As life expectancy increases, an ever-growing number of people are in need of healthcare. This is pushing healthcare resources and infrastructures to their limit, which is putting our social system and health insurers under tremendous pressure. The gap between rich and poor is growing bigger and bigger, and we need to ensure that everyone has access to health care. The global pandemic that has placed unparalleled demands on our healthcare system has emphasized this challenge. As healthcare organizations reached their capacity limits, many of them turned to technological solutions. This alone shows how much potential lies in this area. At the same time, we are living in an era marked by a remarkable number of medical breakthroughs. Thanks to the tremendous advances in genome sequencing and synthetic biology, thousands of new medications are currently undergoing clinical trials; and the convergence of groundbreaking 10x biotechnology methods is opening up many new possibilities.


Already today, computers are able to make more precise diagnoses at an even earlier stage than radiologists. Over time, they will continue to outperform human capabilities and allow for doctors to recognize diseases earlier and find the right, personalized treatment, which will dramatically increase the patient’s chances of recovery. Digitizing medical data and using that data to train algorithms and find parallels will bring medical breakthroughs and insides that would never have been possible with manpower alone. The amount of data that needs to be analyzed far exceeds our capacity. The use of artificial intelligence in this sector will open completely new doors in the field of medical diagnosis and treatment, which is also referred to as precision medicine.


Precision medicine doesn’t only affect diagnosis and treatment. With the latest developments in proteomics, researchers are getting closer to solving what is referred to as the protein solving problem. Having a software predict the shape of a protein solely based on its amino-acid components would eliminate time-consuming procedures like x-ray crystallography and replace them with a few hours of computing power. Analyzing potential drug candidates and re-analyzing existing drugs for additional functions would allow us to tremendously accelerate drug development and potentially cure chronic diseases that often originate from a single misshapen protein.


Another promising field that could further accelerate drug development by providing better testing environments and even lead to cultured organs for organ-transplantations in the long run is organoid technology. Organoids are tiny, self-organized three-dimensional tissue cultures that are derived from stem cells. Such cultures can be crafted to replicate much of the complexity of an organ, or to express selected aspects of it like producing only certain types of cells, allowing for a much more precise testing environment for new drugs than the one we have to date with animal testing.


With further developments in synthetic biology, we will not only be able to precisely predict how proteins fold or how organs will react to certain drugs. We will ultimately be able to modify our DNA and actually edit the very building blocks of life. As scary and far-fetched as this may sound, several CRISPR methods are actually already being tested in the quest for a cure for cancer. The biggest challenge being that the immune system oftentimes can’t detect cancer cells, scientists are trying to switch off the camouflage mechanisms of cancer cells using CRISPR methods, which could potentially enable the patients immune system to eliminate the cancer cells itself. Another method that is being tested involves modifying the specimen of the patient’s immune cells to enable the cells to detect and destroy cancer cells directly.

We believe that the next few years will see tremendous advances in medicine and biotechnology, and we would love to support disruptive teams to provide technologies that could potentially save lives. Given our background and our expertise, we will focus on the interface of software and hardware/medical research.

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