From Bed[side] to Bench: Involving Patients and the Public in Biomedical Research

By Celine Cammarata

 

Many of us doing biomedical science never really see patients, the very people our work will hopefully one day help. But what if we did – what if those individuals who will eventually be using our research on a daily basis were in fact involved in the work from the start? How would research change?

 

This is the concept underlying the movement toward Patient and Public Involvement or PPI, a title that (logically enough) refers to efforts by researchers and institutions to engage patients and members of the public in the process of biomedical research and, in doing so, fundamentally change the way scientific information is created and disseminated. Traditionally, the flow if information between science and society was seen as relatively unidirectional, with researchers passing scientific knowledge down to an uninformed, receptive public. More recently, however, there has been a growing recognition that information flow from the end-users of research back to investigators is also critical.

 

One way to accomplish this is to directly incorporate those users – broadly defined as patients, caregivers, members of the public rather than clinicians or practitioners – into the research process. A prominent definition of PPI is “research being carried out ‘with’ or ‘by’ members of the public rather than ‘to’, ‘about’ or ‘for’ them” (INVOLVE). Individual instances of PPI can be quite variable, though most engage users in some form of advisory role, often through interviews, surveys, focus groups, and hosting users alongside researchers on regularly-meeting advisory groups (Domecq et al., 2014). PPI is represented at all stages of research, from inception of project ideas through the data collection process to implementation of findings and evaluation and is most prevalent in research that is either directly related to health or social issues and services.

 

A primary driving force behind PPI is the belief that input from users will push research toward questions that are more relevant to those users. Individuals with first-hand experience of an illness or other condition are thought to hold a particular kind of expertise and therefore able to craft more immediately relevant research questions than an academic investigator in the field might.

 

One important stage at which patients and the public are having an impact is by working with funding agencies to establish research priorities. For instance, the UK’s NHS Health Technology Assessment program involves users alongside clinicians and researchers in the development and prioritization of research priority questions. Members of the public were engaged in several different stages of the process, from initial suggestion of research ideas through to selecting topics that would be developed into solicitations for research. Analysis revealed that overall these lay members exerted an influence on the research agenda approximately equal to that of academic and clinical professionals (Oliver, Armes, & Gyte, 2009).

 

PPI can also increase the relevance of individual studies, with specific examples including: users of mental health services shifting outcome measurement in a study of therapies to improve cognition away from psychological tests in favor measuring performance on daily activities; the investigation of environmental factors such as radiation, which researchers originally considered negligible, in a study of breast cancer; and the development of new assessment tools to measure the mental and psychological condition of stroke victims in a study that initially planned to focus only on physical health outcomes (Staley, 2009).

 

Users may express particular suspicions or hunches about their condition that they believe should receive further investigation, may increase pressure on investigators to clearly state how their work will contribute to the public, and may challenge whether a project is even conceptualized in a way relevant to those who experiencing the situation in question, helping to determine whether a research problem is truly a “problem” at all. An excellent example of the impacts of PPI in research commissioning is the Head Up project, an entirely user-driven project in which patients with motor neuron disease working with one of the CCF programs pushed for research on an improved supportive neck collar.

 

PPI may also help increase the up-take of research findings because user’s are generally able to relate to and communicate with other users and practitioners in a uniquely meaningful way. Patients and members of the public may help to write up study findings, present at conferences or, importantly, bring findings directly to the user community.

 

Of course, nothing comes without a cost. A number of challenges in conducting PPI have consistently been identified, including: insufficient time and funding; tension over roles on the project and difficult relations between academic researchers and users; lack of training for both users and researchers; and a tokenistic attitude toward PPI on the part of investigators. Still relatively little is known about the precise effects of PPI or best practices. However, these are active areas of scholarship. Also of note is the relative lack of PPI in basic science research; PPI is predominantly relegated to applied health and social research. An important step in furthering PPI would be to establish who the “users” of basic research are, whether PPI in basic research is likely to be beneficial, and how the practice could be implemented.

 

Overall, it is clear that the end-users of research can be incorporated into setting the research agenda, designing studies and communicating results, and suggests that such user engagement can increase the relevance of research and the dissemination and adoption of findings.

Open access: the future of science publishing?

By Florence Chaverneff

On the eve of receiving the Nobel Prize in Physiology or Medicine in 2013, Randy Schekman shook the scientific world in an altogether different manner when he announced in the Guardian newspaper he and his group would boycott the three leading scientific journals. These bastions of scientific publishing have long been held on a pedestal by the research community the world over and regarded as depositories of excellence in science. Their reputation is tightly associated with high ‘impact factors’, a parameter determined by article citations, and which Schekman judges to be a “gimmick” and a “deeply flawed measure, pursuing which has become an end in itself – and is damaging to science”. Yet, career advancement in academic research is heavily – if not exclusively– reliant on individuals getting their work published in these high impact scientific journals, which Schekman calls “luxury journals”, comparing them to bonuses common on Wall Street, and from which “science must break [away] “. He deems that “the result [of such a change] will be better research that better serves science and society”. The Nobel Prize awardee touts the open access model for scientific publishing, presenting it as all-around anti-elitist, which…it is.

 

In 2001, the Budapest Open Access Initiative defined open access for peer-reviewed journal articles by its “free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself”.

 

This is how open access makes for a more level playing field: by allowing immediate dissemination of scientific findings without restrictions, and by accepting articles without highly demanding criteria, while maintaining sound peer-review practices. This comes in sharp contrast to the 300 year old model of subscription-based scientific publishing, accepting limited numbers of articles in each issue, and requiring exceedingly demanding standards for acceptance. This results in significant publication delays and considerable time effort spent polishing articles for publication. Time which could be spent… doing research.

 

While many in the community will agree on the benefits granted by this still recent and evolving model of science publishing, open access journals, being less established than older household names, and lacking in their majority an impact factor, may not appear as prime choice for researchers. The question then can be posed: what would it take to bring about a shift in attitudes where open access publishing would be favored? Granting agencies and academic institutions, which contribute to setting the standards for scientific excellence need to start being more accepting of non-traditional models of scientific publications, and judge on quality of research, and not solely on journal impact factor. National policies encouraging open access publishing are also paramount to support such a shift. Moves in that direction are underway in the UK with a policy formulated by the Research Councils, and in the European Union with the Horizon 2020 Open Research Data Pilot project, OpenAire. In the US, the Fair Access to Science and Technology Research Act and the Public Access to Public Science Act aiming “to ensure public access to published materials concerning scientific research and development activities funded by Federal science agencies”, if passed, would be a step in the right direction.  All else that is needed might be a little time.

 

Should Systematic Review be a Bigger Part of Science?

 

 

By Celine Cammarata

For years, groups such as the Cochrane Collaborative and the Campbell Collaboration have worked to support and promote systematic review of medical and social policy research, respectively. These reviews can then help decision-makers and practitioners on the ground – doctors, public health officials, policy developers, etc. – to make scientifically based choices without having to wade through hundreds of journal articles and sort the diverse fragments of evidence provided. In a Lancet editorial last November, authors Iain Chalmers and Magne Nylenna expounded on how systematic reviews are critical for those within science as well, particularly in the development of new research. Given these lines of reasoning, should we as scientists try to elevate systematic review to a more esteemed position in the world of research?

Systematic reviews differ from traditional narrative-style reviews in several ways. Traditional reviews generally walk readers through the current state of a field and provide qualitative descriptions of the most relevant past work. In contrast, systematic reviews seeks to answer a specific research question, lays out a priori criteria to determine which studies will and will not be included in the review, uses these criteria to find all matching work (as much as possible), and combines all this evidence to answer the question, often by way of a meta-analysis.

Chalmers and Nylenna argued that many scientists fail to systematically build future work upon a thorough evaluation of past evidence. This, the authors believe, is problematic both ethically and economically, as it can lead to unnecessary duplication of work, continued research on a question that has already been answered, and waste of research animals and funding (see the Evidence Based Research Network site for more on research waste). Moreover, research synthesis as supported by Cochrane and Campbell helps package existing scientific findings into something that practitioners can use, thus greatly facilitating translational research – one of science’s hottest buzzwords, and with good reason. On the flip side, as Chalmers and Nylenna argue, if a field does not actively synthesize it’s findings, this can cause inefficiency in answering overall research questions that can have significant consequences if the issue at hand has important health implications.

I think there are many reasons large-scale research synthesis is currently less-than-appealing to scientists. On the production side, preparing a systematic review can be extremely time consuming, and generally offers little career reward. On the usage side, some researcher may not consider a systematic review necessary or even preferable as a basis for future work – they may feel that less systematic means are actually better suited to the situation, for instance if they have less confidence in some findings than others based on personal knowledge about the study’s execution. Additionally, investigators may consider narrative reviews to be a sufficient to basis for future studies even if these reviews do not employ meta-analysis, for instance if such narrative reviews were authored by leaders in the field whose expertise and scientific judgment is respected.

What would it look like to put research synthesis in a position of greater prominence? For one thing, as mentioned above, contributing to reviews would likely have to be incentivized if investigators are to be enticed away from their busy schedules, so this would constitute a change in the current academic reward structure. In addition, if scientists saw research synthesis as more valuable than individual high-priority papers, this might both necessitate and foster a more collaborative attitude. Doing research with the explicit goal of making it usable to those who will build off it and filling specific holes in the current body of knowledge may drive very different experiments than does a goal of producing exciting, flashy papers (obviously this is not an either-or situation – in fact I think the vast majority of scientists work somewhere in the middle of the spectrum between these poles).

One step in this direction might be the growing movement of data sharing. Another might be greater coordination within a field about methodology and research questions, which could streamline synthesis. For example, a recent Campbell review on Cognitive-Behavioral Therapy found that of 394 potentially relevant studies, only 7 were ultimately eligible for inclusion in the review, indicating that many investigators either used insufficiently rigorous methodology, fell short of fully reporting data, or prioritized different design aspects than those review authors needed to address the question at hand.

 

Should these changes be made? To me, this remains somewhat opaque. Arguments such as Chalmers and Nylenna’s are strong, and a focus on synthesis could come hand-in-hand with some refreshing changes in how science is done. But systematic review is not the only tool in the toolbox. For now, it remains a choice each scientist will have to make for her or himself.

Are Existing Policies Regulating Recombinant DNA Technology Adapted for Synthetic Biology?

 

By Florence Chaverneff, PhD

 

Background on Synthetic Biology

Synthetic biology is gaining increasing interest as one of the most promising new technologies of the 21st century. Its revolutionary nature, wide-ranging applications across several scientific disciplines, and the fact that it may help solve some of the world’s most pressing issues, all contribute to the justified enthusiasm for the field. As the boundaries, prospects and even nature of synthetic biology still need to be clearly outlined, the definition advanced by a high-level expert group of the European Commission, encompasses it well: “Synthetic Biology is the engineering of biology: the synthesis of complex, biologically based (or inspired) systems which display functions that do not exist in nature. This engineering perspective may be applied at all levels of the hierarchy of biological structures-from individual molecules to whole cells, tissues and organisms.”

 

In the same manner that recombinant DNA technology revolutionized biology in the 1970s, synthetic biology is breaking new grounds. However, because it requires a greater need for DNA synthesis than recombinant DNA technology, synthetic biology brings life sciences closer to engineering. It aims to make biology easy to engineer. And that is the revolutionary part. Its multi-disciplinary nature at the nexus of biology, engineering, genetics, computational biosciences and chemistry implies that synthetic biology be practiced in a global and networked fashion, posing it as the ultimate collaborative venue for scientific research.

 

Applications of Synthetic Biology

The array of what synthetic biology allows to design and produce, from biomolecules, to cells, pathways, and ultimately, to living organisms, in by itself gives an idea of the power of the technology. Synthetic biology, with its new category of tools that allow advanced DNA synthesis, conceptualization of biologically complex systems, and standardization for mass production is more approachable to a less skilled workforce in a more efficient and manageable manner than what is currently practiced in biotechnology companies.

 

Applications of synthetic biology are wide-ranging, from global health (e.g. vaccine and antibody production, regenerative medicine, development of therapies for cancer, approaches for cell therapy) to generation of biofuels, to food production. And as the field is growing, technologies are bound to evolve, giving rise to an even wider array of applications. One of the most notable and highly publicized successes of synthetic biology was published in Nature Biotechnology in 2003. The article describes a novel way of producing the anti-malarial drug artemisinin, using the bacteria E. coli as a host, in which enzyme and metabolic pathway for artemisinin production were expressed. Artemisinin synthesized in this manner can be produced at much higher yield and much lower cost than by plant extraction. These considerations are of great importance for an anti-malarial drug, destined to large populations in low income countries.  Another powerful example of the promises held by synthetic biology lies in a study published last year in Science, reporting the assembly of a synthetic yeast chromosome, heavily edited from its natural counterpart, yet functional when expressed in its organism.

 

Crafting Policies for Synthetic Biology

Despite being over a decade old, synthetic biology is still in its infancy, its full potential has yet to be realized, and a regulatory framework indispensable to any new technology that can be applied to life sciences, will have to match the field’s evolution. Some policies for synthetic biology may be adapted from existing ones that were designed to regulate recombinant DNA technology and genetic engineering. However, it is critical that new regulations, tailored to synthetic biology, which is tantamount to engineering artificial life, be established. Considerable changes in regulations should be avoided, as they might result in holding up development of the fast-evolving synthetic biology.

 

Perhaps one of the most important policy aspects to consider for synthetic biology is linked to its sheer nature. Synthetic biology permits manufacturing of whole living organisms, which, if released in the environment, could greatly affect it by interacting with ecosystems. It is therefore imperative that preventive measures be taken and that ethical oversight be installed to avoid misuse of the technology. Another policy aspect particular to synthetic biology is related to its multi-disciplinary nature: all its practitioners, not just biologists, should be educated in biosafety. Additionally, policies should allow for training of scientist, researchers and other professionals to meet the demands of the field. Several top institutions in the US have already launched graduate programs in synthetic biology, but more educational programs are required.

 

Synthetic biology research and frameworks for funding are also vital to support evolution of the field by strengthening research and development capabilities, and supporting innovation. Synthetic biology should be practiced in academic institutions and private ventures alike.  In both instances, policies should be adapted so that results from research meet demands of modern economy, by taking measures to industrialize innovation in commercially successful ways through facilitation of technology transfer and intellectual property management.

 

Finally, because synthetic biology is heavily reliant on openness and sharing and holds great potential for becoming the poster child of international scientific cooperation, national policies formulated in the US and elsewhere could serve as template for transnational policies.

 

The “Big Data” Future of Neuroscience

 

By John McLaughlin

In the scientific world, the increasingly popular trend towards “big data” has overtaken several disciplines, including many fields in biology. What exactly is “big data?” This buzz phrase usually signifies research with one or more key attributes: tackling problems with the use of large high-throughput data sets, large-scale “big-picture” projects involving collaborations among several labs, and heavy use of informatics and computational tools for data collection and analysis. Along with the big data revolution has come an exploding number of new “omics”: genomics, proteomics, regulomics, metabolomics, connectomics, and many others which promise to expand and integrate our understanding of biological systems.

 

The field of neuroscience is no exception to this trend, and has the added bonus of capturing the curiosity and enthusiasm of the public. In 2013, the United States’ BRAIN Initiative and the European Union’s Human Brain Project were both announced, each committing hundreds of millions of dollars over the next decade to funding a wide variety of projects, directed toward the ultimate goal of completely mapping the neuronal activity of the human brain. A sizeable portion of the funding will be directed towards informatics and computing projects for analyzing and integrating the collected data. Because grant funding will be distributed among many labs with differing expertise, these projects will be essential for biologists to compare and understand one another’s results.

 

In a recent “Focus on Big Data” issue, Nature Neuroscience featured editorials exploring some of the unique conceptual and technical challenges facing neuroscience today. For one, scientists seek to understand brain function at multiple levels of organization, from individual synapses up to the activity of whole brain regions, and each level of analysis requires its own set of tools with different spatial and temporal resolutions. For example, measuring the voltage inside single neurons will give us very different insights from an fMRI scan of a large brain region. How will the data acquired using disparate techniques become unified into a holistic understanding of the brain? New technologies have allowed us to observe tighter correlations between neural activity and organismal behavior. Understanding the causes underlying this behavior will require manipulating neuronal function, for example by using optogenetic tools that are now part of the big data toolkit.

 

Neuroscience has a relatively long history; the brain and nervous system have been studied in many different model systems which greatly range in complexity, from nematodes and fruit flies, to zebrafish, amphibians, mice, and humans. As another commentary points out, big data neuroscience will need to supplement the “vertical” reductionist approaches that have been successfully used to understand neuronal function, by integrating what has been learned across species into a unified account of the brain.

 

We should also wonder: will there be any negative consequences of the big data revolution? Although the costs of data acquisition and sharing are decreasing, putting the data to good use is still very complicated, and may require full-time computational biologists or software engineers in the lab. Will smaller labs, working at a more modest scale, be able to compete for funds in an academic climate dominated by large consortia? From a conceptual angle, the big data approach is sometimes criticized for not being “hypothesis-driven,” because it places emphasis on data collection rather than addressing smaller, individual questions. Will big data neuroscience help clarify the big-picture questions or end up muddling them?

 

If recent years are a reliable indicator, the coming decades in neuroscience promise to be very exciting. Hopefully we can continue navigating towards the big picture of the brain without drowning in a sea of data.

The Global STEM Alliance – Revolutionary or More of the Same?

 

By Celine Cammarata

A few weeks ago, the New York Academy of Sciences and an impressive slew of public and private partners announced the Global STEM Alliance, a new initiative to attract and retain bright young minds in science, math and engineering. On the surface this new project seems much like many other efforts to “fix” STEM education that have already come and gone, and indeed the Alliance is built on principles that can hardly be considered unprecedented: it seeks to provide better resources for science teachers, give kids exposure to real labs and scientists to pique their interest, and leverage the internet to reach widespread populations. But the unique combination of details comprising the program give the impression that it might actually achieve something more revolutionary.

 

Networks that Work

The Global STEM Alliance is using an innovative combination of on-the-ground and online components. While the Alliance will work with partner agencies to develop classroom materials, teacher education and other activities, the crux of the operation will be an new online platform combining videoconferencing and state-of-the-art educational tools to create, essentially, a virtual playground for science learning. Although the Alliance has not revealed exactly what will be hosted on this platform, it seems the main idea is that the e-space will foster collaborations, and will provide a central location for Alliance programs to reach diverse audiences.

 

Locally Conscious with a Global Perspective

True to name, the Global STEM Alliance will be an international endeavor. The Alliance is building from the NYAS’s current educational projects, which already are established or developing in six countries, and will use strategic partnerships to continue expansion from there. At the same time, the group plans to structure on-the-ground components so that they can be tailored to local needs.

This framework hopes to increases diversity, capturing the creative power and scientific spark of students in nations that may not typically be considered science hubs. Furthermore, this global reach replaces the nationalist rhetoric often associated with STEM education with a more collaborative approach, stressing science as something the brings humanity together rather than as a source of competition. The goal is not, in this case, to ensure our STEM workforce continues to dominate that of other nations, but instead to ensure that, collectively, we can meet the scientific challenges the world poses.

 

Mentors Matter

The program will heavily emphasize mentorship, particularly as a means of fighting attrition of students from STEM fields due to disinterest and discouragement; the hope seems to be that getting students under someone’s wing – preferably someone they can relate to – will help them feel more encouraged to pursue STEM, more excited and inspired, and to find STEM fields more accessible. Furthermore, the online platform will enable previously unlikely mentor-mentee relationships, linking researchers, industry professionals, and others from all over the world with an equally distributed student pool.

 

An All-Star Team

The Global STEM Alliance is not only built on partnership, but arguably has some of the best possible partners available. The NYAS has buddied up with communications giant Cisco to develop the online component of the Alliance, and has (or will be) recruited Nobel laureates and leaders in industry to be among the collaborative network and to mentor students.

 

Soft Skills Sell

The Alliance also claims that it will be emphasizing soft skills – management, teamwork, communication – which lie at the heart of the “STEM paradox.” However, it remains unclear how the Group plans to accomplish this, particularly given that most of the proposed activities that have been describes, such as working with a team of other future-scientists to solve a research problem, are not too different form the training already being received by university, graduate and postdoctoral students in STEM, which apparently has not prevented this crisis from occurring.

 

Impact?

What can we expect to result from the Global STEM Alliance? While the project’s success of course remains to be seen, it seems likely that this effort will make significant headway in improving retention so students in STEM, inspiring them to consider STEM careers, and possible better preparing them by developing the soft skill side. The impact of this, in turn, depends on your perspective. While the Alliance says that it’s efforts will drastically combat the ongoing STEM crisis, numerous commentators have called into question the existence of many such crisis. But that remains for another day…

Squeezed Science – Should We Switch to a Business Mindset?

 

By Jesica Levingston Mac leod, PhD

It is a common conversation topic among researchers, but it was not until the NPR article saw the light, and the dark side, that the public realized the problems that young scientists are facing when pursuing a successful career in Academia. As we raise awareness about these tribulations, my colleagues mentioned how a “postdoc”’s quality life depends on the quality of the lab, the institution, the project, the relationships with colleagues and the Principal investigator or PI (the boss), not forgetting that this is a very self driven career. So, if your hypothesis is very difficult to prove, or you have been hitting your head against the wall with all the negative results that took you years to get, you may eventually come to hating this path and leaving Academia. The same if you have been working in a non “hot field” where the funding sources do not consider interesting enough to support or your PI is not supportive, or you have a very wicked competence inside or outside the lab. All these negative situations can aggravate the perspective of the very little options one may have by pursuing a career in Academia. On the other hand, if you are obtaining excellent results, publishing in top tier journals, made hundreds of good connections and collaborators, have a “great boss” and literally love you job… well, probably you are also doomed…

One solution could be implementing the business approach to the scientific mindset: Why only having one PI per lab? At the end, two minds think more than 1. Perhaps collaborative research centers have a solution were 2 or more PIs can have access to more equipment, grants and professionals, and therefore use the best skills needed for the job, like a company where you have an executive committee and you distribute the stock between the employees, in order to make them be part of the enterprise.

Having a business mindset would mean to have a planed strategy about your career development. Having a backup career plan is one example of this: starting to apply for jobs before needed, or before it is too late. Begin with your preparation to be a leader, and make your PI know, and discuss a good starting point. Look for leadership opportunities in any situations, such as coordinating workshops or conferences.

Sign up to run workshops and career developing series!. Many postdocs can discover a great professional gain if these opportunities would be offer to them. Get training in other expertise to be competitive in, for example, the investing or consulting field. Taking classes about how to give a class is a great example of a course that could be offered to postdocs and graduate students, in order to train them to explain and transfer their empirical knowledge to the next generation.

A month ago, at the Mount Sinai Postdoc symposium, Dr. Bruce Alberts (yes, THE Alberts,  from “The Molecular Biology of the Cell” book) who spoke about “The Future of Biology: Keeping Science Healthy” and illustrated the dramatic changes in the age of the scientist successfully obtaining project grants from NIH. In contrast to 30 years ago, the average age of new investigators with PhD at initial RO1 was 36.8 year old, a large number of grants were awarded to scientist in their early 30s, but this tendency has been decreasing drastically, to the point where now, the mean age for receiving these prestigious grants is 42 years of age. Dr. Alberts, himself, made fun on the fact that he obtained his postdoc position, before been awarded with his PhD. (which actually his thesis was rejected the first time, delaying the whole process) and learned from his failures. He also pointed out that he got his professor position at a very young age, something that is almost impossible nowadays. He advocated for a change in this unfair situation, which cripples the young innovators from getting a start. Also, he encouraged researchers to get out of the lab and talk to the public about science and its importance. First, to attract/engage curious minds to the scientific field, and second to communicate “in simple language” what we do for 9 hours plus per day in the lab.

We must offer to all this new scientific minds the reality about the current situation of science, but we also need to fix it, so it is not going to turn into a snow ball and make disappear all the interest in pursuing a scientific career for the new generations. In a business mind-set we must recognize that the money is not only in the governmental funding, but also in private foundations and other organizations like angels or venture capitals. So go out there and try to pitch your science to investors.

Squeezed Science – What Does it Mean for the Next Generation?

 

By Celine Cammarata

Recent mainstream media coverage of the severe funding shortages in scientific research and the ramifications thereof have re-kindled discussion of these topics, already on the minds of many researchers. As a post-bacc trying to determine whether and how best to pursue a career in science, such discussion always make me question the implications for those of us at the threshold of the field. What new challenges should our scientific “generation” prepare for, what can we learn and what can we do differently to improve our likelihood of flourishing in science?

 

To young prospective scientists, a preliminary challenge is determining how much worry the current funding issues deserve to begin with. Not only do we, as newcomers to the field, lack the experience to compare this to the normal ebb and flow of research funding, but when we look to our mentors we get mixed advice, and of course we tend to only be in labs that do have funding. Consequently, it is extremely difficult to get a clear idea of just how serious the problem is, and what it means for us and our career choices. While concern about funding is a frequent topic of conversation among science students, it is rarely cited as a factor in their choices of whether to pursue research careers.

 

If we do decide to follow the scientific path, how can we update our expectations to match today’s reality – must we set aside the goal of one day running labs of our own? In one NPR piece, NYU post-doc program director Keith Micoli commented that even aside from budget cutbacks, a system in which one PI trains multiple post-docs who all expect to “replace” the PI is not sustainable. Changing expectations may help alleviate parts of the problem, both psychologically by reducing stress and disappointment and empirically by guiding modern scientists down more fruitful career paths. But how can that change be realized?

 

Currently “alternative” careers for science PhDs are often treated as a backup plan rather than a potential source of genuine excitement; the default remains to strive for a tenure-track position. This artificially limits the scope of careers options science students consider and in turn prepare for, both psychologically and in their training. No doubt this bias in part due to the fact that students are generally trained by professors, and so academic science is the primary career they are exposed to. Engaging other professionals in training students and presenting an array of career possibilities from the earliest point in scientific training are among structural changes in science education that could improve the plight of future generations of scientists.

 

What does the shifting reality of science research imply for outreach? Despite the current funding challenges, much outreach work is still geared toward attracting young people to careers in science, often specifically research. Undergraduate students are encouraged to consider research and often even stand to gain funding through scholarships and fellowships. Does this amount to recruiting for jobs that do not exist? At a minimum, extending the above line of thought, should outreach efforts of this sort try to represent the diversity of scientific careers available and not emphasize academic research? I myself am no longer sure what to tell the undergraduates I work with; can I encourage their interest in research, without contributing to the potential insecurity of their future careers?

 

I believe that most of my generation of students wants to see academic research as a viable career, but we also see the writing on the wall – times have changed and the career trajectories of our mentors may not be applicable to ourselves. The question remains: armed with this knowledge, how can we build on the old and create the new so that the next years of scientific minds may continue to flourish?

Should Postdocs Jump The Academic Ship?

By Elizabeth Ohneck, PhD

 

A recent series of articles on NPR called “Science Squeeze” painted a rather abysmal picture of the current state of scientific research, from lack of funding, to job shortages for young scientists, to stories of scientists “giving up,” leaving academia for other, though not always better, ventures. The article “Too Few University Jobs for America’s Young Scientists” features interviews with a few postdocs at NYU about their current situations and their prospects for an academic future. Their responses are not altogether negative, but are far from resoundingly positive. The article also hints that PhDs may be better off pursuing careers outside of academia, a path that more and more graduate students and postdocs are beginning to take. To get a broader perspective on how the current scientific research climate is affecting the career trajectories of postdocs, I talked with several postdoctoral scientists at varying stages of their careers about their reactions to the NPR series and how the issues presented affect their outlook for the future.

 

Not all postdocs are ready to jump the proverbial ship when it comes to pursuing an academic career, despite awareness of the hurdles ahead. Dr. Randy Morgenstein, a senior postdoc an Ivy League university, pointed out the limited scope of the NPR series, which focused on only a couple specific universities and individuals whose situations were particularly dire, and felt the articles portrayed the academic environment in an overly gloomy manner without actually addressing the overarching flaws in the system. “The articles make a pity party out of 1 or 2 places or people without making me feel the system isn’t working. So overall, I think they might have presented the state of scientific research in this country in too much of doomsday state… A better approach would have been to make me feel bad for society because good scientists are unable to get grants and do research.” He acknowledges, however, the truth of difficulties in obtaining grants and the competition for an extremely limited number of faculty positions. Despite these factors, he is persistent in pursuing a career in academia. “Academic research gives you the most freedom to pursue the research you are interested in. I like that aspect of it and think it is worth the risk to pursue.” When asked how one might overcome the obstacles in funding and faculty position availability, he responded, “I think anyone becoming a PI has to be self-confident almost to the point of arrogance, and therefore think that it’s the other people who won’t be able to get grants.  I do not think I am doing anything special to overcome these difficulties. Same as everyone else, I am trying to publish the best papers that I can, hopefully on a topic that people think is worth funding in the future.”

 

What about those who have successfully made the transition from postdoc to assistant professor, who might provide hope for those postdocs still set on an academic track? Dr. Francis Alonzo III is one such scientist, having recently obtained an assistant professor position at Loyola University Chicago. He chose to pursue an academic career because of his love of science and education, and credits his success to persistence, passion, drive, and curiosity. In addition, he added, “I really just could not see myself doing anything else. Because of that, I knew what my goals were from the start and worked as hard as I needed to get there.” But he feels that the NPR series accurately portrayed the state of scientific research, and this reality of uncertain funding means securing an assistant professorship doesn’t necessarily relieve his apprehension. “I do still love engaging in the scientific process and being involved in training and educating students,” says Dr. Alonzo. “And I still get a lot of joy coming into the lab everyday. However, I am considerably more apprehensive about what the future holds. In particular because I am just gearing up to submit my first larger grants and I have no idea how my ideas will be perceived.”

 

There are, however, many postdocs struggling to find jobs, and many who are turning away from academia in hopes of finding more opportunities. Dr. Bree Szostek Barker, a junior postdoc at the University of North Carolina, originally planned to pursue an academic career, but has recently been looking into possibilities outside of academia. She feels the NPR series actually understated the severity of the problems with funding and the job outlook in academic research. “The articles’ focus on a few universities, namely Baylor and Virginia, makes it appear that this is an issue isolated to a portion of schools/institutions/researchers that overextended during good times,” she said. “Every university and the vast majority of PI’s are feeling this, with the exception of the select few who are immeasurably successful.” The lack of job security created by limited academic positions and uncertain funding resulting from the current system of the academic research sector has pushed her to explore alternative careers. But securing a job in the private sector or a job that is not research-based has turned up its own set of problems; specifically, PhDs and postdocs seem to be missing relevant experience in the eyes of recruiters for these positions. For this reason, Dr. Szostek Barker disagrees with the assertion made in “Too Few University Jobs for America’s Young Scientists” that there are abundant jobs for PhDs outside of academia. “The fact is the number of jobs seeking a PhD with no experience in their industry is low and to pretend otherwise is offensive. And the jobs that do arise are so heavily competed for that the chances of getting the position is extremely slim,” she said, adding, “Unfortunately academia doesn’t count as ‘experience’ for anything except academia.”

 

It seems that the NPR series may have portrayed academic research in too much of a doom-and-gloom state, but also didn’t delve deep enough into the overarching problems in the structure of the scientific research sector. Funding is difficult to obtain, and faculty positions are few. Yet there are success stories to be found, and there are postdocs maintaining a hopeful outlook in spite of the enormous obstacles they face. But the system in which each PI trains multiple successors is unsustainable, and so to overcome job shortages, many postdocs are looking outside of academia for careers. What is not acknowledged in this series is that these non-academic jobs may be equally as hard to come by. Altogether, the consensus is that the system is flawed. But how do we fix the system? More money alone is likely not the answer. What contributes to one’s success on the academic track? Plenty of bright, passionate, confident, motivated scientists end up leaving academia, unable to secure funding, or worn down by the fierce competition, so what factors, both personal and academic, allow some to flourish while forcing others out? And finally, how can we better prepare PhDs for jobs outside of academia? The NPR series has brought these issues to the public eye. Hopefully this exposure will drive further discussion and a search for solutions to ensure a future full of happy, fulfilled scientists and prolific, productive scientific research.

 

Where Would Biomedical Research Be Without Open Data?

 

By Florence Chaverneff, PhD

 

Two major approaches in the study of neuroscience are electrophysiology, which consists in recording electrical activity of cells or cell populations and requires elaborate-looking equipment, and molecular biology, which requires…pipettes. Arguably, most biologists are thoroughly trained in either discipline, as they involve distinct skill sets, thinking process, abilities…My training is in cellular and molecular biology. An electrophysiologist friend of mine once told me (wording might be slightly inaccurate due to unconscious bias): “Molecular biology, that’s all about recipes! You follow the recipe, it works”, opposing it to none other than, you guessed it…electrophysiology. Unsurprisingly, electrophysiology, according to him, is soooo much trickier. Turns out, in practice, molecular biology is not all that straightforward.

 

Had my friend (being no more a wizard than the rest of us) ever actually had to use molecular biology to do his work, he most likely would have realized that it takes much more than following a recipe to obtain usable and reproducible data. The same holds for regular cooking, in that, carefully following recipes in a cookbook doesn’t turn one into Julia Child. That’s where biologists have understood that sharing tips for protocols used in molecular biology for example, can help the community (e.g. Protocol online). Making it freely accessible, providing feedback and a platform to interact. Well, this is sort of the concept of open data. What is open data? According to the Open Data Handbook, it is: “data that can be freely used, reused and redistributed by anyone – subject only, at most, to the requirement to attribute and share alike.” In biology, open databases are either started and maintained by institutions: e.g. UNIProt  by the Swiss Institute for Bioinformatics, Stanford’s SOURCE, or governmental organizations such as the National Center for Biotechnology Information provides the richest source of databases with for example Genbank, Epigenomics, EST and also Prodom. Which biologist, over the course of their career, has never had recourse to open access databases? Probably, very few. And we are all extremely grateful for them. And by open access, I mean, open access. As in, freely available online to anyone with an internet connection. Our work is not only facilitated by these databases, they have become an integral part of biomedical research.

 

The age of the internet has brought about a cultural shift. Sharing is not an attitude that’s associated with the mentality of the research community, where competing for funding, publications and jobs prevails. We compete, that’s who we are. But we are also learning to share information and resources, knowing our work will benefit from doing so. That’s who we have become. Thankfully. Understandably, the sheer existence of some of these databases is due to lack of manpower to analyze huge amounts of data (think big data), hence, the sharing. However, the majority of open databases addresses real needs and has, as sole purpose to benefit the entire community.

 

A parallel can be drawn between open access biological databases and the free online encyclopedia – Wikipedia. A few years ago, I caught a colleague of mine in his laboratory, working on the Wikipedia page of a topic related to his studies. At the time, I didn’t think much of it, being under the misconception that most information on this site was unverified, and that anyone could contribute, regardless of their expertise. My colleague corrected me, pointing to the fact that additions to the site go through a review process and require proper referencing. A while later, I heard a TED talk by Wikipedia co-founder, Jimmy Wales. In his talk, this open access pioneer describes the original concept of Wikipedia where “every person on the planet is given free access to the sum of all human knowledge […] written by thousands of volunteers around the world in many different languages […] managed by an all-volunteer staff”. Wikipedia, is the epitome of open access, particularly under Mr. Wales’ definition. Why is it, then, those individuals who do not get credit or monetary compensation, spend valuable time and effort contributing to such databases? What are their motivations? Are some people simply altruistic? Or does it provide some sort of ‘feel good’ effect? I would say, it’s as simple as that: they do it to benefit, at their level, mankind.