Covid-19 Research Is Moving Incredibly Fast

Scientists, publishers, and regulatory agencies are working at breakneck speed to tackle coronavirus


Julia Bauman

3 years ago | 6 min read

Upon hearing that treatments for Covid-19 are months or even years away, the public’s common response seems to be a mix of frustration, hopelessness, and anger.

As a scientist, my reaction is quite different: I’m amazed by the breakneck speed with which researchers are attacking this scientific challenge.

By normal scientific standards, Covid-19 research is fast. I mean, breathtakingly, astonishingly fast. Within weeks of a global outbreak, scientists revealed insights into the virus’ mechanism of entry and disease provocation, and in three months there have been over 1,400 papers published on medRxiv and bioRxiv (two non-peer reviewed, open source life sciences publication platforms) about SARS-CoV-2. Additional coronavirus projects are being completed and new ones initiated at an incredible clip, rapidly adding to the body of knowledge around this single disease.

There are already treatments being tested in patients, treatments for a disease that didn’t even exist five months ago.

Why is this so impressive? For context, the development of new scientific knowledge requires several time-consuming but vital steps, including:

  1. Determining the research question and planning the experimental approach
  2. Applying for funding
  3. Setting up for experimentation
  4. Science!
  5. Writing up results and submitting for publication
  6. Waiting for peer review and journal response/paper revision

Nearly every part of this process is slower than one might expect, though (mostly) for good reason.

First, there’s ideation. The scientist looking to embark on a new project must come up with a research question that a funding agency sees as worthy of hundreds of thousands of dollars.

The question should be specific, important, and testable, and achieving those three adjectives is hard.

A scientist must take the time to build a broad understanding of a research area in order to know what’s important, yet also become deeply familiar with the details of a subfield in order to ask specific questions.

To ensure that the question is testable, the researcher must have in mind a biological model system (for example, a genetically engineered mouse or a type of cell), and methods for measuring biological outcomes.

The scientist should have strong reason to believe that their chosen model and measurement systems are well suited to their research question, based on experience and reporting from other researchers.

They will likely need to spend many hours reading or conducting preliminary experimentation to thoroughly convince themselves of this.

By normal scientific standards, Covid-19 research is fast. I mean, breathtakingly, astonishingly fast.

Once ideation and broad planning are complete, the scientist summarizes all of this in a five-to-25-page grant proposal to be submitted to funding agencies.

It can take weeks to prepare this document, but waiting to hear back from the potential funders is even slower — the typical turnaround time for grant proposals is three to nine months.

Almost a year later, with funding in hand, it’s time to do some science! Well, not right away — some scientific groundwork needs to be laid before the real experimentation can begin.

The aforementioned model system must be built (if new) or validated (if previously used elsewhere).

Developing a new model is an especially lengthy process that may require months or even years of work, for several reasons:

1) Biological systems operate on biological time scales. Human cells in a petri dish take days or weeks to grow, and they often must be grown repeatedly for separate tests. If animals are used, the time horizon multiplies — for example, each experiment with a mouse can take months, and any genetic manipulation of mice requires breeding multiple generations.

2) Many tests must be run to ensure a model is usable for a particular scientific question. As a simple example, if you wanted to study the growth of cancer cells under various conditions, you need to confirm that certain conditions either halt or accelerate their growth in an expected way (negative and positive controls, respectively). Sometimes, a generated model will inexplicably fail control tests, and further testing must be done to discover the root of the problem.

3) If insurmountable challenges arise with model generation, the scientist may need to just start over. More time spent building a model is always better than using a bad one.

Then, there’s the actual experimentation.

Typically, a scientist will have some general idea of how long they’ll work on a project, but only in a minority of projects can they actually plan out every experiment they will need to complete.

More often, there is a launch point and a set of broad objectives (that is, understand the mechanism by which Gene X causes effect Y), but the road map to arrive there is flexible.

A scientist may start out with a hypothesis only to discover that it is incorrect, leading to a revised hypothesis and a brand-new set of experiments to test it.

This process can occur several times over the course of a scientific project. Again, if any animal work is involved, timelines are generally extended. The months spent edging closer to an answer easily add up.

Other unexpected challenges can arise as well. The fastest possible timeline for a set of planned experiments is rarely achieved. Equipment breaks. Cell cultures get contaminated with bacteria.

A week-long experiment must be delayed because the experimenter has an immovable commitment on a given weekend. Science requires highly specialized and delicate systems (and human scientists), so necessary breaks to restore their function can be more or less expected.

There are already treatments being tested in patients, treatments for a disease that didn’t even exist five months ago.

When a project is (finally!) finished, it’s time to publish the work in a scientific journal. This is a process that can take years. First, the writing of the paper itself is arduous and time-consuming.

The body of a scientific paper is, on average, 3,000 to 10,000 words long, and packed with data and citations that must be carefully curated and formatted.

In addition, one must typically assemble a lengthy supplementary data and figures submission, to show full backing for all scientific claims and to make crystal clear how all experiments were conducted. Once this is complete, it is submitted to a journal.

If the journal editors believe the paper may be appropriate for their publication, peer review begins. Peer review is, of course, extremely important for ensuring high-quality scientific work, but does slow down the publication process a great deal. One researcher found that the average time from submission to publication for his lab was nine months.

What happens in all this time?

The journal assigns at least two reviewers to pore over the paper, making detailed comments on the data, formatting, and wording of the paper.

The reviewers will either reject the paper outright, accept it as is (very rare), or return it to the authors with requested changes. In the latter scenario, the scientists are typically asked to execute additional experiments to solidify certain claims made in the paper, and/or to make changes to figures or text.

This can take several months to complete and incorporate into a new version of the paper, extending the time to publication. After resubmission, the reviewers and editors will accept the paper if they are satisfied with the changes.

If not, the submission process (and the clock) begins again with a different journal.

Last, but certainly not least, is the process of injecting science into the real world. If research is directly relevant to medical practice (that is, discovery of a drug target, or genes associated with a disease), it is said to be “clinically translatable,” and these types of discoveries tend to have a more rapid tangible effect.

If research results in a novel biomedical invention that is intended to be used in humans, such as a pharmaceutical drug, it will need to undergo an FDA-regulated trial.

These trials are notoriously time consuming — the average length of the testing phase for a new pharmaceutical is six to seven years, followed by a ~1.5-year review process if the drug passes testing. In total, that sums to a total of 12 years, on average, from the start of research on a drug to the time it’s available to the public.

So how have coronavirus researchers managed to accelerate the normal pace of scientific work? Well, first of all, many scientists are working overtime, and they aren’t really able to work on much besides Covid-19.

They’re thinking hard about research questions, discussing which to prioritize, and working as fast as they can to answer them. When their work is finished, they’re often immediately publishing their work on open-source platforms, then later submitting to academic journals.

Fortunately, several scientific journals are accelerating their review processes so that papers can get out to the public quickly. This has enabled peer-reviewed, high-quality work to surface in a matter of weeks rather than months (or years).

Importantly, regulatory agencies are speeding the initiation and processing of clinical trials for coronavirus treatments in hopes of expediting the emergence of lifesaving or disease-preventing drugs.

Several months may sound like a long time to wait for a coronavirus treatment; a year feels like eons to wait for a vaccine — but these timelines are actually incredibly short by regular standards.

The takeaway? We may have to wait a little while for treatments, but waiting is necessary and worthwhile — time is the premium on safety and efficacy.

Meanwhile, scientists, the medical community, and regulatory agencies are working really, really hard to combat this virus.

We owe them a debt of gratitude for the many hours they’re giving, the sacrifices they’re making, and their deep dedication to solving this problem — for us.


Created by

Julia Bauman







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