October 29th, 2021 Innovation Insights
Modern medical technology has already shown us how it is changing the future and our lives with the rapid development of the vaccine COVID 19. Advances in medical technology are not only a source of hope for people. With new therapeutic approaches and faster vaccine development, it also offers solutions for society and the healthcare system.

In the context of SARS-CoV-2, representatives of the medical technology (MedTech) industry expect a surge in digitalization, because digital excellence is more important than ever for future viability. It is therefore worth investing in medical technologies. Successful MedTech companies are all about new product development, and it only takes one breakthrough idea to change a product category forever. Such companies manage to get closer to patients by developing new solutions. For example, medical health data (Big Data) can be mastered and analyzed at lightning speed with the help of artificial intelligence. The new innovations, provide a consistently better experience for all users, drastically reduce process costs, enable patient data to be matched with the best possible therapies, and thus accelerate decision-making even in time-critical situations.

In our latest Innovation Insight, the focus is on the megatrend of health. Swiss investment analytics company ALPORA gives you an insight into data-driven drug and medical research as well as new approaches from cancer research. Want to learn even more about innovative insights & megatrends? Click here for our latest Innovation Insights.


Human medicine is undergoing a fundamental transformation, driven by years of medical expertise, coupled with detailed, meaningful patient data and high computing power. Big Data, algorithms, artificial intelligence, and blockchain are refining medicine at an unprecedented pace. Data-driven medicine promises both better diagnoses and faster production of new drugs, as well as more precise therapies and tailored personalized treatments.

Data-driven and digital medicine is already a reality at select tumor centers. But what does it look like? In clinical decision-making, physicians are supported by pathological and genomic data, for example. Depending on patient history and medical records, sophisticated algorithms predict the best possible course of action, considering high probabilities of efficacy and good chances of survival. This allows the experts to quickly agree on the best therapy even under enormous time pressure. The further course of the disease is tracked with the help of artificial intelligence, and in the event of alarming signs, the doctor to be treated automatically receives a direct message.

Using the Big Data software Netculator (learn more under ALPORA Methods), we analyze current and topic-specific scientific publications for each Innovation Insight. This allows us to draw conclusions about future innovations based on basic research in the respective fields. Most publications on the topic “Health & Innovation” have been published in the following journals:



In clinical decision making, physicians are exposed to high expectations and must deal with a large amount of clinical data. In this complex matter, the physician decides on the information needed, the texts to be performed, the interpretation of the results, the combination of diagnostic hypotheses, and finally the best treatment method for the patient. Thus, diagnoses are made by recognizing typical clinical pictures. In relation to everyday situations, such identification of clinical pictures is efficient and easy to handle. For decision making in particularly complex cases, however, a quantitative analytical methodology may be a better approach. Analytical decision making is also commonly used to avoid misdiagnosis and to confirm the diagnosis made by the physician. For example, a clinical decision support system (CDSS) can assist the physician in decision making.

A clinical decision support system is a health information technology that not only provides personal information but also presents knowledge relevant to decision-making. CDSS follow similar approaches as management information systems and data warehouses but are usually based on advanced mathematical methods. For example, artificial intelligence techniques are used to process medical data. Tools that improve decision making in clinical workflow include patient data summaries, diagnostic support, computerized alerts and reminders, and contextual reference information. The goal is to improve healthcare for the benefit of everyone’s health.


Day by day, huge amounts of data such as clinical studies, laboratory results, cancer registries, X-rays, and diagnostic reports accumulate in the medical field. The goal is to intelligently combine these disparate data sources to draw a conclusion to advance medical research and disease treatment. Artificial intelligence algorithms are designed to evaluate the so-called medical Big Data so that diseases can then be accurately detected by computers.

In some fields, including medicine, human skills are already surpassed by computers when it comes to analyzing CT scans and mammograms. It takes years of practice to deduce a diagnosis from high-resolution images. And even then, there’s no guarantee that some tiny piece on the image has not been missed. This is a classic case for the use of Doctor AI.
Computers have a distinct advantage over the human eye when it comes to reading image information. This is because computers process images pixel by pixel, detecting minimal gradations in brightness, color, and gray levels that are imperceptible to humans. It can be said that computers are much better analysts of what are now very detailed and high-resolution images.


The blockchain mechanism is ideally suited for secure data exchange. Shivom, a young startup from Germany based in Munich, takes advantage of this feature. They are combining blockchain, AI, and machine learning technologies with a new branch of science, genomics, to create a secure data hub for genomic data. AI algorithms continuously analyze and learn from the data fed into the data hub.

Not only can pharmaceutical and diagnostic companies use the genomic data for drug and medical research, but patients can also transmit their personal health data from medical devices and wearables live to the platform. There, a comparison of the imported health data with the existing genome data subsequently takes place to enable conclusions to be drawn about diseases or predispositions. Blockchain technology is ideally suited here to manage complex data rights, track security aspects, and control access based on smart contracts.

Have you read our latest Innovation Insight on Blockchain and Smart Contracts? Click here for more information



Ilex Medical Ltd. is an Israel-based company operating in the medical sector. Its innovation focus is on in vitro diagnostic equipment for laboratory use. The company is heavily involved in laboratory management software and offers state-of-the-art diagnostic devices and reagent systems.


Roche Holding manufactures pharmaceutical and diagnostic products and develops reagents and equipment for medical testing. In the research area of oncology, for example, bispecific T-cell antibodies are researched and analyzed using Big Data and bioinformatics. In the process, new innovative solutions are developed for previously undiscovered medical needs.


Maravai LifeSciences Holdings, Inc. is a life sciences company. Its innovation focus is on developing new diagnostic solutions to support human disease research. The company’s businesses include nucleic acid manufacturing, biologics safety testing, and protein detection.


Fulgent Genetics, Inc. is a technology company in the healthcare industry. It offers genetic testing to provide clinically actionable diagnostic information to physicians to improve the quality of patient care. The company has developed a technology platform that integrates data comparison and suppression algorithms, adaptive learning software, advanced genetic diagnostic tools, and integrated laboratory processes.


Cancer is the second leading cause of death worldwide after cardiovascular disease. Not only in the case of lung cancer, doctors and researchers rely on the body’s own immune system to get the life-threatening tumors under control. The classic standard therapy, consisting of surgery, radiotherapy, and chemotherapy, is now being supplemented by another procedure: immuno-oncology. The aim is to attack the tumor with the means of the immune system. There are currently various treatment approaches available.


More than 100 years ago, the German physician and researcher Paul Ehrlich put forward the thesis that the body’s own immune system is capable of fighting cancer cells. His theories were considered the inspiration for important developments in cancer therapy. Although researchers have increasingly succeeded in deciphering the immune system’s response to cancer cells over the past 30 years, they have still not succeeded in understanding everything down to the smallest detail. This has repeatedly led to many unsuccessful immunotherapeutic approaches. In contrast, immune researchers Tasuku Honjo and James Allison have recently made a breakthrough with the discovery of so-called checkpoints. They succeeded in finding a way to influence the activity of tumor cells (T cells) of the specific immune system. In 2018, they received the Nobel Prize in Medicine for their cancer immunotherapy.

Generally, drug therapies such as chemotherapy or hormone therapy aim to remove or shrink the malignant tumor. Or at least to prevent it from growing and spreading uncontrollably in the surrounding tissue. Immuno-oncological therapies follow the modern approach that the cancer treatment does not attack the tumor itself, but the body’s own immune system is taken to help.


Compared to radiation and especially chemotherapy, targeted therapies are designed to attack only tumor tissue without harming healthy cells and tissue. In immunotherapies, the cancer cells are marked, so to speak, so that the immune system can recognize them as harmful invaders. A prerequisite for successful application is that the tumor has corresponding molecular properties, which is why we also speak of molecular biological therapies. It is therefore essential to precisely characterize each tumor tissue in advance in order to determine which patients are suitable for targeted therapy. The modes of action differ in that some therapies cut off the tumor’s nutrient supply, while other therapies inhibit its growth drive.

Our immune system is vital. When it is smoothly intact, it fights off infections and protects the body from pollutants, pathogens, and disease-causing cell changes. Despite the fact that the body’s immune system is strong and highly complex, it is not infallible. For one thing, cancer cells can protect themselves from immune system attacks by inhibiting immune cell activity. In other words, cancer cells can be recognized by the immune system but cannot be fought. On the other hand, cancer cells repeatedly manage to trick the body’s own defenses, i.e., to escape undetected and camouflage themselves.
In this way, camouflaged cancer cells can imitate the appearance of healthy cells and multiply and spread unhindered. These so-called “camouflage or escape mechanisms” can be targeted by new treatment methods with checkpoint inhibitors or with genetically modified immune cells (CAR-T cells). The so-called checkpoints are control points on the T cells that are activated by the cancer cells to camouflage themselves and thus slow down the immune system. Immune checkpoint inhibitors are specially designed antibodies to reactivate the immune system and, metaphorically speaking, make the camouflaged cancer cells visible again. Antibody therapy with a checkpoint inhibitor releases the brakes on the immune system and allows the immune system to take up the fight against cancer. For cancers such as lung cancer, bladder cancer, skin cancer, or kidney cancer, innovative immunotherapies contribute to extended therapy.


Next Generation Sequencing, or NGS, is a massively parallel sequencing technology that has opened new avenues in genomics, oncology, and ecology. It is used to develop vaccines and often to clarify genetic diseases such as cancer. Tumors are caused by changes in the genetic material, so no two cancers are alike. Genome sequencing can help find mutations in a tumor when standard cancer therapies fail or it cannot be determined where the cancer originated. When a change is found in the genome, it gives doctors better clues as to which targeted therapies or drugs will help and lead to better cancer treatment.

Compared to traditional methods, NGS offers advantages in terms of accuracy, scalability, and speed. The technology is used to determine the sequence of nucleotides (building blocks of nucleic acids in both DNA and RNA strands) in whole genomes or in specific regions of DNA (deoxyribonucleic acid) or RNA (ribonucleic acid). Medical laboratories have been empowered by NGS to implement a wide range of applications and study biological systems at a whole new level. It is said that NGS has revolutionized the life sciences!

Next-generation sequencing has the ability to sequence (read) the building blocks of many hundreds of cancer-specific genes in parallel and with high accuracy. This means that multiple genes can be examined in a single test to determine the original mutation. This in turn means that this multigene approach consumes fewer valuable clinical samples and tests, shortens the time to answer, and presents a more economical solution. This speed and accuracy enabled scientists to rapidly sequence the new COVID-19 virus and identify potential vaccines.

In terms of vaccine development, NGS offers the ability to test numerous vaccine candidates in a high-throughput process. This helps scientists to better understand how a particular vaccine affects the human body and interacts with a virus. NGS can therefore be used not only in the early stages of vaccine development but also to determine the efficacy of vaccines. It is therefore expected that many biotech startups will be able to develop new more efficient products in increasingly rapid cycles.

For genomics-oriented pharmacology, next-generation sequencing has already proven to be a valuable method, especially for gaining a deep and detailed insight into the molecular basis of individual tumors. Furthermore, targeted therapies are part of the new therapeutic standard in oncology and NGS-based companion diagnostics are seen as a driving force in treatment selection to optimize patient outcomes in the future.


Genmab A/S

Genmab is a Danish biotechnology company focused on antibody discovery and the development of antibody therapeutics for the treatment of cancer. The company has three approved products and four proprietary next-generation antibody technologies.


Merck & Co. Inc. is a research-driven global pharmaceutical company exploring a broad range of novel drugs, vaccines, and biologic therapeutics. The company makes use of biotechnology, genetic research, and gene therapy. Its research focuses on the treatment of cancer and cardiovascular diseases.


Pharma Mar, S.A. is engaged in the research, development, and production of biopharmaceuticals. Its research and development focus on oncology technologies such as antitumor agents of marine origin. The company operates through its subsidiaries in three business segments: Oncology, Diagnostics, and RNA Interference.

Bavarian Nordic A/S

Bavarian Nordic is a Danish biotechnology company focused on the development, research, manufacturing, and marketing of cancer immunotherapies and vaccines based on viral vectors for the delivery of antigens against infectious diseases and cancer.


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