To be successful in biotech - what does it mean?

[Alex G]

I am considering moving to the biotech from academia/clinical research and would appreciate the advice from people with experience.

First, what qualities and achievements are required in order to get promoted or just to be called a good employee in the biotech? Say I am hired as a Scientist II in a mid-size company. What do I need to do in order to get promoted to Scientist III eventually? Is it just to do my job well, gain experience and then fill in the position when it opens? To demonstrate leadership skills? To get the projects done better/faster than the others? What are the actual criteria for recognition and promotion?

Another question is what is the level of freedom that you actually get in the biotech as a scientist? Is there any at all? I realize that I will need to forget about the luxury of asking questions. But what about having the freedom of choosing my way of finding the answer? Is this common or rare to have at least that?

Also what if you were told to find an answer to the question, but then you found that the question itself is wrong, the things are working in a totally different way. Is it good or bad for you? Will it be appreciated that you found something new, or will you be called a troublemaker?

[Ana]

Hi Alex,

Your questions are too vague to be able to give you proper answers. Would you ever ask someone if it is ok to come up with new ideas that challenge hypothesis in academia? the answer is obviously that “it depends on the lab and the PI”. Some labs expect their trainees to challenge ideas, some prefer them to stick to the protocols they were given and not to ask for questions.

Within the same company you will also find a variety of cultures based on the group or department, let alone if you ask as broad as within biotech as an industry.

What I feel I can answer is your question on how to move up. In general a promotion to the next scientist level as you listed won’t be by filling an opening, it will be a promotion. And there might be limitations such as not being able to promote you in less than 2-3-4 years since the last promotion no matter how well you are performing.

In general to move up you will need to score high in three categories. Two are the usual categories of performance appraisals, the third is to have a good relationship with your manager:

# Performance
# Perceived ability to grow
# Relationship with manager

Performance appraisal uses in most places the common grid of 3x3 where you have in one of the axis the performance of the employee (underdeliver, delivered or overdelivered based on the predefined performance objectives) and in the other axis his potential to grow (from needs development to high potential individual).

As a mid-size company they are probably using this system to track performance, so candidates for promotion should be in the top box of high performer and high potential for development. Have a conversation with your manager on what they understand would mean “high performer" and "high potential for development” for them because it is highly subjective.

The third key aspect is relationship with your manager. It is your manager who needs to propose you for promotion. If he or she does not like you or is too concerned with his own career he won’t advance yours, just like some academic PIs.

So doing the job well, as you ask, goes in one of those three categories (performance). Showing leadership skills goes in another (potential to grow). Faster projects are again performance. And don’t forget it is people who needs to put you forward for promotion so the relationship with other people and in particular your manager is again critical.

Level of freedom and how well they will take your original ideas is completely team-based. No way to answer you from here. Make sure you ask those questions when interviewing Alex! those are clearly important aspects of the job for you so you will need that information to make a decision and you can only get that information directly from them.

Good luck,

Ana

[PG]

I think that the main difference between academia and industry is that within industy the goal for your research is almost Always fixed. Your research is aimed at developing a certain drug, device or diagnostic. You are usually also limited by the critera set for that product by your marketing department or Company mannagement. For example you may need to develop a drug that can be administered as a pill, to use real time PCR on a specific robot for your diagnostic assay or something else. The final limitation is that time is usually a lot more important in industry as compared to industry which also sets limits for what you can do. The value given to time also means that research teams working on a specific question is often larger in industry as compared to academia and the amount of Resources invested within a short timeframe significantly higher.

Otherwise your freedom depends on the type of position that you have. If you work as a Project leader your feedom can often be rather large as long as you stay within the frame discussed above. If you on the other hand have an entry level scientist position you will usually have someone that tells you what to do in more detail.

[Alex G]

Thanks a lot guys for great and detailed answers! I understand that my questions are vague and general, but this is a whole different world and I know virtually nothing about it. I do realize that things are very different in different places, I am merely trying to grasp on some basic principles. I assume biotech has a totally different way of thinking and approaching things and it is important to understand their ways before making any long term commitments.

I guess it boils down to this for me. Based on my (and many others') experience in academia, the original project/hypothesis that you are hired to research is rarely the same what you end up with a few years later (if you are indeed successful). I would say usually the original approach or hypothesis is always wrong, what varies is the extent of how much is it wrong, and your actual job is to figure out what is right. And this is just the state of things. That's OK to find a way to get your project to work (with some PIs, hehe). Often you are hired to do a project that is based on a completely unrealistic hypothesis. And PI has a grant for it, needs to show productivity and does not care. One way out of it that I saw is when people demonstrate with enough evidence that, OK, this just does not work, but there is another way, and we still can get something out of it. PIs won't be happy but something is better than nothing if they are reasonable enough to see the original flaw. Hey, I know enough people who published high impact papers on side projects that they developed on their own or by doing something their PI did not want them to do in the first place. It will not always work out like this, but the freedom you have in the academia gives you at least some room to maneuver out of such situations.

What I think is going on in the industry, and I most probably is wrong? On one hand, things should be a bit easier because they already are working with things that are proven to work in some way. But, as this is the industry, I assume there is always a whole deal of things that have been overlooked. Some of them might have been overlooked at the proof of concept stage, some may just stack up eventually. This is the inevitable consequence of the "good enough" approach, I think. Now it is not my intention to go there and start stirring trouble by challenging everything I see, but what if this will happen?

Say I went there, were given one project then another and another and they just don't work out. By that I mean to produce "negative data" in a biotech way of thinking. Again, I will be judged based on my productivity, and it appears that it will depend a lot on some external factor that I won't have any control over. And nobody will care why things are not working, at the end that will be my fault, as always.

And based on some small clues and my academic knowledge and experience, I suspect that the original approach is wrong, say the drug might have some alternative mechanism of action. I can't just show up to my manager and say I think the approach is not the right one. I would need to present some hard and quite compelling evidence first to even get their attention given that they will care at all. In the academia I would do some research around and then say: hey, we got it all wrong initially, but this is how it really works, and in many cases it will be even OK. Actually if I don't do this I will be just continuing to bang my head against the wall, frustrating my PI and eventually end up with a failed project. What is the way to deal with this in the industry if I won't have the freedom to generate and test my own hypothesis?

[Ana]

Companies kill projects all the time, they are NOT in love with one idea or one protein/target, something much more common in academia.

I worked in pharma for 5 years and went through 27 different discovery projects. There is a very high turnover and only a few survivors. Think of projects as a screening, you launch 10 to make sure 3 work by the end of the year so that one can make it forward - or not.

Something very used is the concept of the killer experiment. Like in "what would be the experiment that could mean a Go/NoGo decision for this project?", and then you focus on getting that killer experiment done.

Designing killer experiments is not just tolerated but expected.

If you were working with the people I worked for (different companies might be different) they would have loved you to come in and tell them about the other mechanism of action that you are suggesting, and then try it.

You will have it a lot easier to kill projects in industry. If that's what worries you you'll ve fine!

Ana

[PG]

In industry your productivity and success is not judged on the success of the actual projects that you are working in but how you contribute to the success of the Company.

For the company to be successful it needs to use its resources in a good way. This means killing the projects that will fail as quickly as possible while focusing on the projects that will be successes forward as fast as possible. Of course this isnt as easy as it sounds. That an experiment fails can be due to multiple reasons which may not be dependent on the project.

For example one of the very big pharma companies had a product candidate that repeatedly failed toxicity studies in beagles. The company were not able to explain this finding at the time and normally this would have been the type of result that would have killed a Project and company management actually even made this decision. However this company had a model that allowed their scientists to spend a small part of their time and Resources on activities of their own choice and the project group for this particular Project decided to push a bit further. As it turned out the toxicity was a consequence of using inbread beagles for the studies that happened to have a genetic defect in an important gene. This drug candidate later became one of the largest blockbuster drugs ever and have been driving revenue for that company for many years.

As a final comment very often there is a lot of unknowns in industry research and a lot of companies spend significant resources in discovery research and other efforts to try to do something really new.

[PG]

Maybe I should add that there is one possible exception to what I just stated and that is early start-up companies. In these cases the success of the company is often the same as the success of a specific project and management might not be overly happy about being told that it doesnt work.

[Ana]

Indeed PG, start ups are some time a one-project company. I'm not sure of Alex definition for mid-size company but I'm guessing it is something larger than your classical single asset spin off.

[Alex G]

Again thanks a lot for very informative answers.

I assume in the big industry they screen potential drug candidates, do proof of concept, maybe some mechanism of action studies, drug combinations, off-site clinical studies etc. So there are a lot of associated projects that are to be validated, and most of those will be killed. Could you please tell a bit more on how is the same applies to the startups or small standalone companies (I guess <50 people, one major and few smaller products in the pipeline)? I guess there won't be that many "fishing" projects to kill but on the contrary a few of projects they would like to get to work?

Or what are the kinds of tasks and types of questions that are given to scientists in big ans small biotech?