It is rather odd how often I hear the expression paradigm shift during contemporary scientific presentations and seminars. The expression was popularized by Thomas Kuhn’s book The Structure of Scientific Revolutions. In that book, Kuhn referred to ground-breaking and revolutionary changes in scientific thought as paradigm shifts, but the expression is so over-used today that even minor discoveries are sometimes marketed as paradigm shifts.

However, once in a while a true paradigm shift does come along and I believe we are currently witnessing such an emerging paradigm shift: open science. This concept entails that research results should be freely and openly accessible to the broad scientific colleagues as well as the public.

The idea of open science goes beyond merely providing public access to published scientific articles because it also includes offering access to the original research data. This would permit fellow researchers to help evaluate and analyze the results, so that the broader scientific community as well as the public can weigh in on the interpretation of the scientific findings. This aspect of open science likely does qualify for being a true paradigm shift, because it will require that we think of ourselves as part of research communities and usher in “networked discovery”, as has been described in a recent book by Michael Nielson and discussed by Bora Zivkovic.

There are still many obstacles that need to be addressed before “open science” becomes generally accepted. Academic publishers currently reap significant profits from selling high-priced annual subscriptions to academic institutions, and they would lose this income if scientists started publishing their results in open-access journals that freely provide articles to readers without charging for subscriptions or per-article fees. Furthermore, academic institutions and individual scientists may be concerned about how they would apply for patents, if the discovery process is networked and involves score sof collaborating scientists.

Marc Kuchner recently wrote about how individual academic careers are currently built on marketing or branding oneself as a leader in defined research areas. If data and research methodologies are openly shared, it becomes much harder for individual investigators to take credit for discoveries and succeed in the competitive academic rat-race. Therefore, the current academic environment does not reward or provide incentives for openly sharing data or research methods.

Nevertheless, under pressure from the public and funding agencies that rightfully demand public access to the results of the funded research, it is likely that our current research culture will change. We will gradually tear down the walls that exist in our current scientific culture. It will not happen overnight, and we will have to develop new infrastructures to share scientific data, novel ways to assess academic success and reward contributions of individual scientists as well as establish high quality open access journals in a variety of scientific areas.

However, one has to keep in mind that certain areas of research are associated with unique challenges when it comes to the implementation of open science. The obstacles presented openly sharing original data and results in biomedical research may be very different from those in astrophysics.

Clinical research is often funded by the private industry and may thus evade mandates of public funding agencies or not-for-profit foundations to publish in open access journals and openly share results. But even publicly funded biomedical research is characterized by some unique challenges.

One such challenge is the importance of maintaining patient confidentiality when it comes to data sharing. Institutional Review Boards monitor the ethics of studies involving human subjects or patients at all academic institutions and one of their biggest concerns is how personal data of subjects or patients is handled. Usually, the data is de-identifed for the purpose of publication so that any kind of description of the disease state, symptoms, mutations or other findings cannot be linked to individuals.

Only a very small group of trained professionals have access to the names of the subjects or patients and usually only these review the medical charts or personal questionnaires of the participants. If the data-sets are made publicly available, it is imperative that appropriate safeguards are put in place to assure the participants that the data will only be shared in a de-identified format and that anybody seeing the data-set will not be able to link the diseases to the individual identity of the participants.

There is another critical obstacle that needs to be addressed when open science is implemented in medical research. The primary target audience for basic research that is not related to medicine or health consists of fellow scientists and science journalists.

I remember that I started my research career working as a chronobiologist on the circadian rhythms of the unicellular marine algae Gonyaulax polyedra. I doubt that anyone other than fellow scientists or science journalists would have been interested in accessing or interpreting our original data, even if all the data and results had been presented in an open access format.

On the other hand, my research in recent years has shifted to areas that have a more direct medical relevance, such as metabolism and stem cells in vascular disease, heart failure and cancer. My research approach is still focused on basic biological mechanisms, but due to the change in my research topics, I have encountered much broader interest from patients as well as healthcare providers.

Patients with severe chronic illnesses and their loved ones scour the internet for possible new therapies, even if these therapies have not been proven to work. The burden of disease makes them emotionally vulnerable so that they may selectively read and interpret the scientific literature in a manner that gives them false hopes.

For example, I remember talking to one of my heart failure patients who wanted to pay out of his own pocket for a trip to Thailand so that he could receive adult stem cell injections to improve his heart failure. He had found out about this experimental therapy through the internet. Since he did not qualify for any of the ongoing adult stem cell therapy trials in the US, he was extremely interested in trying out this therapy that was being offered overseas (for a substantial fee). He was not aware of the potential side effects of invasive stem cell injections or the importance of quality control and he assumed that it was proven that they work for heart failure. It was only after extensive counseling that he understood there was no clear evidence supporting the therapy and decided to avoid subjecting himself to the questionable therapy.

Many healthcare providers such as practicing physicians do not have a scientific background and are not necessarily trained to critically evaluate research data. They currently rely on review articles or meta-analyses published in respected journals, but they are also influenced by scientific data that are presented to them by representatives or consultants for the pharmaceutical industry.

At first glance, open access to original data sets should increase the transparency of research. However, if we remember the adage that “we only see what we want to see”, we have to realize that open access to research data will also create an opportunity for pharmaceutical companies or for-profit hospitals to promote medical therapies on the basis of limited scientific data.

Selective reporting of the publicly available data by special interest groups could find an excellent breeding ground among emotionally vulnerable patients or healthcare providers who may be easily swayed by the plight and hopes of their patients. One example of selective reporting or selective analysis would be when negative clinical trials are re-analyzed to identify some subgroups of patients that showed a statistically significant improvement with the experimental therapy.

Another example could be that the clinical significance of in vitro cell signaling studies or animal studies could be over-stated. In a traditional academic paper, most of our scientific colleagues (voluntarily or after peer-review) highlight the limitations of their studies. If the data is publicly available, the data would be open to variant interpretations, even by members of the community who are not trained to appropriately interpret the data.

The solution to these potential issues that may arise when we transition to an open science format is not to limit the access of the data. Instead, it is imperative that concomitant with the creation of an open science environment we also build independent institutions or organizations that help interpret the available the data in a manner that non-scientists are able to receive accurate and solid information about the nature and significance of the results.

“Consumer Reports” in the US or “Stiftung Warentest” in Germany routinely test consumer products for their quality and safety, and report them in a manner that members of public can understand the results. Consumers buy subscriptions to their websites or magazines and they enjoy respect among consumers, who have confidence in their unbiased evaluations of products.

One could envision similar institutions that evaluate the biomedical research data and can give solid advice to non-specialists. Ideally, such institutions would need to include independent expert scientists as well as independent experts at communicating science to the broader public. The reason for including expertise in science reporting and science communication is simply due to the fact that many scientists are “communicatively challenged”. It does not help the broader public if a group of scientists charged with providing independent evaluation of publicly available datasets produces reports that are full of technical jargon. As funding agencies and the public push for open access to scientific research data, they also need to push for developing and funding infrastructures that can help the public interpret the openly accessible data.

In summary, I believe that the time for open science and networked discovery has arrived and that it will definitely enhance the progress of scientific research, as long as we build institutions that help us process and understand the flood of scientific data that will be released in the new open science world.

Image: Yann on Wikimedia Commons.