Management of (big) research teams

Ideas to successfully manage a team of researchers, and what success means in this context.

Some academic research teams are standalone, usually embedded in university departments, while others are part of research institutes or other structures with shared goals. Most teams are rather small, with an average (for biology research groups in the UK in 2015, from this reference) of around 7 members including staff and students. Published analyses of productivity of research groups suggest that small to medium-sized groups are more productive (same reference as above).

However, groups of much bigger size exist. There are not many, but groups of 30, 40 or even 100 members, with one PI, exist. They might have competitive advantages given the right conditions, or maybe they are just the unavoidable statistical outliers of an imperfect funding system. In any case, because of their oddness, learning about the way they are run could be useful for the smaller groups. The basic premise behind this post is that a big research group that has survived as such for some time is probably efficient and noteworthy in the way it’s managed. Their experience can be useful for smaller groups and also for created structures like research institutes that are in several ways similar to big research groups.

In connection with this, the existence of very big research groups puts to the test the definition of their productivity. In particular, it seems difficult to measure the role of PIs as teachers and mentors, and the contribution that post-docs and PhD students make in careers other than academic research. Additionally, one can often see examples that high productivity needs more than scientific talent, and group culture for instance has a big role in how productive a group is in the long term.

Recruitment. Really big research groups first grow to an intermediate size because of one or several PI that are able to gain funding while they employ talented people who are also successful in bringing in more funding, supervise students and so on. It is very important how the recruitment formal and informal processes in the group work, how the PIs and the group members are able to identify and attract other researchers with great talent and team building skills, and also with a same shared research vision. I believe this is the single most important factor for the creation of a big group, i.e. a PI with a remarkable scientific vision that also happens to be good at recognising talent and attracting it. This is also critical for small groups that while remaining small survive for a long time. Other pieces of the puzzle might be not in place but this is always quite outstanding in the big groups I have looked into.

In-house support. All big groups seem to have dedicated support staff other than the support staff at departments, schools, university services, that the group manages to hire and maintain over the years. Roles include project management, scientific coordination, laboratory management, help with proposal writing, financial administration, engagement/impact, business development, and others. It’s difficult to say how important this is for a group, but big groups that have been in place for a long time all seem to have a highly profesional support structure within the group that typically comprises of around 8-10% of the total group staff. Small sized groups might take advantage of this strategy as well, and should consider to budget support staff in their proposals.

Organisation of research activity. The group is formally or informally a combination of several research teams, each with one or several team leaders. The team leaders coordinate research activity within the team and ideally also manage the career aspirations, training needs, etc. of team members. One group in the UK asks all team members to “make a one page summary every two months describing their work, goals, collaborations, problems, & tasks with times. A key part of the OPS is that list the time left in the group, match this against their tasks, career aspirations”.

  • Team meetings. Team meetings of one kind or another are usually weekly. Some groups have a meeting with the whole group weekly and another with only the smaller team also weekly. One to one meetings with the PIs or team leaders are also usually planned (every week, every two weeks, monthly… ) and sometimes upon request, although I think most groups / PIs in reality have only a guidance in place and usually attend requests as they happen.
  • Shared knowledge. Additionally to group meetings where ongoing work is presented and discussed, most groups usually have some kind of shared folders, group server or intranet, with different levels of access, where papers, awarded and rejected grants, raw laboratory data, presentations, meeting notes, and so on, are available. If managed properly this can be a great tool to teach students how to write, analyse and present information up to a high level.

Building group culture. A group, big or small, that openly discusses career aspirations of its members, that has a collaborative environment, that teaches not only the science but also how to be professional, transparent and accountable, has all the chances to be most productive in the long term. Its members are productive while in the group and also maintain productive links after leaving and moving to other groups, industry, or other fields altogether.

  • Solving disputes. Groups with a good culture have figured out how to best deal with problems between members. This depends on the PI personality and social skills, also on the team members’. The same protocols may not work well everywhere. In general, PIs that behave in a professional and transparent manner, that have empathy with personal life situations, that admit and correct mistakes, that do not let grudges or jealousy between team members unanswered, set an example that team members follow. Groups that for whatever reason don’t resolve disputes are bound to have mediocre collaboration within the group.

Collaboration with other research groups. Bigger groups seem to have more research partners in academia and in industry in particular. The ratio of partners per team member is probably not that different, but bigger groups have a critical mass that allows access to networking and industry leads that are more unusual to see in small groups.

Want more? There are many several good resources to learn about research group management. Here, to choose just one, I recommend a 1983 book ( High Output Management by Andy Grove) actually not focused at all at research groups, but at team management in general. This is an excellent book to learn about delegating, organising meetings, the critical importance of the team’s culture, leveraging one’s tasks to maximise the output of the team, monitoring/evaluating with indicators, and more. This summary is a good resource.

To finish. Should all teams follow the same best practice? Absolutely not. Your group might be better off doing some of these and some other different stuff. The aim of this post is to explain how most big groups do it and what could be useful to groups of all sizes.

In vitro models of tissues. Key industry players in 2021.

Clinical trials are the final step to demonstrate if a new drug is safe and works. Before testing on humans, drugs usually pass numerous preclinical studies. Sometimes a compound seems to be effective in its therapeutic function and non toxic in a preclinical model, but then it fails to perform equally in humans. Actually, it happens most of the time. Statistics from the year 2000 to 2015 [1] show that the average success rate for all drugs and vaccines is only 13.8%. Oncology has an astonishing low 3.4%. Companies spend a lot of money only to fail during clinical testing. And success in this case just means regulatory approval, not automatically that a drug works well, it may be because there aren’t any good alternatives. Trials fail for diverse reasons [2]. Most times failure can be associated with deceptive information from preclinical studies.

The collaboration between biologists and engineers, in academia and in industry, is blooming with new in vitro models of tissues and organs that can improve our understanding of disease and physiology [3-5]. These systems arise fundamentally from the availability of new protocols to produce induced pluripotent stem cells (iPSCs) and differentiate them into several cell types, and from a better understanding of cell culture in 3D microenvironments. They themselves provide new strategies to understand extracellular matrix (ECM) functions, cell-to-cell and cell-to-ECM interactions, matrix mechanical properties in each tissue or pathological condition, growth factor and other molecule-mediated mechanisms, that individually or together can lead to changes in cell phenotype and alterations in drug response.

Organoids and other in vitro models are showing that they can be excellent functional models of human disease and of normal non-pathological function. Research to produce humanised in vitro systems that more closely recapitulate native tissues has an immediate application in making drug discovery more efficient: it improves results of current in vitro methods to screen for drug candidates, allows testing high numbers of molecules, and generally avoids the use of animal models. A different application is personalised medicine and toxicology testing, where in vitro models of our own organs can be used to predict the effect of a particular drug on us, or identify which drug from a cocktail is causing an adverse event.

Recreating complex tissue functionality at microwell or chip scale still remains challenging, but there is a growing number of companies that develop and already offer advanced human in vitro models to support drug discovery and toxicology testing. This is a selection of market leaders and emerging stars (alphabetical order):

BioIVT (USA) – https://bioivt.com. Provider of biological samples including human and animal tissues, cell products, blood, and other biofluids. Services from target and biomarker validation, phenotypic assays to characterize novel therapeutics, to in vitro hepatic modeling solutions. Focus on  hepatic modeling solutions. Supplier of ADME-Tox model systems, including hepatocytes and subcellular fractions.

Biopredic International (France) – https://www.biopredic.com.  Initial focus on primary hepatocyte cryopreservation, now offers the isolation, production and distribution of fresh and frozen human and animal biological products, including tissues, primary cells, cell lines and reagents. Founded in 1993 from a technology transfer of INSERM.

Cellesce (UK) – https://cellesce.com. Bioprocessing technology for the expansion of human-derived cancer organoids. Founded in 2013 on expertise from the University of Bath and Cardiff University.

Crown Biosciences (USA / UK) – https://www.crownbio.com. Preclinical efficacy models, both in vitro and in vivo testing services, for drug discovery in oncology, inflammation, cardiovascular, and metabolic disease. Multinational company, part of JSR Life Sciences since 2018.

Cyprio (France) – https://www.cyprio.fr. Expertise in physicochemistry, liver biology and drug screening. With proprietary technology for the fabrication of spheroids. Created in 2017 at ESPCI Paris.

DefiniGENhttps://www.definigen.com. Human induced pluripotent stem cell (hiPSC) derived hepatocytes, intestinal organoids and pancreatic beta cells. Created in 2012 on results (OptiDIFF platform) from Ludovic Vallier lab at the Wellcome–MRC Cambridge Stem Cell Institute.

Emulate (USA) – https://www.emulatebio.com. Organ-on-a-chip technology for liver, kidney, intestine, brain, and lung. With multicellular configurations, primary cells, relevant ECM components, hardware and software apps. Created around 2013 as a spin-out of Donald E. Ingber lab at Wyss Institute / Harvard University.

Hubrecht Organoid Technology (Netherlands) – https://huborganoids.nl.  Organoids from epithelial tissue derived adult stem cells (ASCs) and related assay services, for applications in cystic fibrosis, cancer, immuno-oncology, toxicology, infectious diseases and other indications. Founded on results from Hans Clevers lab at the Hubrecht Institute for Developmental Biology and Stem Cell Research (KNAW).

Hµrel Corporation (USA) – https://hurelcorp.com. “Microlivers” from self-assembling co-cultures of primary cryopreserved hepatocytes with a non-parenchymal (stromal) cell line.

Kirkstall (UK) – https://www.kirkstall.com. Hardware platform to build organ-on-a-chip type of systems, based on interconnected cell culture flows. Established 2006 initially with technology from the University of Pisa.

Mimetas (Netherlands) – https://www.mimetas.com/en/home/. Microfluidic culture plates for organoids and spheroids. Related services and protocol for some in vitro models. Founded in 2013 in Leiden, the Netherlands. Now over 100 employees in four sites in the Netherlands, USA, and Japan.

STEMCELL Technologies (Canada) – https://www.stemcell.com/. Multinational biotech company with products and services for academic and industrial research, including reagents and culture media kits for the culture of organoids (kidney, intestinal, lung, forebrain) from human stem or primary cells. The intestinal organdie kit is developed with licences from Hubrecht Organoid Technology.

OcellO B.V.  (Netherlands) – https://ocello.nl. Cell line-derived spheroids and organoid models grown in matrix embedded 3D cultures. Patient derived xenografts, tumoroids, models, for oncology, immuno-oncology, inflammation and cystopathy indications. Drug discovery screening services. Created in 2011 on technology developed at Leiden University.

Qgel (Switzerland) – https://www.qgelbio.com. Patient derived organoids based on synthetic hydrogel technology. Cancer, colon, lung, breast, and pancreas applications. Founded in 2009 in Lausanne, Switzerland.

References:

[1] Chi Heem Wong, Kien Wei Siah, Andrew W Lo. “Estimation of clinical trial success rates and related parameters.” Biostatistics, Volume 20, Issue 2, April 2019, Pages 273–286. DOI: 10.1093/biostatistics/kxx069

[2] David B.Fogel. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. Contemporary Clinical Trials Communications, Volume 11, September 2018, Pages 156-164. DOI: 10.1016/j.conctc.2018.08.001

[3] The promise of organoids and embryoids. Nat. Mater. 20, 121 (2021). DOI: https://doi.org/10.1038/s41563-021-00926-3

[4] Small. Special Issue: Advanced In Vitro Models for Replacement of Animal Experiments. Volume 17, Issue 15. April 2021

[5] Horejs, C. Organ chips, organoids and the animal testing conundrumNat Rev Mater(2021).

Where did all the nanomedicine go?

Well, it didn’t go anywhere, as in it didn’t disappear, but it seems that progressively for the last few years it has been not been calling itself “nano” that much anymore.

Last month we submitted a proposal to the last Euronanomed call, a ERA-NET type of platform under H2020 that has been running for twelve years and closes now. Also notably, the new Horizon Europe programme doesn’t have a NMBP programme anymore (NMBP stands for “Nanotechnologies, Advanced Materials, Biotechnology, and Advanced Manufacturing and Processing”), where many biomedical projects used to be funded. While naming things nano in science seems definitely less popular than 4-5 years ago, the area has probably grown in activity. The topics and the goals have merged with other areas where an application is envisaged (biomed, biotech, photonics, photovoltaics, etc.) and where the nanometer scale and the science behind it now uses more flowery and varied words to describe itself. The hypotheses here is that most niche research lines have evolved with their own vocabulary and keywords that include less the word nano. I figured out that it should be possible to trace and measure in some way how much the nanomedicine community continues to use it or not, and preliminary results are the matter of this post.

The European Commission has a public online database called CORDIS with information on all EU-funded R+D projects. For each project you can check for instance title, abstract, summary of periodic and final reports. I looked for projects in the H2020 downloadable spreadsheet that use the text string “nano” ( 1737 out of 19178 projects) on their summary or public periodical reports, and those that at the same time are related to biomedical and biotechnology applications (680 of the 1737). To simplify the search I looked for projects that contained several (4 or more) of a list of 20 words common in projects in those areas (health, clinical, pathology, cancer, bone, illness, biomaterial, biomed, injury, brain, stem cell, in vitro…). Then, to compare numbers year to year I normalised the number of projects related to nanomedicine by the total of projects in the year.

This was all done pretty quickly and improvement is very possible. I would like to refine how to identify projects within a chosen topic in the area, i.e. the list of words or by a different method, just not manually! Also it would be great to extend the series to include the FP7 database for 2007-2013 projects also available from CORDIS. A more ambitious goal that should be possible with these databases would be to identify which words and subtopics are getting more popular within the nanomedicine area, how their use moves over the years. Funded projects should be a good tool to predict emerging topics and interest, as they are one of the first public dissemination of ideas in science, many time earlier than publications for instance.

In the graph below we see number of EU-funded projects related to biomedical and biotechnology applications that use the text string “nano” per thousand projects of the total funded each year.

How to become a successful academic

Several times already during this last month I’ve seen myself in the troublesome situation of giving advice about how to become a successful academic. I’m not an academic myself so one idea that I try to gently put forward is that one way to be a successful academic is to move out. It’s an option to think about. The second idea that may help is that there are so many ways of being successful during a career at Academia. There are many because Academia doesn’t work in linear ways, although sometimes does, and many times contradicts itself. A few days ago I saw this Twitter thread by Maarten van Smeden (@MaartenvSmeden) that became very popular quickly because this is a topic of interest to many, and probably also because it’s a great sarcastic take on the available advice, highlighting how advice on how to become a successful academic can be so frustrating because it’s many times at odds with other advice, even from the same source. 

In his thread Maarten van Smeden offers lots of food for thought:
1) Be the ultimate collaborator but also don’t be. Say yes to as many collaborations as physically possible: co-produce papers, LEARN, co-write grants, DISCUSS, it is all about synergy. But also, collaborations slow you down, have your own ideas! Just say no to collaborations.
2) Be the methods ninja but also don’t be. Science is only as good as its weakest link: don’t be satisfied by applying the default analyses in the field. But also, don’t let perfect be the enemy of the good and don’t confuse reviewers. Just apply the default analyses in the field.
3) Be the superstar teacher but also don’t be. Professor means teacher, it is LITERALLY in the name. Being a good professor means being a superstar teacher. But also, focus on the science and minimize the hours of teaching, don’t try to become a superstar teacher.
4) Be the open science practitioner but also don’t be. A modern scientist is an open scientist. Open up your code, your data and your publications. But also, your code is messy, the data isn’t yours to share and you should save the APC of open publishing to hire new lab members.
5) Be the literature addict but also don’t be. READ YOUR LITERATURE. Be the literature addict and know what is out there to prioritize your own science and become THE EXPERT. But also, there is just too much! Invest time spend on reading in writing your own stuff! DON’T READ.
6) Be the supreme knowledge sponge but also don’t be. Become the best in the world by borrowing knowledge from different scientific disciplines and by working in multidisciplinary teams. But also, be THE SPECIALIST. Focus on your own discipline and team, your CV is begging you.
7) Be the social media rockstar but also don’t be. Outreach! Show you can and will communicate with the public to explain your science. But also, TIME DRAIN! Surely your tenure track committee is not impressed by your 30k SoMe followers half of whom are bots anyway.
8) Be the peer review soldier but also don’t be. Be an active part of the scientific community: be ready for peer review duty. The system will collapse without you! But also, peer review is a waste: everything will be published anyway. Don’t answer the calls for peer review duty.
9) Be the frequent flyer world traveler but also don’t be. You are an internationally oriented researcher: fly as much as you can for talks, collaborations and make sure you participate in ALL the discussions. But also, think about the environment: fly as little as you can.
10) Be the family person but also don’t be. Don’t forget to live while becoming successful: family time should always be the number 1 priority. But also, all of the above should be number 1 priority.

An “open space” meeting, but online

Open space meetings are an incredibly potent tool to discuss almost anything in a group setting, and don’t need a lot of preparation. For our purposes, they are a simple and effective way to build a project proposal with a solid foundation on goals, checking with stakeholders, actually addressing the correct challenges and questions that relate to our research proposal.

Before the social contact restrictions of the cover-19 pandemic this meetings usually went like this: participants in a room, guided by a facilitator, used a whiteboard, a pin board or a table to write down the main issues, topics or questions that in their individual opinion need to be addressed by the group. The dynamic is quite simple, informal and hands-on, so that for instance the participants have to use pens, post-its, etc. themselves and therefore get engaged in the discussion. Then the group or facilitator goes over the topics proposed and groups them in themes or workshops, that are discussed in a second part of the meeting. Each workshop has a framework of simple principles and its goal is to discuss topics with a bit of more detail, for instance to develop a list of actions required, who should take them, a list of questions to be answered in a R&D proposal, etc. In this link there’s more info on how to organise these kind of meetings.

A team in our lab has started to prepare an R&D proposal for an upcoming call. Earlier this week we managed to get a few stakeholders online to present a first draft of the proposal and run a conversation more or less organised following an open space framework. The meeting was successful to improve the proposal and to rewrite its goals. This is how we did it to make it work online:

We had 9 participants and a one hour of meeting at most. The participants were from 3 different stakeholder organisations that have complementary areas of expertise in the topic of our research proposal. We have been in contact with all of them previously, although in some cases just a few weeks ago for the fist time. Hopefully we will be partners in the ad-hoc R&D team once the proposal is submitted for funding.

Before the meeting we prepared an outline of the research proposal with the basic goals and actions we believed make sense. For the open space dynamic, we prepared a simple table with six topics of discussion from the main themes of the research proposal.

We found a time slot free for all using doodle, a very useful free online tool to schedule meetings. We sent the meeting invitation email with a two line description of how the meeting was going to be organised.

The day of the meeting we started the meeting right-away, without proper introductions, with a 15-minute presentation of the project. The presentation was focused on background information about the general medical problem we initially want to address and the technologies we believe we can use.

We then started the open space part of the meeting, with a quick introduction of the participants and the basic rules: Chatham House rule, pre-established topics can be amended,

With a shared screen I took notes of the questions and statements that participants were willing to share about the different topics. This allowed participants to provide real time feedback and expand on the questions already being put forward.

The whole meeting took about 50 minutes and was very successful in identifying several important aspects of the proposal that we had not considered at all and that will be incorporated in the final bid.

A great evaluation report

In a recent European H2020 call our lab has been awarded a very exciting and pioneering grant. The evaluation summary report was quite long and with a lot of feedback on what we did right to get the proposal approved. I believe this can be a great resource for other teams building and writing similar proposals. This is an excerpt of the report for Criterion 2 – Impact, where we got an score of 5. Just a few confidential bits about the project specific goals have been removed.

Note: The following aspects will be taken into account, to the extent to which the outputs of the project should contribute† at the European and/or International level.

The extent to which the outputs of the project would contribute to the expected impacts listed in the work programme under this topic

Evaluator 1

The proposal features a radical vision and disruptive innovation. It has the potential of providing solutions for other fields, such as —– . There is good potential for long-term commercialization of developed technologies and job creation within Europe, which can be carried out by the involved SME. Applicants identified a pathway towards future clinical studies, which adds to the long-term impact. Potential industrial interactions with the medical device industry are also outlined, which could be promising for future technology maturation and transfer. The proposal will involve early-career researchers adding to the European research excellence. The participants apply for the first-time to FET.

Evaluator 2

This proposal has a high potential to leverage a radically new line of technology (—–). Advances in the technologies pushed forward by the presented concept will lead to long-term benefits for other applications in —–. The results of the project will improve patients’ survival and quality of life and contribute to the sustainability of healthcare systems. The developed platform will provide the highest flexibility to support unprecedented applications in —–. The project will involve young scientists that will receive the appropriate training to develop a wide range of scientific skills to broaden their professional horizon.

Evaluator 3

This project will contribute the expected initial focus of developing a product that can be used to treat —— which will have wide impact on the large number of EU and international patients suffering from —–. There will be associated economic healthcare benefits. The project will also train researchers in this important and growing research area.

Evaluator 4

Estimated project impact demonstrates convincingly a very good potential to establish a solid baseline of know-how – by providing the techniques and mechanisms that will allow ——, and to strengthen a research community by developing technologies for —–. Proposal involve young scientists and ambitious high-tech SME. In long-term perspective, synergies with other industrial partners are foreseen. This very good matches with two of the expected impacts of the work programme – building leading research and innovation capacity across Europe and facilitating future social or economic impact (creation of the market of ——).

Effectiveness of measures and plans to disseminate and use the results, including management of IPR and to communicate about the project to different target audiences.

Evaluator 1

The proposal has the ambition of a strong online presence through the use of social media tools and a dedicated project website. The communication matrix is well developed and different audiences are taken into account. Data management and technology transfer activities are recognized as a separate task, which is a strong point. An exploitation plan for the foreground is foreseen, which will provide clarity on IPR aspects. The proposers plan to organize a final open scientific conference, which adds to the dissemination outcomes. A potential shortcoming is the lack of outreach to specialized medical device companies in the Advisory Board.

Evaluator 2

The communication plan is highly detailed including diverse target audiences, e.g. patients, health financers and associations, health companies, and the general public. The dissemination plan includes open-access publications, conference presentations, training, and education courses, as well as data storage in open repositories. The dissemination to the public includes the development of project website, press releases, and promotions on social media. The project includes a fair and transparent IPR policy regarding patents, rights of ownership, and exploitation of results.

Evaluator 3

A variety of appropriate methods to disseminate the research to stakeholders have been described. It is clear how the IP will be managed and what the proposed translational and commercial road map is. As such, the plans to manage IP are effective. The plans to communicate to a wider audience are effective and appropriate.

Evaluator 4

The draft plans for the exploitation and dissemination are well conceived and go far beyond the standard dissemination to scientific communities (through scientific publications, conferences, seminars, workshops) and foresee specific activities to reach additional stakeholders attention and wider public engagement. IPR management is relevant.

Guía de actividades en casa para estudiantes de doctorado y otros investigadores

Ahora que es complicado recoger datos experimentales, algunas recomendaciones sobre cómo organizarse y qué actividades hacer. Adaptado de un hilo de twitter de la Dra Zoë Ayres, de este artículo en Science, y de un poco de experiencia personal.

Empieza el día con una rutina de planificación. No todas las personas y los hogares son iguales, pero un poco de organización ayuda a aprovechar y llevar mejor los días en casa. Nuestra rutina es de ducha, desayuno, veinte minutos de gimnasia o yoga (vídeos en youtube) y entonces hacer una lista de actividades del día. Si estás en casa con niños u otras personas dependientes es buena idea dedicar diez minutos a organizar con ellos su día, por ejemplo utilizando un sistema de agenda diaria como el descrito aquí.

 

A continuación hay un resumen de actividades que puedes elegir añadir a tu agenda de estos días.

Escribe secciones de tu tesis y artículos en marcha. Si eres estudiante de doctorado no importa en qué momento de la tesis estés, tendrás una idea más o menos aproximada de los equipos, herramientas y protocolos que has usado o vas a usar. Puedes comenzar a escribir las secciones de materiales y métodos de tu tesis, y además aprovechar para analizar qué protocolos y experimentos necesitan alguna mejora.

Es un buen momento para hacer figuras. Las figuras son una parte fundamental de tesis y artículos científicos. Algunos revisores es lo primero que miran. Si tienes datos, imágenes de microscopía, etc. en crudo pero aún no organizadas en una figura, ahora puede ser un buen momento. Aprende a usar Excel, Powerpoint o herramientas gráficas como Inkscape (gratuito) para que tus figuras sean mejores. Una idea relacionada válida para todos es crear un resumen gráfico de tu investigación. Un resumen visual auto-explicativo de los principales objetivos y hallazgos de tu investigación es una forma muy útil de comunicar ciencia. Es necesario dedicarle tiempo para hacerlo bien, pero una vez que hayas creado uno, puedes adaptarlo para posters, presentaciones, documentos varios, redes sociales, y son una manera de construir marca personal.

Lee literatura científica relevante y empieza a escribir la introducción (objetivos, estado del arte) de tu tesis y artículos en marcha. Si estás empezando tu tesis, leer es imprescindible para  comprender dónde se sitúa la tesis en el estado del arte, definir bien objetivos, y a pensar a fondo sobre cual es el plan de trabajo óptimo para conseguirlos.

Aprende a manejar aplicaciones informáticas y a programar. Depende de cual sea el tema de tu tesis, el manejo matemático, la estadística de los datos experimentales, pueden ser cruciales. Hay algunas guías y cursos gratuitos excelentes para Excel, Python, R y Matlab, LaTeX, en youtube por ejemplo.

Aprovecha para poner al día tus cuadernos de laboratorio. Asegúrate de revisar y anotar bien en detalle todos los métodos que has estado usando hasta este momento.

Revisa los experimentos fallidos o datos a priori de poca utilidad. ¿Se puede escribir un apartado o un capítulo de la tesis con ellos? ¿Quizás con una revisión o una figura mejor se puede acabar de escribir un artículo publicable?

Si eres estudiante de doctorado, escribe lo que puedas de las secciones de resultados y discusión de tu tesis. ¿Hay experimentos o datos que faltan en este momento? No hay problema. Deja un espacio por ahora.

Promociona tu trabajo online. Dedica un poco de tu tiempo a marketing en redes sociales. Actualiza tu web personal o de tu laboratorio, pon en marcha un perfil de Twitter y aprende que son los hashtags como #AcademicTwitter y conecta con otros investigadores que trabajan en tu campo. También puede ser el momento de escribir un artículo de divulgación, o crear un video de YouTube explicando algún aspecto de tu trabajo.

Escribe propuestas para convocatorias de financiación de la investigación. Además de las becas y subvenciones habituales de las agencias nacionales y europeas, ahora puede haber tiempo de echar un vistazo a premios de la industria, fundaciones privadas o asociaciones de pacientes, pequeños fondos y ayudas de investigación que normalmente pasan desapercibidos. Cualquier tiempo dedicado a escribir propuestas de subvenciones es en cualquier caso útil como aprendizaje, es una habilidad difícil de dominar.

Piensa en tus planes profesionales. Normalmente es difícil pensar en nuestra carrera profesional a largo plazo. Ahora en casa podemos dedicar tiempo a averiguar más sobre las opciones en nuestra profesión. Si nos sentimos un poco valientes podemos contactar con profesionales que tengan trabajos como los que nos gustaría a nosotros tener en un futuro, buscando a través de LinkedIn, ResearchGate, directorios de universidades y empresas, etc. En medio de una pandemia igual no es apropiado pedirles que se reúnan para tomar un café, pero quizás sí para una llamada telefónica o una teleconferencia rápida. La realidad es que casi seguro estas personas también estarán trabajando desde casa y seguramente no les importará algo más de contacto social. Estos contactos pueden ser una buena manera de romper el aislamiento, aprender sobre la carrera de alguien y construir una red, manteniendo la distancia!

Empieza a crear planes sobre lo que vas a hacer cuando puedas regresar a la universidad. Planes con cierto nivel de detalle, para ser lo más eficiente posible sobre todo cuando tengas la oportunidad de entrar de nuevo en laboratorio.

Recuerda que nadie es verdaderamente eficiente todo el tiempo todos los días. Reserva tiempo en tu día en casa también para pausas de café, almuerzos, charla con colegas por teleconferencia, etc. Investiga un poco sobre gestión óptima del tiempo, como el método Pomodoro. Reserva y organiza tiempo para contactar con compañeros de trabajo y con amigos de manera periódica. Este momento de aislamiento va a ser duro emocionalmente para muchos de nosotros y el contacto humano es importante aunque sea a través de una pantalla o una llamada de teléfono.

Haz cosas divertidas. Asigna parte de tu tiempo a hacer otras cosas además de las relacionadas con tu trabajo que te dan alegría, que te ayuden a aliviar algo de estrés. Recupera aficiones para las que ya no tenías tiempo. Leer y escribir ficción, bailar, cocinar, hacer conservas, dibujar y pintar, coser (mascarillas), tocar un instrumento, escuchar música, jugar a juegos de mesa, juegos online, ver películas y series, aprender un idioma, plantar un huerto (buen momento ahora que empieza la primavera). Cuídate a ti mismo y a los que te rodean.

Twitter, una herramienta para la ciencia. ¿Dónde empezar, hacia dónde ir?

Twitter ha evolucionado en su uso como herramienta social rápidamente en pocos años. Aunque para muchos académicos sigue siendo casi desconocido, hay un número creciente de investigadores que lo usan en el ámbito profesional. Nuestro perfil puede estar centrado en leer información que nos interese y mantenernos al tanto de novedades en nuestro campo, en diseminar nuestra actividad y resultados para aumentar nuestra visibilidad, conectar con colegas conocidos y desconocidos, interactuar con el público, usar la comunidad extendida y experta en Twitter para pedir ayuda en encontrar información específica o resolver problemas difíciles de todo tipo, o todo a la vez. En resumen, un perfil en Twitter como profesional de la ciencia es fácil de montar y el retorno puede ser extraordinario.

Nada más empezar en Twitter. ♦ Elegir un nombre de usuario (twitter handle) corto y fácil de identificar. Nuestro nombre real entero, parte, o abreviado, suele funcionar bien.  Montar nuestro perfil con cuidado. Dedicar un rato a completarlo y volver a revisarlo después de los primeros días de usar Twitter. Foto, imagen ‘banner’, mini biografía 160 caracteres máximo, enlace a web, y un tweet fijado representativo de nuestra actividad.  Buscar y seguir a unos 20-25 investigadores en nuestro campo. Mirar entonces las sugerencias de Twitter de otros usuarios a quien seguir, en el recuadro “Tal vez te guste” en el menú de la derecha, y seguir el enlace a “Mostrar más”. A partir de los usuarios que seguimos Twitter nos sugiere otros perfiles a los que seguir, y esto puede ayudarnos a encontrar muchos otros investigadores con intereses similares a los nuestros.  Los hashtags se pueden usar para encontrar personas que trabajen en temas similares y para hacer más visible nuestro perfil. Por ejemplo, en mi campo #biomaterials #regenerativemedicine #tissueengineering #stemcells

Si hubiera usado más Twitter hace unos años seguro habría tuiteado sobre esto.

Nuestra audiencia y contenido. Seguramente lo más difícil de acertar en Twitter es determinar quien queremos que sea nuestra audiencia y qué contenido funciona mejor para nuestros objetivos. No sorprenderá a nadie que los usuarios con contenido de más calidad y frecuencia suelen ser los que tienen más seguidores. Algunas ideas de contenido para investigadores: Un artículo interesante que has leído, porqué es interesante. Ideas en las que estás pensando. Preguntas que tienes. Artículos que has publicado recientemente. Recursos útiles para investigadores en tu campo. Clases que estás dando. Conferencias a las que asistes. Búsqueda de socios para propuestas de proyectos. Retuitear y responder a los tweets de otras personas.

Averiguar qué son las listas en Twitter y usarlas. Son una manera muy eficiente para recibir y leer información en nuestro campo.

El potencial de Twitter para hacer contactos. Con Twitter podemos seguir a las personas cuya investigación nos interesa, pero también comentar en sus tweets y enviarles mensajes directos. Si somos un poco activos podemos multiplicar nuestra red de contactos. Por ejemplo, si no podemos asistir a una conferencia interesante en persona, podemos seguir los hashtags de la conferencia y contactar o responder a participantes que estén allí en persona. En general en Twitter podemos ser más bien atrevidos a la hora de comentar y producir contenido como herramienta para hacer contactos. Hay que usar el sentido común y como en la vida real a la larga es más atractivo ser respetuoso y ponerse en el lugar de los demás.

 

Pequeña guía de las reuniones de grupo

En muchos laboratorios de investigación es normal tener una reunión periódica, semanal por ejemplo, en la que se habla de cuestiones de todo tipo y suele haber una presentación corta. Una reunión frecuente y bien estructurada puede ser una pieza fundamental de la vida de un grupo de investigación, y uno de los ‘marcadores’ de un buen líder de grupo.

Aunque la mayoría de investigadores se forman desde el inicio en la cultura de las reuniones de grupo, no es igual ni mucho menos en todos los laboratorios, y puede ser una cuestión importante para los investigadores que acaban de crear su grupo o para los que se preguntan si su rutina habitual tiene aspectos mejorables. Cada IP y cada grupo tiene sus particularidades y no todo funciona igual de bien en todas partes, aunque algunas directrices generales pueden ayudar:

La regularidad (lugar y momento) es una buena idea para programar reuniones de grupo, da tiempo a planificar el resto de la agenda, otras reuniones, experimentos, etc.

El formato puede ser muy variable según el tamaño del grupo y el estilo del IP. Un grupo pequeño puede funcionar bien con una reunión tipo mesa redonda donde cada investigador dedica unos pocos minutos a hablar de su trabajo en marcha. En grupos grandes hace falta algo más de organización para mantener el foco de la reunión, y suele haber alguna presentación con pantalla.

La reunión puede incluir una ‘puesta al día’ por parte del IP, sobre en qué emplea su tiempo, propuestas a convocatorias de ayudas, publicaciones enviadas o rechazadas, contactos y networking, estrategia, uso de labs, etc. Este espacio puede ser delicado en algunos grupos y es mejor introducirlo poco a poco y modularlo según la dinámica pasada del grupo. Bien utilizado tiene muchos beneficios para el grupo: (i) la discusión pública puede ser fuente de nuevos puntos de vista, información, ideas no contempladas por el IP; (ii) la discusión y la información compartida ayuda a construir una visión compartida de equipo, a alinear los intereses personales de cada investigador con el grupo; (iii) es un momento de mucho interés formativo para futuros líderes de grupo.

La reunión de grupo también es un buen momento para discutir resultados de manera informal. Es habitual que la reunión incluya una presentación corta sobre trabajo en marcha por parte de estudiantes de doctorado o postdocs, con resultados más o menos en crudo. Es importante que este momento sea de ayuda para el investigador que presenta, para mejorar su trabajo, avanzar en la interpretación de sus resultados, en la planificación de experimentos futuros, etc., pero que cuando se destaquen errores sea siempre para proponer y discutir soluciones. El propio IP o alguien en el grupo debe encargarse de organizar la rota de presentaciones. Puede ser una buena norma que cuando alguien se incorpora al grupo, o los que realizan una estancia de investigación en el grupo, realicen una presentación lo antes posible sobre su trabajo y experiencia previa. También se puede aprovechar la visita breve de otros investigadores para proponerles que hagan una presentación de su trabajo en nuestro grupo, aunque entonces debe cambiar el formato de reunión y adaptarse a una presentación algo más formal.

Otra forma interesante de presentación, que algunos grupos programan de manera independiente pero que puede ser útil para completar la rota semanal en grupos más pequeños, es un ‘journal club‘, en el que alguien presenta un artículo científico especialmente relevante para el grupo, y se discute con más o menos profundidad su utilidad, sus deficiencias, técnicas empleadas, etc. Es una buena manera también de transmitir en el grupo una rutina sistemática de lectura y análisis de artículos.

Finalmente, la reunión puede ser un buen momento para compartir información de manera eficaz sobre la propia vida de grupo. Se puede pedir opinión sobre las reuniones de grupo en si mismas, comentarios sobre procesos de laboratorio, sobre la dirección científica, cuestiones específicas del grupo, etc. Es una herramienta que depende mucho de la dinámica de cada grupo, y que hay que manejar con cuidado. Si se utiliza bien, puede ayudar mucho al IP a recoger opiniones e ideas que no llegan por otros medios. Si se prefiere que este tipo de discusión no sea en la reunión con todos los investigadores, se pueden hacer encuestas anónimas sobre la vida en el grupo. Es muy fácil hacer una encuesta en google forms para compartir como enlace en un email. Aunque haya alguna pregunta de feedback general es mejor tener una encuesta con preguntas estructuradas.

Tanto la discusión abierta como anónima a través de encuestas es una retroalimentación muy valiosa para mejorar la dirección de un grupo de investigación. Después de todo, todos tenemos siempre algo que aprender, incluso como IPs con décadas de experiencia. Aunque puede ser estresante en algunos momentos, creo que es importante seguir preguntando y revisando la cultura de nuestro laboratorio y la forma en que hacemos las cosas.

Biomedical entrepreneurship in Valencia – 1st VLC INNOSALUD event.

A remarkable event took place last Tuesday in Valencia. The two main local universities and three hospital research trusts introduced eleven selected entrepreneurship initiatives to investors. Besides the many impressive proposals and the gifted teams leading them, this first edition stood out as demonstration of the powerful outcomes of collaboration among these public institutions. For many years they have successfully encouraged and funded seed actions for inter institutional research projects. Most of the showcased companies have indeed been born at the interface of biomedical, clinical and engineering research. This history of joint promotion of research is hopefully growing into more coordinated strategies to transfer research results into innovation and as a symbiotic voice towards regional and national political decision makers.

At the event, after institutional and political speeches that were a bit dull and lacklustre, presenting entrepreneurs had around 10 minutes to talk about their plans and answer questions from investors. These are my quick notes on them, please excuse brevity and inaccuracies.

Eritrocare (Presented by Emilio Sánchez Ortiga). Microscopy tools for the diagnosis of diabetes in real time. Detection, without staining, of morphological changes in erythrocytes from a blood capillary sample, with specialised propietary hardware and software. Launching with TRL4 and plan to reach TRL9 in 3 years with an investment of 500k€.

Match Biosystems (Presented by Adrián Teruel). Rapid in vitro detection of infectious pathogens. Mesoporous material with molecular gates that match oligonucleotide chains and release staining visible with the naked eye or with fluorometry. Beachhead application for candida albicans, with a diagnostic time of less than one hour, high sensitivity and low cost. Currently in TRL6.

MetSPag (Presented by Nuria Cabedo). New therapeutic agents for metabolic syndrome. PPARs agonist molecules. Currently in TRL3. Current plan to finish the pre-clinical phase.

DuraLocK (Presented by Carles). Seal kit to treat accidental ruptures of the human dura mater membrane. Application kit and implant / resorbable PLA thread to respond to and treat on site an accidental puncture of the dura, like the ones that rarely but sometimes happen during an epidural anesthesia procedure, with potential grave complications for the patient. Currently in animal model trial (sheep).

3D Surgical Technologies (Presented by ) Prosthesis for neo vaginal surgeries custom manufactured by 3D printing. An implant (named Paciena) for women born without a vagina. Most common current surgical technique uses artisanal prostheses, not well designed and with frequent complications. Plan to finish certification and implementation of marketing channels during 2020, with a need for financing of 400k€. Product launch in 2021.

Endoscopic Smart Center (Presented by Oscar Díaz and Lucas). System for monitoring and control of homeostasis in cavities. Insufflator system for endoscopy with temperature sensors in the surgical trocars, volume of the cavity, control and recycling of the gas used, and an artificial intelligence system that uses the images in real time to help the clinical decision. Plan to move from TRL6 to TRL9 in two years including clinical trial, with a budget of a bit over € 1M.

HistShock (Presented by José Luis García Gimenez). Test for sepsis diagnosis with isotopically labeled peptides. Relies on mass spectroscopy equipments, but with critical advantages over current tests, sensitivity and speed. 4-year investment plan of 3M€, 560k€ the first two years with clear milestones.

Brain Touch (Presented by Paco Camarena). Helmet for neurological treatments. Several neurological conditions targeted, Alzheimer’s, and others. Helmet focused utrasound with propietary system of lenses, to open the blood brain barrier and allow drugs into the brain. Plan to develop prototypes, validations, and certifications during the next three years.

Smart-Sens-H2S (Presented by Pilar Campins Falcó). Colorimetric sensor for halitosis detection. Bag test for blowing, onto colorimetric sensor, and mobile app.

Imaging Biomarker Analytics (Presented by Eric Abado). Biomarkers for the early detection of breast cancer. Image analysis software, multiparameter integration. Hospital license business model.

NELA Biodynamics (Presented by José Expósito Ollero). Expandable medical devices for orthopedic and trauma surgery. Intra bone marrow hip implant with expandable polymeric materials. The NELA implant is made by drilling instead of by impact reducing bone fracture during surgery. The procedure introduces the implant with slack and then it is expanded to a tight fix adaptable to bone and patient. Plan to move from TRL 6 to TRL 9 in four years.

More about the event in this press release.