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Keeping up with new scientific literature

Researchers struggle to read everything that comes out in their field. Not surprising, knowing that almost 2.3 million scientific papers were published in 2016. That is around 6,300 a day!

Researchers often have their own routines to keep up with the most relevant literature, usually checking a few critical journals when new issues are published, following known authors in the field, and using online tools like Google Scholar, ResearchGate or Academia.edu. This post is a quick review of a few easy tricks to set up alerts with Scholar, that can make a reading routine much more efficient. Google Scholar is by now the best known and used search engine for scientific literature.

First thing to do is to set up your Google Scholar profile. Visit the Google Scholar site and log in to your Gmail or Google account. Click in the three parallel lines on the top left to open the menu. Follow the instructions of the account setup. Add your articles, areas of interest and verify your email. Add co-authors as this is helpful later to set up alerts.

Once logged in (to Gmail or your Google account) visit the Google Scholar site, and click in the three parallel lines to open the menu.

Scholar allows to set up citation alerts for your own papers, alerts for your entire body of work in just one click. Whenever one of your articles is cited Scholar will send you an email. Usually a paper that cites one of yours has a high likelihood of being relevant to your research interests. To set up this alert, click on “My  profile” on the left side menu and then click on the “Follow” blue button. Select “New citations to my articles”. Done! In this same window select “Recommended articles” too, and that will set up an alert for Scholar’s own assessment of publications that might be of interest to you. These are based on your own papers and the papers that you have saved in your Scholar library. Build  up these two sources to get more relevant alerts.

Researchers usually know several other researchers that work in the same field and they like to follow, read their papers and listen to their talks in conferences. In Scholar is also possible to set up new article alerts for academics in your field. Just search for their Scholar profile and click on the “follow” button. You can choose to follow their “new articles” and their “new citations”, but for highly cited authors be aware the latter might well flood your inbox.

Finally, particular topics and keywords can also be tracked just running a search in Scholar and clicking on the “create alert” link in the menu. This will send you alerts whenever there is a new result for these particular search terms. Choose your keywords wisely!

Recruiting talent in academia

There seems to be a growing consensus in business management discussions that human capital is now the determiner for success, more than strategic planning or even finance/funds available. This looks to apply very well to scientific research organisations where positions seem to be increasingly difficult to fill in. In this post I explore a few ideas around recruitment of talent in academia.

The reasons for the rising importance of talent in organisations may be worth studying separately, to understand what applies to us, but they are a bit complex to deal with just in a few lines. Summarised: the speed of change in our society has increased, with accelerating scientific discovery, technological innovation, social changes, and other changes that apply only to some sectors or regions. Because of this, successful organisations now appear to be the ones that can make quick decisions and adapt to these unplanned changes, as strategic planning is usually not able by itself to prepare the organisations to keep everything under control and be competitive.

Once we realise how important it is to recruit talented people into our organisations, questions arise about the kind of talent that we need or how we find and attract it.

Imagine a new position is going to be offered in your organisation and the first thing you do is probably to prepare a job description for it. When doing it, reflect on what technical skills are actually critical and which ones can be (quickly) learned on the job. A way to do this is to go over extended lists of questions that can be asked in an academic interview, adapt them to our field and open position, and realise which are the few ones, both technical and non-technical, that we want good answers to. Is a good understanding of our niche field, or the handling of a complex equipment a critical skill? Very probably yes, but exactly why? Thinking about the why may allow us to understand better what is that we more importantly ask from a successful candidate.

Not only technical skills are important. The interview and any other interactions with the candidate is a good chance to screen for the right attitude, values and behavioural skills. These are not the same in all organisations or labs and some positions may require good relationship building skills while others more abilities to work independently for instance. It’s a good idea to use the curriculum of the candidate to learn about character. Use the education and work history to ask about the person as a whole, not only about skills but also about what’s important in their life and how they made decisions. Ask question like “Let’s walk through your time at X”, “let’s talk about your role in project/paper Y”, to find out about accomplishments, transition to one role to another, low points, and what the candidate considers more important in an authentic way (this is called chronological interview).

Build a talent pipeline. It can make a great difference to plan a bit in advance and have our network of contacts active for recruitment. We also should be open to adapt to the conditions of the talent we want to recruit. In academia it happens frequently that the time window to hire is quite narrow and the candidates available not as good as we had imagined. Usually when awards are granted new positions need to be filled quickly.

Recruitment of talent can start early.

But then the postdoc we want in our team is not yet available, or we didn’t have the time to receive enough competitive submissions to the job offer. Maybe it’s worth delaying the hiring process a few months and attract the right people even if it means losing a bit of the award budget. Ideally when a position is opened in our lab we would have already two or three names in our head that we would be happy to recruit.

Marketing for scientists – adapting marketing and sales strategies to the management of science

A young researcher experimenting with basic social media tools

I recently was told to read Leveraging the psychology of the salesperson, what seems to be an important insight into sales strategies widespread today. There it is argued that salespersons are more successful if companies manage them as addicted gamblers that are after the thrill of the sale. This is an ‘archetype’ or type of personality called ‘happy loser’ that finds fails rewarding too, as a reminder of the chance to succeed. It seems that this strategy has been adopted thoroughly and intensely by most corporations in the last decade. It was published by Harvard business review in 2006. I dislike this strategy for several reasons, although I can see how it can work in some scenarios.

Anyway, reading that paper had me thinking if this had any use or could be adapted to the marketing of science, the marketing activity of research groups and companies. This idea or ‘archetypes’, new to me, is interesting. What should be the best way to present ourselves to a new research partner? or to a funding body? Surely others have already thought about it. Exactly, there’s a lot of knowledge out there about adapting marketing and sales strategies that work in classical business management situations to the management of science and innovation, an also based around archetypes. For innovative companies there are plenty of documented models and strategies to choose from but it’s more difficult to say what applies to research teams in academia. The starting point or need is that researchers have to explain their ideas and results to colleagues, partners, and funding bodies, actually spending quite a lot of effort on it over the years, so it makes sense to have at least a basic understanding of what drives this activity and how to improve it.

These below are my ongoing notes and links about sales and marketing concepts applied to science, about relationship building, branding, visibility, storytelling, use of general and social media, and so on:

  • Archetypes and diffentiation. Archetypes help create differentiation in the minds of the audience. Differentiation is very valuable in a crowded situation, like most scientific research fields. This video and this post in Nature by March Kuchner about archetypes and common archetypes in the academic workplace. More about archetypes and their use in the life sciences industry by David Chapin here in  this blog post.
  • Design of figures for papers. Scientist also make decisions driven by emotion. The use of particular types of figures in proposals can impact the chance of success. There are three types of figures that appeal to the right parts of your colleagues’ emotional brains.
  • Structure and storytelling in case studies. Case studies are usually used in teaching and also used as a powerful marketing tool. In this latter case they have to be designed for engagement. If used to promote our lab or company, they can’t have the same structures of peer-reviewed papers that are designed for completeness and accuracy. A good structure for a case study with this goal has seven components. More on the topic by same author here.
  • Social media and digital advertising. A innovative biomedical company and even an academic lab, can and should have a social media strategy, even if simple.  Digital advertising can be paid for maximum impact, but organic (free) activity can also bring results. There are three main types of digital advertising tools: (1) search advertising, which is focused around matching ads to user search queries on search engines like Google, (2) display advertising, which is focused around serving ads on websites, and (3) social advertising (paid and organic), which is advertising on social networks like Twitter, LinkedIn, Facebook, Instagram, YouTube and others. (1) and (2) are not very important for academic labs, but (3) can be useful. Having curated social media profiles can be useful to reach new audiences, create new opportunities, target specific types of partners, and in general build relationships and networks. This can increase citations for our papers, invitations to join multi-partner proposals, and build a stronger standing in our communities of interest.

What happens after the enterprise fellowship – RSE Enterprise Fellowship

Of the many ways to launch an innovative new company I think an enterprise fellowship is the best suited to new entrepreneurs with little business experience, like often those arising from universities. These fellowships offer a few months of training, good networking action, and fellows are prompted to assess with new eyes the potential of their company even before is totally formed. They are also very good for the local/national economy, as it seems a good fraction of the fellows stay around to grow their companies or bring their new skills to other local companies.

In Scotland there are a at least two programmes of this kind that I know of: the RSE Enterprise Fellowship and the Saltire Fellowship.

How the fellows fare after the fellowship?

In conversations about fellowships, challenges and prizes to support the creation of new innovative companies the question often comes about the past fellows and winners – where are they now?

The RSE programme was established in 1997 and has supported about 240 graduates so far. It has enough history to study how these kind of entrepreneurs continue their careers. I had a quick look at the bits of online information about past fellows that the programme has, and these are the results:

Figure 1: Fellows with vs without company already set up – 77% historical average, higher in the last few years.
Most of the fellows go into the programme with a company already set up (Figure 1). There’s no information available about the stage of development of the companies although it is assumed that most are at very early stages and some are counted even as pre-seed or concept stage companies.

Figure 2: Fellows with company set up before or during the fellowship, by origin of fellowship (Scottish Enterprise, BBSRC and SFTC
There are small differences in the percentage of fellows with a company already set up depending on the origin of their fellowship. BBSRC fellows seem to have a higher historical average than Scottish Enterprise fellows (Figure 2), although in any case a very clear majority of fellows have a company set up. This in theory may help personalise and enhance the learning experience, but obviously there is no information on the base data to conclude this.

Figure 3: Current employment situation of the fellows by year of fellowship.
After the fellowship, there is a slow transfer of fellows from their own start up companies to other companies in the field or to academia and other government related institutions (Figure 3). It is quite remarkable I think, compared to the experience of other entrepreneurs, how many RSE fellows continue to work in their companies after several years, meaning that they remain engaged with the local economy and also that the companies still exist. There is around a 35% chance after as long as 7-8 years that a fellow that had the fellowship with a company set up remains with that company, which is a good rate I think.

Figure 4: Current employment situation of the fellows by origin of fellowship.
Looking at the origin of their fellowship, there are some noticeable differences on the current place of work of the fellows (Figure 4), as the BBSRC fellows seem to transfer noticeably more than the rest into universities and government institutions.

This first glimpse at life after the RSE fellowship it’s quite encouraging for the strength of the programme. There are other complex questions to answer however, that would need maybe to conduct a survey of fellows, of challenges they have encountered and solved, and so on. Every story is certainly different and a learning source on its own, that requires more than a few numbers and graphs to conclude anything more specific about the virtues of the programme and how to make the most of it.

Paper citations in patents as a business development tool

Last March this year Redtransfer organised a meeting for Spanish tech transfer managers in Madrid  where colleagues presented their views and experiences on several topics. Pedro Fernandez‘s talk caught my attention. A new, at least for me, use of patent databases as a tool to get leads for networking and commercialisation strategies.
The idea is to use the capability of some patent search engines to search papers for citations of patents, to check out our own papers, or the papers of a person of interest. When someone cites your paper in a patent you have a good argument to contact them and explore a partnering interest.
I have gone over the papers of the researchers I work with and indeed the tool has brought up a few surprises that are worth checking. The main drawback is that citation of papers in patents is not widespread and many times you will find none or very few leads even for papers that have good scientific impact.
All in all the tool can uncover interesting pieces of information of your research, and albeit with limited success in general, it can be a useful tool for business development and networking of an established research profile.
How to do it

Go to lens.org and choose the “Scholar” search option in the search field. Run a search and find the paper or papers that you would like to check. A search with author names is usually a good way to get several relevant papers in the same search. Then check their linked patent citations for leads!

Talking to investors

Technologies developed in Academia usually follow two paths towards commercialisation: (i) they get licenced to an established company or (ii) they are the basis of a spinout company. In the second case the spinout is usually initially led by the academic researchers, and it becomes critical quickly to recruit management expertise, funding and market knowledge.

We have been figuring out the opportunity to spinout the bone regeneration technologies developed in our labs in Glasgow. We’ve had interactions with a few different professionals working in one way or another in the biomedical market, and we have seen an interesting and valuable side of the conversation when talking with potential investors.

The interaction of investors and the spinout team can be not only about presenting a novel technology and the plans to make it to market. It’s also a chance to learn from them, learn what they know about the target market of the spinout. Most investors are specialised and know well the market they operate. We can then use the information gathered to better adapt ongoing or future R&D plans towards applications with more chances of success.

For instance, in the lab in Glasgow we have discussed with investors our planned bone grafting applications and pre-clinical models and have as a consequence looked into clinical indications where our technologies can make a more significant improvement, compared to current available treatments. Our techs work very well in the animal models that we have carried out so far, but approved clinical products also work well in those models. The comparable clinical outcomes, even with a somewhat cheaper price, may make it difficult for the clinician and health provider to risk a change. In conclusion, we are planning development for indications and relevant pre-clinical models that address bigger challenges in terms of clinical outcomes, indications with available products in the market providing a less satisfactory solution.

As a way to start this kind of conversation the spinout team can ask about the type of products and techs that are getting investment in the field. Companies to look at that we can study to learn what they are doing right? What are the segments in the market, the end-users, that are drawing attention. For instance, in the biomedical field, we can ask about the indications that are of their interest. Our technologies in Glasgow are primarily focused on bone regeneration so we want to learn about the orthopaedic applications that could use our technologies.

We can also ask investors about feedback on our commercialisation strategy, check with them if the business model we have devised is the one that makes more sense in the current market, and discuss the timing of spinout regarding ongoing R&D, especially if there is a big gap and risks between where the technology is at the moment and where it needs to be before it is commercialised. This is particularly relevant in the biomedical field, where regulatory issues are very important and can take a long time and large investments and be unsuccessful nevertheless.

Creativity in programs to foster innovation from Academia

In the past I have been involved in a few small or medium-sized initiatives to fund research or innovation. Policy makers that design these programmes have to balance the urge to guide the activity towards what they think it’s the right way to spend the money while allowing for the freedom and incentives needed to engage a sufficient number of academics. Actions that fund Academia and Industry collaborations struggle the most with this. One can find from very flexible frameworks of collaboration to specific, and creative, actions that fund interactions between university researchers and companies.

Below there’s a list of a few calls and programmes from UK Research Councils or internal university funds that support actions in direct collaboration with industry or towards spinning out and commercialising technology.

Centres for Doctoral Training (EPSRC)
CDTs are one of the three main ways by which the EPSRC provides support for doctoral training. The other routes are the Doctoral Training Partnerships (DTP) and Industrial CASE Studentships (ICASE) and basically allow more or less industry involvement and discretion in choosing the strategic focus of the PhD. In CDTs one or several universities together with industrial sponsors supervise students (at least 10 per year for 5 years) all focused in one of a number of priority areas of national strategic interest. Industry needs to finance about 20% to 40% of the total cost of the studentships. The EPSRC defines what are the priority areas of research but gives flexibility on the models of collaboration between industry and academia.

Flexible Talent Mobility Account (BBSRC)
The FTMA supports Academic/Industry secondments and collaboration, as a two way people exchange. It covers the expenses of a secondment (not research) and it’s open to research students and postdocs. Awards of £5k-10k expected, with a duration of 1 week to 3 months.

Industrial Partnership PhDs (UofG, College of MVLS)
Short Term Industrial Projects, to develop solutions to grow business. 3 month placement, for a laboratory or desk-based project to support business needs.

PhD in Precision Medicine (Medical Research Council)
A 3.5 – 4 year PhD with industry, to increase collaboration with industry and gain skills in two distinct research cultures. Includes a 3 month placement with industry.

Proximity to Discovery (Medical Research Council)
Funding for engagement with industry (secondments or networking). Awards of £2k-£6k. Does not support industry or research costs.

Confidence in Concept (Medical Research Council)
Translation of fundamental science. Preliminary translational work. Diagnostics and therapeutic projects. Advancement of the path to commercialisation. Awards of £50-100K. Requires match funding (monetary or in-kind). Project expected to last 6-12 months. Reported research outcomes upon completion. Not for bridging funds or IP costs.

Excellence with Impact (BBSRC)
Stakeholder engagement. Projects in line with BBSRC strategic plan and can include: Product design, engagement with stakeholders, market intelligence. Awards of up to £5k assessed on case by case. Awards >£5k are panel assessed. Not for public engagement, staff or industry costs.

RSE Enterprise Fellowship overview (Royal Society of Engineering)
RSE Enterprise Fellowships enable promising science and technology researchers to develop into successful entrepreneurs. Awardees get to focus solely on refining their business ideas, whilst receiving one year’s salary, expert training in entrepreneurship and access to mentorship from business Fellows of the RSE and other successful entrepreneurs in the business community.

Impact Acceleration Accounts (several Research Councils)
UK Universities usually hold Impact Acceleration Accounts (IAA) from the BBSRC, EPSRC and ESRC, that aim to increase, advance and accelerate the achievement of impact from research council’s funded projects. The IAAs supports a range of Knowledge Exchange (KE) interventions with a focus on small-scale investments that pump-prime wider KE activities and impact generation. The IAAs typically provides two core funding streams to build on previous research council funded projects, proof-of-concept, and collaborative development.

 

All the skills for a successful career in research, or after research.

The path that postdocs tread is narrow, and the drop is shear and very high. Does this song ring a bell? Early career researchers in most countries live in a competitive environment where you are supposed to look for the legendary permanent position, usually as teaching staff. So what skills do you need to excel at, what makes you successful in Academia nowadays? But also, what if you look for greener pastures elsewhere, will you be prepared?

Over the last decades the postdoc group has kept on growing to the point that they now constitute the largest staff grouping in most research oriented universities. Academic tenure tracks, positions that allow independent research, haven’t increased in parallel. In the UK, maybe an extreme case
with a huge postdoc group, only about 4 out every 100 postdocs who come up on the academic rollercoaster are destined ultimately to stay in university; see this Nature paper for more details on the numbers.

So the question is not only what do you need to do as a postdoc to stand out and get a permanent position, but more, what can you do to get a good job when you leave the academic path and join one of the many careers available to researchers and managers with research experience.

YOU NEED TO MANAGE PRIORITIES AND YOURSELF

Focus. What is your top priority as researcher? You have a good chance of getting a fellowship or grant if you can produce original independent research. This research should be something that is closely linked or derives from your current employment. You most often have been hired as a postdoc to fulfil the goals of a research project, with a PI that has a research line progressing in said project. Do your goals align? Both your goals as a hired postdoc and as an early career research should be well aligned. What is that you are doing that qualifies as original independent research? You should be able to claim responsibility and leadership of a goal as a hired researcher that also qualifies as your independent research. If you don’t have an answer to this, you should drop everything and figure out what the answer is. Having an answer here forces clarity and focus. Not having an answer is dangerous – it guarantees that you’ll be working on unimportant things and wasting your precious time.

There will always be an endless stream of things to do. It’ll be tempting to do whatever is easiest, or most fun, or most familiar. But this is a trap that will screw you over in the long run. It’s better to make small progress on your most important thing than to finish lots of tasks that don’t actually move the needle.

Manage your goals as researcher. Make your goals and targets precise. You most certainly are part of a team, with a line supervisor that manages probably more people like you within related projects and lines of research. What is that you own in those? Ideally, it should be a metric that is tied to your top priority. If it isn’t, you should discuss it with your PI or boss and establish what your top priority really is. Have a framework plan for your goals as researcher, with needed experiments and so on, that shows what you are accountable for and where you can measure progress. Once you’ve settled on a metric you’ll want to make sure that you know as much as possible about how to make a positive dent in this metric. If things are vague or ambiguous, set aside time to make them precise. Don’t work with ambiguous plans – it’s a recipe for distraction. In general, learn to identify and clean vagueness in your own thinking, writing and communications.

Dominate your area of responsibility. You want to be really good at the thing that you’re supposed to be handling. Obvious, but sometimes it can be tempting to try to do a bunch of secondary things. Keep the main thing the main thing. Select and read papers on your field. Daily. Ask other people about techniques, access to equipment, about what they know; see point below about communication.

Be honest about what you don’t know. Be honest with yourself, most importantly. Practice communicating your uncertainty in a constructive, inviting way. It’s refreshing to be around people like that. Set aside time for learning. When you find good content about your field, bookmark it for later, and go through it at a regular interval. Weekly is pretty good, 30 minutes daily first thing in the morning is even better. If you’re doing a bunch of reading and learning, share your findings with someone else. This helps you understand. Implement your learnings. Set monthly and quarterly goals.

Have a schedule and respect it. Start by making really small, simple plans for the day and then get them done. Write down something that you can do in 5 minutes, then do it, and scratch it off. Do this over and over and get better at it.

Reflect and review on your past work. This helps you improve by figuring out what worked, what didn’t, what went well, what didn’t… you should be doing this regularly, on your own. Not everyone takes detailed notes and reviews them, but it pays off to be systematic and disciplined about this. Take time to use your lab book as an efficient tool for this.

Articulate your processes. This is helpful at multiple levels. First of all, simply taking something out of your brain and putting it on paper is an incredibly useful habit. It forces you to figure out what you really mean. What are you trying to achieve? How do you make decisions? When you articulate your processes, you can analyse them. You can look for weak points and improve them. It’s like watching a replay of yourself. You can share your processes with others, and get feedback. Again, use your lab book for this as much as possible.

You are in charge of yourself. Even if you have a great PI, you ultimately need to take responsibility for your own learning, your own execution, your own growth. It is common to spend the first years as postdoc in a sort of reactive mode (rather than proactive). A great manager will give you valuable targets, advice, context, structure and so on, but this can spoil you a little, because it is only you who can set loftier goals for yourself, and meet them. Nobody is going to push you as hard as you can push yourself, challenge yourself in terms of pushing yourself out of your comfort zone.

Take care of your mental and emotional health. Your work is going to fill a large part of your life, so it’s a good idea to do it well, to take it seriously, to enjoy it, to challenge yourself and so on. But if you find yourself getting burnt out, depressed and so on, don’t lie to yourself about it. You are the most important person in your life; take care of yourself. What makes you happy? 

YOU NEED TO COMMUNICATE WELL

Improve your writing skills. Establish a good writing practice early in your career. Improve your grammar, punctuation, proofreading and editing skills. Learn what you need to write an excellent grant application or paper.

Communicate effectively, early, and often. Show your work. Share your sketches and drafts. Early-stage feedback is much more useful and actionable than late-stage feedback. Sometimes simply asking a few questions or chatting about something in an open-ended way can lead to superior ideas and solutions that you didn’t expect. Ask clarifying questions. Everything is vague to a degree you don’t realize. Make an effort to make things precise. Being clear about exactly what is expected is very important. People having different expectations, different understandings of a situation, interpreting vague instructions differently, etc – all of these are sources of lots of friction and frustration. It’s worth spending time and energy making sure everyone is aligned on whatever you’re doing.

Practice speaking, give talks, presentations, etc. Communicating what you know with other people is a powerful skill. It will make you a better professional. And you’ll feel lighter at work, too, because the act of teaching and sharing makes you more comfortable and confident in your area of expertise. Build your confidence by practising often. Learn strategies to control nerves, make the best use of your voice and pace your delivery.

Lean on your team; ask for help. Real life isn’t a closed-book examination, where you have to get everything done right yourself, in isolation. Ask for help if you need it. This may vary a little depending on your lab culture and personality. Some people might be intrusive and demanding. But I generally get the sense that smart, respectful people tend to err on the side of caution – not wanting to interrupt others. That said, when you ask for help, be simple and clear about it. “Hey, when you have a moment – I need some fresh eyes to look at my slides for a few minutes and offer copy suggestions”. Don’t interrupt people with open-ended non-requests, that’s disrespectful. Give people a very clear ask, and sometimes they’ll even be grateful for the brief distraction and the chance to help move something along.

Be encouraging and supportive to others. It makes a difference. It can make all the difference.

YOU NEED TO CONNECT WITH PEOPLE

Always be networking. We are social animals, a society made of people; build relationships with them. Meet people who are in similar roles as you, doing work similar to what you’re doing. This will help you do your job better. And it’s also quite pleasurable and heartening in its own right, for its own sake. Most people will tell you things in person that they won’t ever write in an email or post online – and these will be some of the most powerful, useful things for you to know. They can open doors for you. They can set things up for you. Sometimes the problem you’ve been struggling with for weeks or months has a simple solution, and that solution happens to be inside somebody’s head – that you can access for the cost of a beer or coffee.

Meet also people who are in different but complementary roles to you. Are you a biomedical engineer? Meet with a medical doctor and talk about the clinical current practice of what you are doing in the lab.

Make a list of people you’d like to work with and learn from. Figure out how to engage with them. It makes sense to build relationships with people for the long haul. It’s good to know good people even if you aren’t necessarily going to make a career in a particular field.

Build and manage your public and online profile. Update and take care of your profile page at your institution. Build your Research Gate, Google Scholar, LinkedIn profiles. Discover the power of social media for communicating research and engaging with the public online. Use twitter, a personal or institutional blog to share your ideas and accomplishments. Engage with mass media and popular science outlets to help increase the reach of your research and the chances of linking to other opportunities.

YOU NEED TO IMPROVE YOUR UNDERSTANDING OF A CAREER IN RESEARCH

Learn the basics of team and project management. Learn what it takes to be a successful leader and influence others towards a common goal or purpose. Learn how to plan resources and time for a project, how to plan for risks, how to decide to kill or continue with a project. Even as a postdoc this will greatly help you when planning and executing your tasks, from daily work to multiyear goals.

Understand how research results are translated to commercial applications in your field. Sharpen your commercial awareness. Learn how executive teams in companies manage their research pipeline, what a newly formed start-up company or an entrepreneur want to see to agree to bring your exciting ideas to life.  Learn about regulations and standards applicable to your field. On top of advancing knowledge, is your research likely to solve a problem, have an impact on other people’s life? Impact statements are of growing importance in most grant applications.

Find out about the research policies and support structures that affect you. Where does the money come from at your institution? Who are the research support office teams in it? Most academic institutions have one or several teams to support you with planning and managing research funding proposals and may offer training that is specific to the type of funder you are likely to interact with. Find out about your country’s funding programmes, European funding, contract research and so on.

Predicting the future

It is very useful to predict the future, but difficult too. And yet, for small and big things, humans are always doing it! Our brains are keen to detect or imagine patterns and deduct what comes next.

Researchers, innovation managers, also have to constantly make decisions trying to figure out the future. A good strategic manager will look to choose the lines of research, the products, the markets, with more chances of success. I myself can’t help doing it just for fun, and I like to imagine how the future will be for the most intriguing breakthroughs in science. This is usually about rather short term predictions, like what clinical applications or diseases will be favoured in a biomedical research funding call. Long term predictions are much more difficult to imagine, let alone to guess right. Anyway I realised, as many other before no doubt, that the standpoint that helps to make these predictions more robust and systematic is the human perspective, not the technological perspective. If we focus on predicting technological or scientific breakthrough we will usually fail routinely. There is actually a tradition that fills many magazine pages and media of all kinds that makes little effort to understand the state of the art of basic science, and makes predictions using the recurrent theme where future technology will be ridiculous applications of the technology already available, at last used to make our daily lives better, in pretty meaningless ways. We are going to have robots that make our favourite sandwiches and order from the supermarket when the cheese runs out, microwave ovens with voice recognition. We could, but we don’t really need these things so they won’t be really mainstream even if the technology exists to make them. Even if these pointless little things do happen, most people won’t care.

That’s not the story of the future. The human perspective is what determines the use of new science and tech, and the key idea for the prediction of the future is that our quest for knowledge keeps fundamentally close to what are our human needs, and it will keep doing so. It has changed and will conceptually change communication and warfare, architecture and transport, education, food and medicine. It will change how we evolve as society. These things are far more complex and harder to predict, so focus is given to predictable improvements in technology that solve problems that don’t really exist, and even if they do they don’t matter much. Good predictions come from understanding how a scientific breakthrough will impact how we handle our fundamental human needs.

 

Technology Readiness Level (TRL) in biomedical development

The team in Glasgow has started to prepare a proposal for the upcoming NMBP-22-2018 call (a call for research projects under the EU H2020 programme) and we noticed that under scope of the projects in the call description it says that “Activities should start at TRL 3 and achieve TRL 5 at the end of the project.”
We know that TRL levels 3 to 5 in a biomedical research is from a proof-of-concept in vitro to animal models / pre-clinical trials completed, but different institutions have slightly different definitions. The call is quite precise on what levels expects at start and end of the project, so I have been looking for more details references of TRLs applied to biomedical research to see if we can better frame the expected goals for this call.

I found this great blog post that reports work by the US Army Medical Research and Materiel Command to develop TRL descriptions for the development of medical devices. The nine Medical Device TRL descriptions developed by the MRMC as they apply to medical devices are copied below. The TRL definitions pertain predominately to Class II and Class III medical devices that are subject to approval via the Premarket Approval (PMA) process.  Devices that are subject to approval via the 510(k) process (Market clearance; generally limited to certain Class I and Class II devices) may not require all of the studies described, and only require an Investigational Device Exemption if human studies are necessary.

These definitions are provided only as an example. If you choose to incorporate the concept of TRLs to product development approach, you need to tailor these descriptions to reflect your organization’s system engineering processes, culture, product line, and current regulations and standards

TRL1. Lowest level of technology readiness. Maintenance of scientific awareness and generation of scientific and bioengineering knowledge base.  Scientific findings are reviewed and assessed as a foundation for characterizing new technologies.  TRL 1 DECISION CRITERION:  Scientific literature reviews and initial Market Surveys are initiated and assessed.  Potential scientific application to defined problems is articulated.

TRL2. Intense intellectual focus on the problem with generation of scientific “paper studies” that review and generate research ideas, hypothesis, and experimental designs for addressing the related scientific issues. TRL 2 DECISION CRITERION: Hypothesis(es) is generated.  Research plans and/or protocols are developed, peer reviewed, and approved.

TRL3. Basic research, data collection, and analysis begin in order to test hypothesis, explore alternative concepts, and identify and evaluate component technologies. Initial tests of design concept, and evaluation of candidate(s).  Study endpoints defined.  Animal models (if any) are proposed.  Design verification, critical component specifications, and tests (if a system component, or necessary for device Test and Evaluation) developed.  TRL 3 DECISION CRITERION:  Initial proof-of-concept for device candidates is demonstrated in a limited number of laboratory models (may include animal studies).

TRL4. Non-Good Laboratory Practice (GLP) laboratory research to refine hypothesis and identify relevant parametric data required for technological assessment in a rigorous (worst case) experimental design. Exploratory study of candidate device(s)/systems (e.g., initial specification of device, system, and subsystems).  Candidate devices/systems are evaluated in laboratory and/or animal models to identify and assess potential safety problems, adverse events, and side effects.  Procedures and methods to be used during nonclinical and clinical studies in evaluating candidate devices/systems are identified.  The design history file, design review, and when required a master device record, are initiated to support either a Premarket Notification (510(k)) or PMA for Medical Devices. TRL 4 DECISION CRITERION: Proof-of-concept and safety of candidate devices/systems demonstrated in defined laboratory/animal models.

TRL5. Further development of selected candidate(s). Devices compared to existing modalities and indications for use and equivalency demonstrated in model systems.  Examples include devices tested through simulation, in tissue or organ models, or animal models if required.  All component suppliers/vendors are identified and qualified; vendors for critical components audited for Current Good Manufacturing Practices (cGMP)/ Quality System Inspection Technique (QSR) compliance.  Component tests, component drawings, design history file, design review, and any master device record verified.  Product Development Plan drafted.  Pre-Investigational Device Exemption (IDE) meeting held with Center for Devices and Radiologic Health (CDRH) for proposed Class III devices, and the IDE is prepared and submitted to CDRH.  For a 510(k), determine substantially equivalent devices and their classification, validate functioning model, ensure initial testing is complete, and validate data and readiness for cGMP inspection.  TRL 5 DECISION CRITERION:  IDE review by CDRH results in determination that the investigation may begin.  For a 510(k), preliminary findings suggest the device will be substantially equivalent to a predicate device.

TRL6. Clinical trials conducted to demonstrate safety of candidate Class III medical device in a small number of humans under carefully controlled and intensely monitored clinical conditions. Component tests, component drawings, design history file, design review, and any master device record updated and verified.  Production technology demonstrated through production-scale cGMP plant qualification.  For 510(k), component tests, component drawings, design history file, design review, and any master device record updated and verified.  Manufacturing facility ready for cGMP inspection.  TRL 6 DECISION CRITERION: Data from the initial clinical investigation demonstrate that the Class III device meets safety requirements and supports proceeding to clinical safety and effectiveness trials.  For a 510(k), information and data demonstrate substantial equivalency to predicate device and support production of the final prototype and final testing in an operational environment.

TRL7. Clinical safety and effectiveness trials conducted with a fully integrated Class III medical device prototype in an operational environment. Continuation of closely controlled studies of effectiveness, and determination of short-term adverse events and risks associated with the candidate product.  Functional testing of candidate devices completed and confirmed, resulting in final down-selection of prototype device.  Clinical safety and effectiveness trials completed.  Final product design validated, and final prototype and/or initial commercial scale device are produced.  Data collected, presented, and discussed with CDRH in support of continued device development.  For a 510(k), final prototype and/or initial commercial-scale device are produced and tested in an operational environment.  TRL 7 DECISION CRITERION:  Clinical endpoints and test plans agreed to by CDRH.  For a 510(k), information and data demonstrate substantial equivalency to predicate device and use in an operational environment, and support preparation of 510(k).

TRL8. Implementation of clinical trials to gather information relative to the safety and effectiveness of the device. Trials are conducted to evaluate the overall risk-benefit of using the device and to provide an adequate basis for product labeling.  Confirmation of QSR compliance, the design history file, design review, and any master device record, are completed and validated, and device production followed through lot consistency and/or reproducibility studies.  Pre-PMA meeting held with CDRH.  PMA prepared and submitted to CDRH.  Facility PAI (cGMP/QSR/Quality System Regulation (QSIT)) completed.  For 510(k), prepare and submit application.  TRL 8 DECISION CRITERION:  Approval of the PMA [or, as applicable, 510(k)] for device by the CDRH.

TRL9. The medical device may be distributed/marketed. Post marketing studies (nonclinical or clinical) may be required and are designed after agreement with the FDA.  Post marketing surveillance.  TRL 9 DECISION CRITERION:  None – continue surveillance