per person.

We offer all the instruments your team needs - and more.

Luigi SolinesManager Laboratory, and Facilities at Switzerland Innovation Park Basel Area

Switzerland Innovation Park Basel Area, Main Campus Allschwil

Technologiepark Basel: ideal for biotechnology startups

In Basel, close to all the life sciences action, Technologiepark Basel rents labs to startups. Lab spaces start from 42 square meters. You can rent private labs but shared infrastructure is also available, like autoclaves, ice machines, water purifiers, centrifuges and incubators. Good to know for biotech startups with high lab rent: Ask the Economic Development Unit of the canton of Basel-Stadt for rent allowance.

Among the tenants at Technologiepark Basel are Anaveon, Cimeio, and NBE Therapeutics. Medtech company Artidis and biotech Cellestia are also at home at Technologiepark Basel.

Keep an eye out for Superlab Suisse

Superlab Suisse has announced to open its labs in Basel in 2024. The company offers labs-as-a-service. After opening labs in Lausanne and Zurich, Basel will be outfitted with lab and research space. The labs will be opened at Stücki Park in Basel.

The 5th Floor CO.LAB in Muttenz

The Fifth Floor in Muttenz offers coworking spaces – but also spaces in the shared lab that can be rented on a monthly or an an annual basis. A space in the chemistry lab that includes two work stations starts at 3500 francs per month. 2 research stations in the biology lab are available for 5000 francs per months. Laboratory equipment can be rented, access to the coworking space is included.

If you would like to know more about laboratories in the Basel Area, download our guide. We introduce you to 16 facilities. The lab guide is updated every year.

Lab Facilities Guide

We took up our work at the Allschwil site of the Switzerland Innovation Park Basel Area with a small team and expanded within five months to the full team size. Basel Area Business & Innovation helped us to settle and find a starting setup with lab and office space. The team supported us greatly with bigger lab space and more office capacity to facilitate our growth.

Jörg BreitlingTeam Leader Application biological Qualification Hamilton

Sign up to receive our newsletter in your inbox.

You might also be interested in

Read the article "What Can AI Do For Health?"

Algorithms help diagnose and treat diseases, discover new drugs and personalize prevention. But what are the problems, challenges, benefits and solutions to the current state of AI in healthcare? 


Read our article “What Can AI Do For Health?” to find the answers to these questions and discover some of DayOne’s ecosystem players and Accelerator Alumni: Zoundream AG, Rekonas and Nutrix. 

AI will bring the most significant benefit to patients and doctors by becoming the new member of the medical team. Automated solutions will assist physicians in medical decision-making, interpret radiology images and treatment plans, and even take over repetitive tasks. AI will help analyze a vast amount of patient data collected by health sensors, wearables and direct-to-consumer tests. In the future, patients will provide insights from AI-supported systems to their doctors. It will further facilitate their relationship with caregivers.” said Bertalan Meskó, MD, PhD from The Medical Futurist Institute.

There is space for improvement in what AI-enabled clinical decision support systems can provide to doctors for an early and correct diagnosis of diseases with overlapping symptoms. Tools that will succeed in integrating real-world data with clinical parameters and molecular profiles, leveraging AI for multi-dimensional data analysis, might significantly impact the definition of personalized medicine.” said Enkelejda Miho, Professor of Digital Life Sciences at FHNW University


Read the full article right here: “What Can AI Do For Health?

Ready for Acceleration?

Your first step to applying to our DayOne Accelerator with its 3 verticals starts here! We are looking forward to receiving your application!
Apply now!

Do you have a question? Get in touch