Gazing into the scientific crystal ball

HAVE A few years ago, I interviewed a patient suffering from an aggressive form of prostate cancer to discuss his clinical trial experiences. In his search for suitable clinical trials, he thoroughly studied the scientific details behind his cancer. In this context, he mentioned how the increasingly popular immunotherapy seemed unattainable to him because it worked well for blood cancer, but ran into a wall when it came to solid tumors. At that moment, I mentally returned to a front row seat at a conference I attended a few years ago.

This conference talk was my first encounter with the concept of coating immune cells with receptors that recognize cancer cells. The presenter concluded his slides by summarizing the pros and cons of the chimeric antigen receptor (CAR) T strategy, and I noted in my notebook that this “approach seems challenging for solid tumors.” I found it fascinating that this detail came to mind—though this time from the clinic, not from the bench.

People often look at basic research as an educational exercise where scientists mess around in the lab, but it's actually at the forefront of innovation. Keeping fundamental research at the pulse allows you to witness the birth of ingenious ideas and the development of cutting-edge technologies, some of which could one day change people's lives.

Take the genome editing tool, CRISPR, for example. When this technology arrived a little over ten years ago, researchers immediately knew that this surge would spread to many spheres of application.1 So last year, when the first CRISPR-based gene therapy, Casgevy, was approved by the FDA to treat sickle cell disease and transfusion-dependent beta thalassemia, no one batted an eye. However, while many expected this significant victory, few would have guaranteed it in advance.

That's because researchers are cautiously optimistic about new advances in science and technology. Just like the game of snakes and ladders, all ideas start on a level playing field. Some make rapid progress or regress due to unexpected developments. A relatively slow research area may suddenly achieve significant milestones due to a new methodology, or an ever-evolving topic may stall if a prevailing theory is overturned.

A recent, prime example of this unpredictability is, ironically, the forecasting model. When Alpha Fold, an artificial intelligence (AI)-based model debuted about five years ago, it almost instantly gave protein biologists the boost they needed to solve a decades-old problem.2 With protein folding in order, AI applications have developed in abundance. .

Today, with increasing cross-talk among interdisciplinary researchers, if a transformative technology emerges in one field, it quickly spreads to other fields. Example: Scientists are using CRISPR to improve the potency of immune cells to treat cancer, and researchers are already trying to identify patient-specific antigens using artificial intelligence to optimize treatment.

Although I could not reliably determine a winning strategy for cancer treatment to my interlocutor at the time, I believe that each incremental positive result is a step in the right direction. Given all the uncertainty, tracking progress in basic research could feel like holding an unmarked winning lottery ticket among a thousand others. However, the good news is that no matter which idea is chosen, we all win in the end.

References

  1. Jinek M, et al. Programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science. 2012;337(6096):816-821
  2. Senior AW, et al. Improved protein structure prediction using the potential of deep learning. Nature. 2020;577:706-710.

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