The most important biomedical-science technology advance–do we have a consensus?

I’ve blogged in the past about the changing nature of the life-sciences, and about how today’s graduate students need to be “jacks of all trades.” As I’ve noted, in the past, graduate students were required to use fewer experimental systems, but perhaps to master them more thoroughly. However, the advent of kits and companies galore has radically changed the way we do science.

But more has changed in science in the last 10-20 years than merely having biotech companies simplify techniques by selling standardized “kits” to robotically carry out a wide variety of experiments. No, there have been major and revolutionary advances in scientific technology that have been driving life-sciences forward.

Given that most of us have been in science for a few years (heh, heh), I would like to pose the question as to what you think is the most important technical advance that has driven biomedical science forward in recent years. I am going to list a few possibilities, but please feel free to add your own candidates, as I’m sure I’m going to miss quite a few.

Here are a few techniques that I think have really advanced science:

Going back a few years:

Monoclonal antibody generation–the ability to specifically design a cell line that secretes specific antibodies. Such antibodies are the mainstream of any work involving proteins.

Blotting–the detection of specific proteins on a piece of filter paper with antibodies, dubbed Western Blotting, and the detection of specific sequences of DNA or RNA on filter paper (dubbed Southern and Northern blotting, respectively). As a student, every instructor was eager to explain these techniques ad nauseum in every course offered.

Cloning and molecular biology techniques–the ability to make cDNA constructs that can be used to generate protein factories in bacteria for a variety of purposes, or to express specific proteins in actual cells.

More recently:

Model organisms–mice or even invertebrates such as flies and worms (or even zebra fish) are generated lacking specific genes or containing flawed ones to determine developmentally and in adult animals what these genes are responsible for.

Silencing RNA (SiRNA)–also known as RNA inhibition (RNAi). This revolutionary technique, barely a decade old, has allowed researchers to study the function of individual proteins in cells by blocking the expression of a specific protein of interest. This has now become the ‘gold standard’ for assessing function of a given protein, but was almost unheard of before 2002.

Proteomics–the use of mass spectrometry to rapidly and specifically identify proteins has become a key tool for all biomedical scientists.

Arrays–the use of “chips” containing hundreds or thousands of genes to determine which ones are ‘turned’ on and which ones are ‘turned off’ under various conditions or in disease cells.

The Human Genome Project–sequencing of the entire human genome, base by base, providing researchers with an online database containing all of our genes. Also unheard of 10-12 years ago as I began my post-doctoral studies.

The PubMed, online data banks, and online computation programs–not to underestimate the degree to which information technology has driven our progress. The Public library of Medicine at NIH, allowing instant access to millions of scientific abstracts (and open access papers) by simple search words, along with all the tremendous advances in computational biology have had a huge impact on the way we do science today.

Well I know I’ve only scratched the surface, so feel free to tender your own favorite technologies, and please vote! I’m going with the SiRNA, which has perhaps made the biggest impact on my own science.

About Steve Caplan

I am a Professor of Biochemistry and Molecular Biology at the University of Nebraska Medical Center in Omaha, Nebraska where I mentor a group of students, postdoctoral fellows and researchers working on endocytic protein trafficking. My first lablit novel, "Matter Over Mind," is about a biomedical researcher seeking tenure and struggling to overcome the consequences of growing up with a parent suffering from bipolar disorder. Lablit novel #2, "Welcome Home, Sir," published by Anaphora Literary Press, deals with a hypochondriac principal investigator whose service in the army and post-traumatic stress disorder actually prepare him well for academic, but not personal success. Novel #3, "A Degree of Betrayal," is an academic murder mystery. "Saving One" is my most recent novel set at the National Institutes of Health. Now IN PRESS: Today's Curiosity is Tomorrow's Cure: The Case for Basic Biomedical Research (CRC PRESS, 2021). All views expressed are my own, of course--after all, I hate advertising.
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13 Responses to The most important biomedical-science technology advance–do we have a consensus?

  1. Daimia says:

    ChIP and 3C-determining regulatory proteins and interacting DNA elements involved in controlling gene expression.

  2. Stephen Moss says:

    Hi Steve
    I would add PCR to the list, but overall the impact of monoclonals in biomedical science has been immense. First as lab reagents for blotting, immunocytochemistry etc, and in more recent years as therapeutics. This year monoclonal antibodies against TNFalpha will gross some $24bn worldwide making them the biggest money-making drugs on the market. So monoclonals are useful in both lab and patient.

    • Steve Caplan says:


      Yes, PCR is obviously supposed to be on that list–although to be fair, I intended that to be included in the “molecular biology advances.” Of course that probably isn’t really fair, as it exposes my own personal bias to towards the protein side, by lumping recombinant technologies, PCR and all in the same group!

      I’d have to agree that for the last 35-40 years, monoclonal antibodies are clearly a front-runner. When I started to write this blog, I was thinking more in line of looking at the past 15-20 y, more or less since I’ve been in this business, but somehow couldn’t let go of the monoclonal antibodies and discoveries of the 70s. So perhaps there should be 2 categories: last 20 years, and last 40 years.

  3. siRNA, next-gen sequencing (genome, transcriptome and, more recently, methylome), and bioinformatics (does that count?!) are making the biggest splashes in my field right now.

    When I was doing my PhD and postdoc (1998-2005), PCR was the advance that the PIs mentioned most often as something they wished they’d had during their own early careers

    • Steve Caplan says:

      Sure, bioinformatics counts. One of your fellow Canucks even went as far as to mention transistors! Listening to radio can help during experiments, but isn’t that overkill?

      As for the “somes” and “omics,” right now to obtain funding I should be talking about endocytomics…

  4. I’m going with the transistor.

    Sure, it’s not specific to biomedical science, but without the transistor – no computers, no microprocessor controlled lab instruments, no telecommunications.

    • Steve Caplan says:

      uhhh, wrong blog?

      • Nope. Can you imagine doing science without (a) the internet, (b) computers, (c) any microprocessor controlled instruments, or (d) email?

        Sure you can. But it would be a right royal pain. 😉

        • Steve Caplan says:

          You are correct, of course.

          But I was trying not to go TOO far back! I mean without Newton’s laws of gravity, there wouldn’t be any centrifugation, and without Darwin, and Mendel, we wouldn’t have site-directed mutagenesis….

  5. Also – the real game-changer in molecular biology is high-throughput (aka “next-generation”) sequencing. Not only is it now feasible to sequence entire exomes and genomes, it can also replace microarrays as readout for transcription/gene expression, chromatin immunoprecipitation, microRNA analysis, and probably other things. It replaces GWAS SNP arrays, and even linkage analysis (just sequence the whole genome and choose the markers you need/want). This is all here and now.

  6. Steve Caplan says:

    I am biased to the protein side of things, but I do see that high-throughput and deep sequencing are the topics of the day!

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