Five research tools and methods that are potential medical game changers ... that we didn't have a decade ago

An illustration depicting a doctor's office with an technological overlay analyzing patients vitals.

In years past, the path from scientific discovery to medical progress was a long and arduous one. But recent advances in research tools and methods have changed the research landscape, and some promise to improve clinical options in the not-distant future. There has never been a more exciting time in biomedical research, so keep an eye on how it affects the medical care your doctor is able to deliver.

1. Prime editing

Gene editing using CRISPR methods has catalyzed a huge wave of research discovery over the past decade. The clinical potential is enticing as well — can we expect a future in which genes will be edited to cure disease? The answer is yes, and it’s already happening. Sort of. A CRISPR-based therapy known as Casgevy, for sickle cell anemia, has been approved by the FDA, but it is applied to cells removed from the body, engineered in vitro, then reintroduced to the body a long and grueling process. There are challenges associated with delivering CRISPR within the body, however, and the danger of double-strand DNA breaks occurring in a wrong, off-target location of the genome has slowed its further expansion into the clinic. At the same time, researchers have continually refined and improved CRISPR editing protocols to increase safety and precision. One step forward, called prime editing, does not introduce double-stranded DNA breaks to make edits in the genome, making it a promising clinical candidate. In fact, the Rare Disease Translational Center at The Jackson Laboratory (JAX) recently received a major grant to develop prime editing approaches to cure four severe neurological diseases, with the stated goal of bringing gene editing to the clinic in the near future.

2. Accurate human immune system models

Mice are useful for biomedical research in myriad ways because they share so much of their genetics and biological traits with humans. But having evolved to fill very different niches, there are also important differences between humans and mice, and one of the less immediately obvious is how their respective immune systems work. This affects research into infectious diseases — for example, mice were unable to be infected by the original SARS-CoV-2 unless engineered to carry a human receptor — autoimmune diseases, cancer and more. As a result, researchers have worked hard to “humanize” mouse immune responses. JAX’s Lenny Shultz helped drive progress by developing the NOD scid gamma (NSG) immunodeficient mouse, into which human cells and tissues can be engrafted. Over the years the mice have been further tweaked for specific investigations and greater engraftment efficiencies. Cancer research has perhaps benefited the most, as both tumor tissue and immune cells from cancer patients can now be engrafted in patient-derived xenograft (PDX) mice, allowing for exploration of the complex interplay between cancer and the human immune response. The platform is already being used to assess treatment safety and efficacy at the individual tumor and immune system level, and it will drive further advances in cancer therapy development.

3. Better long-read sequencing

The “next-generation sequencing” explosion brought in a new era of genomics research. It was a great leap forward, but few outside the field knew the whole story behind short-read technology, which, while relatively inexpensive and accurate, requires genomes to be broken into 250 base-pair segments before they are reassembled. Short reads had limitations that led to “whole genome” sequences only containing about 90% of the sequence, and they did not detect important structural variation within every genome. Long-read technologies that address these problems have made huge strides over the past decade, and they can now cover sequences of thousands and even millions of base pairs. Recently, the “telomere to telomere” consortium published a truly whole genome sequence, and JAX’s own Charles Lee investigated the notoriously hard-to-sequence Y chromosome, revealing striking variation across 43 different individuals. The findings have far-reaching implications for human health, as diagnostic short-read sequencing still fails to produce a diagnosis a majority of the time. And structural variants (SVs), long overlooked in function and disease, are now being found to contribute to many diseases and disorders, including cancer, and can be an important finding in any clinical sequence analysis.

4. AI for data analysis

Several years ago, “big data” was a prominent buzzword. The focus was on managing big data sets, analogous to analyzing a spreadsheet with trillions of lines of numbers. But people little suspected that in 2024 such analyses would and could be performed by machine learning (ML) algorithms or the data fed into large language models (LLMs) for more varied applications. All fall under the umbrella of artificial intelligence (AI), a field that is exploding and affecting many aspects of our daily lives, whether we are aware of it or not. Biomedical research is no different, as various ML algorithms and AI methods are being applied to the ever-expanding amount of experimental data to help spot patterns, identify hidden connections and streamline discovery, including drug discovery. At JAX, I’ve written extensively about how Associate Professor Vivek Kumar, Ph.D., uses ML algorithms to analyze massive amounts of video data to gain unprecedented insight into mouse movement, behavior, sleep and other characteristics. And JAX’s wealth of data in disease research has caught the interest of technology leaders. In fact, LG AI Research will use JAX’s Alzheimer’s disease and cancer research data to train and refine its ML engine, EXAONE, with the goal of identifying actionable targets for preventive and treatment strategies.

5. Human cell lines, organoids and 3D cell cultures

In an ideal world, the best experimental platform for research into human diseases would be the human patients themselves. And it’s true that we are able to obtain a huge amount of data and insight from them, and more now than ever before. But truly experimenting with humans — to fully control variables, perturb genetic backgrounds, really dive into the molecular biology — would be wildly unethical, so we use proxies such as mice. Now, with recent advances that allow us to differentiate mature human cells into different cell types (induced pluripotent stem cells, iPSCs), create tiny facsimiles of organ function (organoids) and culture human cells in a 3D environment far more like their natural state, we can better bridge the human-mouse gap. The inherent limitations involved on both sides are not insignificant: Mice are not human, of course, and human in vitro (artificial, outside of the body) experimental platforms don’t have the systemic connections needed to fully explore many aspects of biology. But they complement each other, and JAX is working at the human-mouse interface for further discovery. For example, cell lines from human patients with neurodegeneration can better inform in vivo (within the body) mouse research, and vice versa. And 3D patient avatars for cancer are a promising research platform on which to better study tumors on a case-by-case basis.